Instructions:(1) Work through the pages below.(2) Use the us_demographics.jmp data table to: (a) select a continuous variable and generate a histogram
(b) select two continuous variables and determine the correlation coefficient(c) generate box plots using College Degrees as the Y, Response variable and Region as the X, Factor variable(3) Copy and paste the results for 2 (a, b, & c) in a Word document.
Histograms, Descriptive Statistics, and Stem and Leaf
Use to display and describe the distribution of continuous (numeric) variables. Histograms and stem and leaf plots allow you to quickly assess the shape, centering and spread of a distribution. For categorical (nominal or ordinal) variables, see the page on Bar Charts and Frequency Distributions.
Histograms and Descriptive Statistics
1. Open the JMP® data table us_demographics.jmp, select Analyze > Distribution.
2. Click on one of the continuous variables from Select Columns, and click Y, Columns (continuous variables have blue triangles).
3. Click OK to generate a histogram, outlier box plot and descriptive statistics.
· The percentiles, including quartiles and the median, are listed under Quantiles.
· The sample mean, standard deviation and other statistics are listed under Summary Statistics.
Example: Car Physical Data.jmp (Help > Sample Data)
Tips:
· To change the display from vertical to horizontal (as shown), click on the top red triangle and select Stack.
· To change the graphical display for a variable, or to select additional options, click on the red triangle for that variable.
· To display different summary statistics, use the red triangle next to Summary Statistics.
· To change all future output to horizontal, go to Preferences > Platforms > Distribution, click Stack and
Horizontal, then click OK.
Stem and Leaf Plot
To generate a stem and leaf plot, click on the red triangle for the variable and select Stem and Leaf.
Tips:
· A key to interpret the values is at the bottom of the plot. The top value in this example is 4300, the bottom value is 1700 (values have been rounded to the nearest 100).
· Click on values in the stem and leaf plot to select observations in both the histogram and the data table. Or, select bars in the histogram to select values in the stem and leaf plot and data table.
jmp.com/learn rev 07/2012
Use to display the distribution of continuous variables. They are also useful for comparing distributions.
Box Plots – One Variable
1. From the open JMP® data table, select Analyze > Distribution.
2. Click on another continuous variable from Select Columns, and Click Y, Columns (continuous variables have blue triangles).
3. Click OK. An outlier box plot is displayed by default next to the histogram (or above if horizontal layout). To display a quantile box plot, select the option from the red triangle for the variable.
jmp.com/learn rev 07/2012
Box Plots
The lines on the Quantile Box Plot correspond to the quantiles in the distribut.
This document provides an overview of the different graph types and options available in the InnerSoft STATS software. It describes 7 main sections of the graphs menu, including general settings, grouping cases, categorical-quantitative graphs, two categorical variables, graph sequences, candlestick/point and figure/stock graphs, and scatter plots. For each section, it lists the available graph types and statistical options. It also provides brief descriptions and settings for specific graph types like Kagi, Renko, candlestick, and point and figure charts.
Excel is a computer program used to create electronic spreadsheets. It allows users to organize data, create charts and perform calculations. Key features include conditional formatting to highlight certain cells based on values, pivot tables to analyze and summarize large datasets, and functions like SUM, AVERAGE, and IF to perform calculations on cell values. Formulas can contain relative or absolute cell references, and functions follow an order of operations to evaluate complex formulas correctly.
PAGE 1Using Microsoft Excel 2010 for Selected Tasks(Thr.docxalfred4lewis58146
PAGE
1
Using Microsoft Excel 2010 for Selected Tasks
(Throughout this document, a set of data refers to observations of just one variable.)
(1) To portray as a bar chart a given frequency, relative frequency, or percentage distribution of a set of qualitative data, one may:
With the categories in one column and the counts or proportions or percentages in another:
1. Select (by clicking-and-dragging) the counts or proportions or percentages.
2. Choose (from upper menu) Insert, then Column (for vertical bars) or Bar (for horizontal bars), then the first pictured sub-type.
3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories, click OK, and click OK.
4. Choose (from upper menu) Layout, then Axis Titles to enter appropriate labels for the horizontal and vertical axes, then Chart Title to enter an appropriate title.
5. If you wish the counts or proportions or percentages to be shown on the bars: Choose (from menu) Data Labels, then your preferred position.
(2)To portray as a pie chart a given frequency, relative frequency, or percentage distribution, one may:
With the categories or numeric classes in one column and the counts or proportions or percentages in another:
1. Select (by clicking-and-dragging) the counts or proportions or percentages.
2. Choose (from upper menu) Insert, then Pie, then the first pictured sub-type.
3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories or numeric classes, click OK, and click OK.
4. (a) Choose (from upper menu) Layout, then Data Labels, then More Data Label Options (which will by default cause each “Value”--i.e, each count or proportion or percentage selected in step 1.--to appear on or near a pie slice); (b) if you wish each category or numeric class to appear on or near a pie slice, select Category name, then your preferred position; (c) click on Close; and (d) if the legend box is now superfluous, delete it.
5. Choose (from menu) Chart Title to enter an appropriate title.
(3) Counting the number of cells (within some range of cells) satisfying a particular condition:
Examples:
· To count how many of the cells A1 through A100 contain the word Agree, one may enter in some blank cell =COUNTIF(A1:A100, “Agree”) Note: In lieu of typing in “Agree”, one may click on a cell containing the word Agree.
· To count how many of the cells A1 through A100 contain the number 89, one may enter in some blank cell =COUNTIF(A1:A100, 89) Note: In lieu of typing in 89, one may click on a cell containing the number 89.
· To count how many of the cells A1 through A100 contain a number in the interval 10 to under 20, enter in some blank cell =COUNTIF(A1:A100,”<20”)-COUNTIF(A1:A100,”<10”)
· Note: Each relative address A1:A100 above may be replaced by the absolute address $A$1:$A$100. In lieu of typing in the absolute address $A$1:$A$100, .
This document discusses graphs and how to create and modify them. It covers basic graph concepts, changing graph types and properties like data series, axes, colors and pictures. Activities demonstrate how to change bar fill colors, graph type, axis scales and remove data series. Common graph types are defined as line, pie and column graphs. Key graph elements are also identified, such as data series, labels, legends and scales. Tips are provided for graph creation, selection of non-adjacent data, formatting axis values and modifying existing graphs.
The document provides step-by-step instructions for using Eviews software to open files, examine variables, create graphs and descriptive statistics, perform regressions, and check residuals. It explains how to open Eviews and files, select variables, view spreadsheet and graph outputs, copy and paste tables and graphs, and estimate equations to analyze relationships between economic variables like GDP, unemployment, and investment. Descriptive statistics, correlations, and regression results are generated and their outputs are viewed, copied, and saved.
This document provides instructions for using a graphing calculator to perform linear regression on a dataset and find the line of best fit. It describes entering paired x and y data values into separate lists, using the LinReg(ax+b) function to determine the regression equation, optionally creating a scatter plot of the original data and regression line, and using the line equation to forecast values. As an example, it analyzes a dataset of alternative-fueled vehicles in the US from 1997 to predict the number in 2014.
Spreadsheets Introduction using RM Number MagicMalcolm Wilson
- Number Magic is a spreadsheet program that allows users to enter numerical data, perform calculations with formulas, and analyze and present data using graphs.
- It has tools for recording and analyzing data, including a topic bank for adding words and pictures, formula builder for easier calculations, and data sorting. Users can create different types of graphs to visualize information.
- The program operates at four levels of complexity and includes features like a detector for monitoring sensory data over time.
This document provides an overview of the different graph types and options available in the InnerSoft STATS software. It describes 7 main sections of the graphs menu, including general settings, grouping cases, categorical-quantitative graphs, two categorical variables, graph sequences, candlestick/point and figure/stock graphs, and scatter plots. For each section, it lists the available graph types and statistical options. It also provides brief descriptions and settings for specific graph types like Kagi, Renko, candlestick, and point and figure charts.
Excel is a computer program used to create electronic spreadsheets. It allows users to organize data, create charts and perform calculations. Key features include conditional formatting to highlight certain cells based on values, pivot tables to analyze and summarize large datasets, and functions like SUM, AVERAGE, and IF to perform calculations on cell values. Formulas can contain relative or absolute cell references, and functions follow an order of operations to evaluate complex formulas correctly.
PAGE 1Using Microsoft Excel 2010 for Selected Tasks(Thr.docxalfred4lewis58146
PAGE
1
Using Microsoft Excel 2010 for Selected Tasks
(Throughout this document, a set of data refers to observations of just one variable.)
(1) To portray as a bar chart a given frequency, relative frequency, or percentage distribution of a set of qualitative data, one may:
With the categories in one column and the counts or proportions or percentages in another:
1. Select (by clicking-and-dragging) the counts or proportions or percentages.
2. Choose (from upper menu) Insert, then Column (for vertical bars) or Bar (for horizontal bars), then the first pictured sub-type.
3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories, click OK, and click OK.
4. Choose (from upper menu) Layout, then Axis Titles to enter appropriate labels for the horizontal and vertical axes, then Chart Title to enter an appropriate title.
5. If you wish the counts or proportions or percentages to be shown on the bars: Choose (from menu) Data Labels, then your preferred position.
(2)To portray as a pie chart a given frequency, relative frequency, or percentage distribution, one may:
With the categories or numeric classes in one column and the counts or proportions or percentages in another:
1. Select (by clicking-and-dragging) the counts or proportions or percentages.
2. Choose (from upper menu) Insert, then Pie, then the first pictured sub-type.
3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories or numeric classes, click OK, and click OK.
4. (a) Choose (from upper menu) Layout, then Data Labels, then More Data Label Options (which will by default cause each “Value”--i.e, each count or proportion or percentage selected in step 1.--to appear on or near a pie slice); (b) if you wish each category or numeric class to appear on or near a pie slice, select Category name, then your preferred position; (c) click on Close; and (d) if the legend box is now superfluous, delete it.
5. Choose (from menu) Chart Title to enter an appropriate title.
(3) Counting the number of cells (within some range of cells) satisfying a particular condition:
Examples:
· To count how many of the cells A1 through A100 contain the word Agree, one may enter in some blank cell =COUNTIF(A1:A100, “Agree”) Note: In lieu of typing in “Agree”, one may click on a cell containing the word Agree.
· To count how many of the cells A1 through A100 contain the number 89, one may enter in some blank cell =COUNTIF(A1:A100, 89) Note: In lieu of typing in 89, one may click on a cell containing the number 89.
· To count how many of the cells A1 through A100 contain a number in the interval 10 to under 20, enter in some blank cell =COUNTIF(A1:A100,”<20”)-COUNTIF(A1:A100,”<10”)
· Note: Each relative address A1:A100 above may be replaced by the absolute address $A$1:$A$100. In lieu of typing in the absolute address $A$1:$A$100, .
This document discusses graphs and how to create and modify them. It covers basic graph concepts, changing graph types and properties like data series, axes, colors and pictures. Activities demonstrate how to change bar fill colors, graph type, axis scales and remove data series. Common graph types are defined as line, pie and column graphs. Key graph elements are also identified, such as data series, labels, legends and scales. Tips are provided for graph creation, selection of non-adjacent data, formatting axis values and modifying existing graphs.
The document provides step-by-step instructions for using Eviews software to open files, examine variables, create graphs and descriptive statistics, perform regressions, and check residuals. It explains how to open Eviews and files, select variables, view spreadsheet and graph outputs, copy and paste tables and graphs, and estimate equations to analyze relationships between economic variables like GDP, unemployment, and investment. Descriptive statistics, correlations, and regression results are generated and their outputs are viewed, copied, and saved.
This document provides instructions for using a graphing calculator to perform linear regression on a dataset and find the line of best fit. It describes entering paired x and y data values into separate lists, using the LinReg(ax+b) function to determine the regression equation, optionally creating a scatter plot of the original data and regression line, and using the line equation to forecast values. As an example, it analyzes a dataset of alternative-fueled vehicles in the US from 1997 to predict the number in 2014.
Spreadsheets Introduction using RM Number MagicMalcolm Wilson
- Number Magic is a spreadsheet program that allows users to enter numerical data, perform calculations with formulas, and analyze and present data using graphs.
- It has tools for recording and analyzing data, including a topic bank for adding words and pictures, formula builder for easier calculations, and data sorting. Users can create different types of graphs to visualize information.
- The program operates at four levels of complexity and includes features like a detector for monitoring sensory data over time.
This document provides instructions for inserting and formatting charts in PowerPoint. It discusses how to insert a chart, enter data, change the chart type and style, modify the chart layout, and format specific elements. Charts are a visual way to represent data and make comparisons and trends easy to understand. The instructions cover the basic chart elements like the title, legend, and axes, and how to modify these elements using the Design, Layout, and Format tabs.
This document provides instructions for creating and modifying charts in Excel. It explains how to insert a chart using selected data, identify the different parts of a chart, change the chart type and layout, apply styles, and move the chart to a different worksheet. The goal is to teach the reader how to use charts effectively to visually communicate data trends and comparisons from a spreadsheet.
This document provides an introduction and guidelines for applied statistics and statistical methods. It discusses topics like data handling, file handling, and graphs. For data handling, it describes how to recode variables into different groups and compute new variables using algebraic functions of existing variables. For file handling, it discusses how to select only certain cases, such as males, and split a file into groups. Finally, it demonstrates how to create histograms and boxplots to explore the distribution of variable scores and identify any outliers in the data.
The document provides instructions for customizing charts created from data in a Word spreadsheet. It describes how to change chart styles, colors, and formatting of data series; modify row and column headings; and experiment with different chart types, labels, legends, and views. The goal is to familiarize the user with various options for visualizing and presenting spreadsheet data visually through charts in Word.
This document provides instructions for creating various charts and graphs in Microsoft Excel 2003, including column graphs, pie charts, organization charts, and flowcharts. It describes how to select and format data, use the chart wizard to generate different chart types, customize chart elements, and insert charts into Word documents. Steps are outlined for selecting data ranges, adding titles and labels, changing background and text formatting, and printing or sharing charts. Organization charts and flowcharts can also be created using shapes and connectors on the drawing toolbar.
This document discusses how to work with charts in Excel. It explains that charts allow audiences to more easily understand numbers in a spreadsheet by making comparisons and trends visual. It then provides instructions for inserting and modifying charts, including how to identify the different parts of a chart, change the chart type and layout, apply styles, and move the chart to another worksheet. The goal is to demonstrate how charts can be an effective tool for communicating data.
The document provides step-by-step instructions for conducting various statistical analyses in SPSS, including frequency distributions, histograms, frequency polygons, measures of central tendency (mode, median, mean), measures of variability (range, variance, standard deviation), standard scores (z-scores and t-scores). It explains how to produce and interpret the outputs for each analysis in 3 sentences or less.
A chart is a tool used to communicate data graphically. This lesson teaches how to insert and modify charts in PowerPoint, including changing chart types, editing source data, formatting styles and layouts. The key parts of a chart are the source data, title, legend, and axes. Formatting options allow customizing the visual aspects and specific areas of charts.
A chart is a tool used to communicate data graphically. This lesson teaches how to insert and modify charts in PowerPoint, including changing chart types, editing source data, formatting styles and layouts. The key parts of a chart are the source data, title, legend, and axes. Formatting options allow customizing the visual aspects and specific areas of charts.
The 7 basic quality tools through minitab 18RAMAR BOSE
The document provides an overview of creating and customizing control charts in Minitab. It explains how to create an I-MR chart and Xbar-R chart from sample data files, including how to select test criteria, format scales and axes, and add reference lines. The document also provides general information about when to use control charts and considerations for the type of data needed to create these charts.
MAT 240 Random Sampling in Excel Tutorial This tutorial wiAbramMartino96
MAT 240 Random Sampling in Excel Tutorial
This tutorial will guide you though the steps necessary to collect a random sample of a data set to put on
a new sheet.
1. Open your data set in Excel. Be sure the Analysis toolpak is enabled. Steps for how to do this are
available on the Microsoft support site.
2. To find a random sample, you first need to insert the =rand() function an empty column next to
your data. In the example being shown, it is column G. To do this, select the target cell and type
in =rand() then press enter.
3. Double click the Fill handle (little square icon) at the bottom right side of the highlighted cell to
copy the formula through to the bottom of the data set. This will copy this formula to each row
of data.
4. Sort your new column to rearrange the data into a random order. To do this, select the data
within your column, then click the Sort & Filter button from the Home ribbon and choose Sort
https://support.microsoft.com/en-us/office/load-the-analysis-toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4
Smallest to Largest.
5. A dialog box will open asking if you what you want to do. Select to Expand the selection and
click Sort.
6. Capture your sample size by selecting the amount of rows you are sampling. A sample of 50
would mean you should select the first 50 rows of data.
a. By selecting only the first cell of data in the first column and dragging down, Excel will
count the number of rows for you.
b. Once you have the correct number of rows, then drag to the right to highlight all the
data in the appropriate number of rows.
7. Cut and paste this selected data set onto a new sheet and you will have your random sample
separated from the main data set.
8. In the Descriptive statistics window, select input range field, then select all your numerical data
9. Then check the Summary Statistics box and click ok
10. You now should see a new sheet with just your descriptive statistics listed in a chart. Change the
titles of the columns to their respective names from your data: median listing price, median dollars
per square foot, median square feet. And remove any extraneous information that is not needed for
this project.
MAT 240 Random Sampling in Excel Tutorial
MAT 240 Scatterplots in Excel Tutorial
This tutorial will guide you though the steps necessary to create scatterplots using your data. It will also
walk you through inserting a linear trend line and inserting the regression equation and the R-squared
value on the chart.
1. Open your data set in Excel.
2. Select all the data for the two variables you are targeting. (example: median listing price & Median
square feet)
a. Tip: holding down the CTRL button while selecting your data will allow you to select two
columns of data that are not next to each other
3. On the Insert tab select Recommended Charts button
4. This will bring up the insert chart dialog box prompting you to ...
MAT 240 Random Sampling in Excel Tutorial This tutorial wiAbramMartino96
MAT 240 Random Sampling in Excel Tutorial
This tutorial will guide you though the steps necessary to collect a random sample of a data set to put on
a new sheet.
1. Open your data set in Excel. Be sure the Analysis toolpak is enabled. Steps for how to do this are
available on the Microsoft support site.
2. To find a random sample, you first need to insert the =rand() function an empty column next to
your data. In the example being shown, it is column G. To do this, select the target cell and type
in =rand() then press enter.
3. Double click the Fill handle (little square icon) at the bottom right side of the highlighted cell to
copy the formula through to the bottom of the data set. This will copy this formula to each row
of data.
4. Sort your new column to rearrange the data into a random order. To do this, select the data
within your column, then click the Sort & Filter button from the Home ribbon and choose Sort
https://support.microsoft.com/en-us/office/load-the-analysis-toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4
Smallest to Largest.
5. A dialog box will open asking if you what you want to do. Select to Expand the selection and
click Sort.
6. Capture your sample size by selecting the amount of rows you are sampling. A sample of 50
would mean you should select the first 50 rows of data.
a. By selecting only the first cell of data in the first column and dragging down, Excel will
count the number of rows for you.
b. Once you have the correct number of rows, then drag to the right to highlight all the
data in the appropriate number of rows.
7. Cut and paste this selected data set onto a new sheet and you will have your random sample
separated from the main data set.
8. In the Descriptive statistics window, select input range field, then select all your numerical data
9. Then check the Summary Statistics box and click ok
10. You now should see a new sheet with just your descriptive statistics listed in a chart. Change the
titles of the columns to their respective names from your data: median listing price, median dollars
per square foot, median square feet. And remove any extraneous information that is not needed for
this project.
MAT 240 Random Sampling in Excel Tutorial
MAT 240 Scatterplots in Excel Tutorial
This tutorial will guide you though the steps necessary to create scatterplots using your data. It will also
walk you through inserting a linear trend line and inserting the regression equation and the R-squared
value on the chart.
1. Open your data set in Excel.
2. Select all the data for the two variables you are targeting. (example: median listing price & Median
square feet)
a. Tip: holding down the CTRL button while selecting your data will allow you to select two
columns of data that are not next to each other
3. On the Insert tab select Recommended Charts button
4. This will bring up the insert chart dialog box prompting you to ...
SimplyMap is a web-based mapping application that allows both technical and non-technical users to create thematic maps and reports using demographic, business, and marketing data. This guide provides instructions on how to get started with SimplyMap, including how to create new maps and reports using wizard tutorials or manually by selecting locations and variables. It also explains how to export maps and reports for use in other programs or for sharing.
A Skills Approach Excel 2016 Chapter 7 Exploring Advanced C.docxdaniahendric
A Skills Approach: Excel 2016 Chapter 7: Exploring Advanced Charts
and Graphics
1 | Page Skill Review 7.1 Last Updated 2/9/18
Skill Review 7.1
In this project, you will analyze U.S. population growth over the last 40 years.
Skills needed to complete this project:
• Applying Quick Styles and Other Formatting to Sparklines
• Changing the Sparkline Type
• Adding Markers to Sparklines
• Adding a Data Series to a Chart
• Creating a Combination Chart
• Formatting Other Chart Elements
• Formatting a Data Point or a Data Series
• Creating a Chart Template
• Inserting a Shape
• Applying Quick Styles and Other Formatting to Shapes
• Applying a Chart Template
• Adding and Removing Trendlines
• Forecasting Values on a Trendline
• Changing Trendline Options
1. Open the start file EX2016-SkillReview-7-1. The file will be renamed automatically to include your
name. Change the project file name if directed to do so by your instructor, and save it.
2. If the workbook opens in Protected View, click the Enable Editing button in the Message Bar at the
top of the workbook so you can modify the workbook.
3. Add Sparklines to the data and apply a Quick Style.
a. On the Population Data worksheet, select cells B4:F13.
b. On the Insert tab, in the Sparklines group, click the Column button.
c. In the Create Sparklines dialog, verify that B4:F13 is the Data Range and specify G4:G13 as the Location
Range. Click OK.
d. On the Sparkline Tools Design tab, in the Style group, apply the Dark Blue, Sparkline Style Dark #6 style.
Click the More button to expand the gallery, then click the first style from the right in the fifth row.
4. Change the Sparklines to lines with markers for all data points and highlight the high point marker in a
different color.
a. On the Sparkline Tools Design tab, in the Type group, click the Line button.
b. On the Sparkline Tools Design tab, in the Show group, click the Markers check box.
c. On the Sparkline Tools Design tab, in the Style group, click the Marker Color button, point to High
Point, and select Red (the second color from the left in the row of standard colors).
5. Create a column chart to represent the population data for Dallas and then add a second series to
represent the overall population of the United States.
a. Select cells A3:F3. Press [Ctrl] and click and drag to select cells A12:F12.
Step 1
Download
start file
A Skills Approach: Excel 2016 Chapter 7: Exploring Advanced Charts
and Graphics
2 | Page Skill Review 7.1 Last Updated 2/9/18
b. On the Insert tab, in the Charts group, click the Column or Bar Chart button, and choose Clustered
Column (the first chart type under 2‐D Column).
c. Click and drag the chart to reposition it immediately below the data.
d. On the Chart Tools Design tab, in the Data group, click the Select Data button.
e. In the Legend Entries (Series) box, click the Add button.
f. Click cell A15 to add ...
This document discusses graphs that can effectively and objectively summarize data versus graphs that can potentially mislead or deceive the viewer. Effective graphs discussed include dot plots, stem-and-leaf plots, time-series graphs, bar graphs, Pareto charts, pie charts, histograms, frequency polygons and ogives. Potentially deceptive graphs discussed are those that do not start the vertical axis at zero, exaggerating differences, and pictographs that depict one-dimensional data with multi-dimensional objects.
The document discusses various data analysis and visualization techniques in Microsoft Excel including filtering, sorting, formulas, functions, pivot tables, charts and conditional formatting. It provides step-by-step instructions on how to use these tools to extract insights from data by filtering to select specific records, using formulas and functions to perform calculations, sorting data, validating data entry, creating pivot tables and pivot charts to summarize data, and formatting cells based on conditions.
This presentation educates you about Tableau - Line Chart and its types Simple Line Chart, Multiple Measure Line Chart and Line Chart with Label with example charts.
For more topics stay tuned with Learnbay.
Excel provides tools for graphing, analyzing, and formatting data. Key capabilities include:
1) Creating scatter plots and adding trendlines to show regression. The layout ribbon customizes graphs by adding titles, labels, and legends.
2) Performing calculations using functions and applying formulas down columns. Formatting options include number of decimals and scientific notation.
3) Adding error bars to express uncertainty in data on graphs. Both horizontal and vertical error bars can be customized.
We would like to introduce sampling software which costs just 10 USD. Sampling is statistical software designed to calculate sampling computation easily such as stratified sampling, cluster sampling, sampling with varying probability and etc. You can download free 7 times running trial license here:
http://www.sampling-software.com
InstructionsW4 Nightingale Case A & B – 35 points - Individual A.docxdirkrplav
Instructions
W4 Nightingale Case A & B – 35 points - Individual Assignment
As indicated in the syllabus, it is important to demonstrate knowledge of MS Project. Week 4 includes using the software and interpreting the results as follows:
1. Read the Nightingale Project - LG textbook pg 333-335
2. Review MS Project Video Tutorials (Lessons/Course Materials/Support Videos) and complete the Case for both Part A and Case Part B.
3. Submit two separate MS Project .mpp files (one for part A and one for part B). Remember to submit the appropriate “view” reflecting all applicable columns and content information.
4. Submit MS Word file to specifically answer all questions for both parts (part A questions 1-3 & part B questions 1-4).
5. Ensure you document the version of MS Project you are using in the submission comments field.
Hints:
You should read ALL instructions in the case and case technical details before you start the Project file.
You may want to set up the Project file ex: start date, holidays, work days, etc. before entering in any tasks.
Ensure the project name is on the first line of the Project file and all other tasks as detailed in the case are indented just once.
The predecessor numbers for all subtasks will then be one higher than in the text as the first line (main task) is now the Project name.
The lag mentioned in the case A section is plus lag.
analyze certain bodily substances and compare them widi a sample from a suspect.
Forensic science consultant Richard Saferstein tells us that portions of the DNA structure are as unique to each individual as fingerprints. He writes that inside each of the 60 trillion cells in the human body are strands of genetic material called chromosomes. Arranged along the chromosomes, like beads on a thread, are nearly 100,000 genes. Genes are the fundamental unit of heredity. They instruct the body cells to make proteins drat determine everydiing from hair color to susceptibility to diseases. Each gene is actually composed of DNA specifically designed to carry out a single body function. Scientists have determined that DNA is die substance by which genetic instructions are passed from one generation to the next. (Saferstein 353-394)
DNA profiling has helped investigators solve crimes and ensure that diose guilty of crimes are convicted in court. Profiling is the examination of DNA samples from a body substance or fluid to determine whether they came from a particular subject. For example, semen on a rape victim's clothing can be positively or negatively compared with a suspect's semen.
police laboratories. Smaller departments may contract with large county crime labs or state police crime labs. Some departments use die services of the FBI lab. (Durose 1)
Private (nongovernment) labs are taking on greater importance in the U.S. legal system. Their analyses are increasingly being introduced into criminal and civil trials, often not only as evidence but also to contradict evidence presented by .
InstructionsView CAAE Stormwater video Too Big for Our Ditches.docxdirkrplav
Instructions:
View CAAE Stormwater video "Too Big for Our Ditches"
http://www.ncsu.edu/wq/videos/stormwater%20video/SWvideo.html
Explain how impermeable surfaces in the urban environment impact the stream network in a river basin. Why is watershed management an important consideration in urban planning? Unload you essay (200-400 words).
Neal.LarryBUS457A7.docx
Question 1
Problem:
It is not certain about the relationship between age, Y, as a function of systolic blood pressure.
Goal:
To establish the relationship between age Y, as a function of systolic blood pressure.
Finding/Conclusion:
Based on the available data, the relationship is obtained and shown below:
Regression Analysis: Age versus SBP
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 2933 2933.1 21.33 0.000
SBP 1 2933 2933.1 21.33 0.000
Error 28 3850 137.5
Lack-of-Fit 21 2849 135.7 0.95 0.575
Pure Error 7 1002 143.1
Total 29 6783
Model Summary
S R-sq R-sq(adj) R-sq(pred)
11.7265 43.24% 41.21% 3.85%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -18.3 13.9 -1.32 0.198
SBP 0.4454 0.0964 4.62 0.000 1.00
Regression Equation
Age = -18.3 + 0.4454 SBP
It is found that there is an outlier in the dataset, which significantly affect the regression equation. As a result, the outlier is removed, and the regression analysis is run again.
Regression Analysis: Age versus SBP
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 4828.5 4828.47 66.81 0.000
SBP 1 4828.5 4828.47 66.81 0.000
Error 27 1951.4 72.27
Lack-of-Fit 20 949.9 47.49 0.33 0.975
Pure Error 7 1001.5 143.07
Total 28 6779.9
Model Summary
S R-sq R-sq(adj) R-sq(pred)
8.50139 71.22% 70.15% 66.89%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -59.9 12.9 -4.63 0.000
SBP 0.7502 0.0918 8.17 0.000 1.00
Regression Equation
Age = -59.9 + 0.7502 SBP
The p-value for the model is 0.000, which implies that the model is significant in the prediction of Age. The R-square of the model is 70.2%, implies that 70.2% of variation in age can be explained by the model
Recommendation:
The regression model Age = -59.9 +0.7502 SBP can be used to predict the Age, such that over 70% of variation in Age can be explained by the model.
Question 2
Problem:
It is not sure that whether the factors X1 to X4 which represents four different success factors have any influences on the annual savings as a result of CRM implementation.
Goal:
To determine which of the success factors are most significant in the prediction of a successful CRM program, and develop the corresponding model for the prediction of CRM savings.
Finding/Conclusion:
Based on the available da.
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This document provides instructions for creating various charts and graphs in Microsoft Excel 2003, including column graphs, pie charts, organization charts, and flowcharts. It describes how to select and format data, use the chart wizard to generate different chart types, customize chart elements, and insert charts into Word documents. Steps are outlined for selecting data ranges, adding titles and labels, changing background and text formatting, and printing or sharing charts. Organization charts and flowcharts can also be created using shapes and connectors on the drawing toolbar.
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MAT 240 Random Sampling in Excel Tutorial This tutorial wiAbramMartino96
MAT 240 Random Sampling in Excel Tutorial
This tutorial will guide you though the steps necessary to collect a random sample of a data set to put on
a new sheet.
1. Open your data set in Excel. Be sure the Analysis toolpak is enabled. Steps for how to do this are
available on the Microsoft support site.
2. To find a random sample, you first need to insert the =rand() function an empty column next to
your data. In the example being shown, it is column G. To do this, select the target cell and type
in =rand() then press enter.
3. Double click the Fill handle (little square icon) at the bottom right side of the highlighted cell to
copy the formula through to the bottom of the data set. This will copy this formula to each row
of data.
4. Sort your new column to rearrange the data into a random order. To do this, select the data
within your column, then click the Sort & Filter button from the Home ribbon and choose Sort
https://support.microsoft.com/en-us/office/load-the-analysis-toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4
Smallest to Largest.
5. A dialog box will open asking if you what you want to do. Select to Expand the selection and
click Sort.
6. Capture your sample size by selecting the amount of rows you are sampling. A sample of 50
would mean you should select the first 50 rows of data.
a. By selecting only the first cell of data in the first column and dragging down, Excel will
count the number of rows for you.
b. Once you have the correct number of rows, then drag to the right to highlight all the
data in the appropriate number of rows.
7. Cut and paste this selected data set onto a new sheet and you will have your random sample
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8. In the Descriptive statistics window, select input range field, then select all your numerical data
9. Then check the Summary Statistics box and click ok
10. You now should see a new sheet with just your descriptive statistics listed in a chart. Change the
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this project.
MAT 240 Random Sampling in Excel Tutorial
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This tutorial will guide you though the steps necessary to create scatterplots using your data. It will also
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value on the chart.
1. Open your data set in Excel.
2. Select all the data for the two variables you are targeting. (example: median listing price & Median
square feet)
a. Tip: holding down the CTRL button while selecting your data will allow you to select two
columns of data that are not next to each other
3. On the Insert tab select Recommended Charts button
4. This will bring up the insert chart dialog box prompting you to ...
MAT 240 Random Sampling in Excel Tutorial This tutorial wiAbramMartino96
MAT 240 Random Sampling in Excel Tutorial
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2. To find a random sample, you first need to insert the =rand() function an empty column next to
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copy the formula through to the bottom of the data set. This will copy this formula to each row
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https://support.microsoft.com/en-us/office/load-the-analysis-toolpak-in-excel-6a63e598-cd6d-42e3-9317-6b40ba1a66b4
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7. Cut and paste this selected data set onto a new sheet and you will have your random sample
separated from the main data set.
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A Skills Approach: Excel 2016 Chapter 7: Exploring Advanced Charts
and Graphics
1 | Page Skill Review 7.1 Last Updated 2/9/18
Skill Review 7.1
In this project, you will analyze U.S. population growth over the last 40 years.
Skills needed to complete this project:
• Applying Quick Styles and Other Formatting to Sparklines
• Changing the Sparkline Type
• Adding Markers to Sparklines
• Adding a Data Series to a Chart
• Creating a Combination Chart
• Formatting Other Chart Elements
• Formatting a Data Point or a Data Series
• Creating a Chart Template
• Inserting a Shape
• Applying Quick Styles and Other Formatting to Shapes
• Applying a Chart Template
• Adding and Removing Trendlines
• Forecasting Values on a Trendline
• Changing Trendline Options
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2. If the workbook opens in Protected View, click the Enable Editing button in the Message Bar at the
top of the workbook so you can modify the workbook.
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b. On the Insert tab, in the Sparklines group, click the Column button.
c. In the Create Sparklines dialog, verify that B4:F13 is the Data Range and specify G4:G13 as the Location
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a. On the Sparkline Tools Design tab, in the Type group, click the Line button.
b. On the Sparkline Tools Design tab, in the Show group, click the Markers check box.
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a. Select cells A3:F3. Press [Ctrl] and click and drag to select cells A12:F12.
Step 1
Download
start file
A Skills Approach: Excel 2016 Chapter 7: Exploring Advanced Charts
and Graphics
2 | Page Skill Review 7.1 Last Updated 2/9/18
b. On the Insert tab, in the Charts group, click the Column or Bar Chart button, and choose Clustered
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Instructions
W4 Nightingale Case A & B – 35 points - Individual Assignment
As indicated in the syllabus, it is important to demonstrate knowledge of MS Project. Week 4 includes using the software and interpreting the results as follows:
1. Read the Nightingale Project - LG textbook pg 333-335
2. Review MS Project Video Tutorials (Lessons/Course Materials/Support Videos) and complete the Case for both Part A and Case Part B.
3. Submit two separate MS Project .mpp files (one for part A and one for part B). Remember to submit the appropriate “view” reflecting all applicable columns and content information.
4. Submit MS Word file to specifically answer all questions for both parts (part A questions 1-3 & part B questions 1-4).
5. Ensure you document the version of MS Project you are using in the submission comments field.
Hints:
You should read ALL instructions in the case and case technical details before you start the Project file.
You may want to set up the Project file ex: start date, holidays, work days, etc. before entering in any tasks.
Ensure the project name is on the first line of the Project file and all other tasks as detailed in the case are indented just once.
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The lag mentioned in the case A section is plus lag.
analyze certain bodily substances and compare them widi a sample from a suspect.
Forensic science consultant Richard Saferstein tells us that portions of the DNA structure are as unique to each individual as fingerprints. He writes that inside each of the 60 trillion cells in the human body are strands of genetic material called chromosomes. Arranged along the chromosomes, like beads on a thread, are nearly 100,000 genes. Genes are the fundamental unit of heredity. They instruct the body cells to make proteins drat determine everydiing from hair color to susceptibility to diseases. Each gene is actually composed of DNA specifically designed to carry out a single body function. Scientists have determined that DNA is die substance by which genetic instructions are passed from one generation to the next. (Saferstein 353-394)
DNA profiling has helped investigators solve crimes and ensure that diose guilty of crimes are convicted in court. Profiling is the examination of DNA samples from a body substance or fluid to determine whether they came from a particular subject. For example, semen on a rape victim's clothing can be positively or negatively compared with a suspect's semen.
police laboratories. Smaller departments may contract with large county crime labs or state police crime labs. Some departments use die services of the FBI lab. (Durose 1)
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Instructions:
View CAAE Stormwater video "Too Big for Our Ditches"
http://www.ncsu.edu/wq/videos/stormwater%20video/SWvideo.html
Explain how impermeable surfaces in the urban environment impact the stream network in a river basin. Why is watershed management an important consideration in urban planning? Unload you essay (200-400 words).
Neal.LarryBUS457A7.docx
Question 1
Problem:
It is not certain about the relationship between age, Y, as a function of systolic blood pressure.
Goal:
To establish the relationship between age Y, as a function of systolic blood pressure.
Finding/Conclusion:
Based on the available data, the relationship is obtained and shown below:
Regression Analysis: Age versus SBP
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 2933 2933.1 21.33 0.000
SBP 1 2933 2933.1 21.33 0.000
Error 28 3850 137.5
Lack-of-Fit 21 2849 135.7 0.95 0.575
Pure Error 7 1002 143.1
Total 29 6783
Model Summary
S R-sq R-sq(adj) R-sq(pred)
11.7265 43.24% 41.21% 3.85%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -18.3 13.9 -1.32 0.198
SBP 0.4454 0.0964 4.62 0.000 1.00
Regression Equation
Age = -18.3 + 0.4454 SBP
It is found that there is an outlier in the dataset, which significantly affect the regression equation. As a result, the outlier is removed, and the regression analysis is run again.
Regression Analysis: Age versus SBP
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 4828.5 4828.47 66.81 0.000
SBP 1 4828.5 4828.47 66.81 0.000
Error 27 1951.4 72.27
Lack-of-Fit 20 949.9 47.49 0.33 0.975
Pure Error 7 1001.5 143.07
Total 28 6779.9
Model Summary
S R-sq R-sq(adj) R-sq(pred)
8.50139 71.22% 70.15% 66.89%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -59.9 12.9 -4.63 0.000
SBP 0.7502 0.0918 8.17 0.000 1.00
Regression Equation
Age = -59.9 + 0.7502 SBP
The p-value for the model is 0.000, which implies that the model is significant in the prediction of Age. The R-square of the model is 70.2%, implies that 70.2% of variation in age can be explained by the model
Recommendation:
The regression model Age = -59.9 +0.7502 SBP can be used to predict the Age, such that over 70% of variation in Age can be explained by the model.
Question 2
Problem:
It is not sure that whether the factors X1 to X4 which represents four different success factors have any influences on the annual savings as a result of CRM implementation.
Goal:
To determine which of the success factors are most significant in the prediction of a successful CRM program, and develop the corresponding model for the prediction of CRM savings.
Finding/Conclusion:
Based on the available da.
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Instructions
Use and add the real life situation provided below to write this paper. Provide examples to explain the behaviors, and use researched material to support your reasoning.
(Real life situation)
Gender Inequality in the Workplace: Sexual Harassment against Women
Although many women have been confident enough to report sexual harassment in the workplace, it is still very hard and uncomfortable for other women to stand up and also makes it more surprising how many of these incidences are still taking place every day. Workplace sexual harassment goes for both genders and it’s even harder for men since they are always viewed as the aggressors and superior gender and the mindset of our society shapes a lot of what we perceive is okay and normal behavior towards each other.
One interesting experience I heard of recently was involving a female service member and her superiors. This female works in an office with about four other males who are very aware about her feelings towards the behavior of her superior who happens to work outside of that specific office. The superior officer comes in everyday to check up on their work, make small talk with the guys and also has a habit of always rubbing her shoulders when he walks over to her desk. She explains that the first time it happened she thought it was odd being that she doesn’t have that type of relationship with him and gave him a pass, but then it became a an everyday thing. She tried tactics such as getting up from her desk, walking away from him and even voiced to the other males how uncomfortable it made her; they thought it was funny. They too had a complaint about him on making them feel uncomfortable: he had a habit of grabbing and scratching his private parts; but accepted it as a guy thing and would be viewed in a negative way if they reported. Her reason for not reporting was because she was afraid to get him in trouble, he had a family and wouldn’t dare to jeopardize his career, or even worse be criticized for making a big deal out of nothing after all its just a shoulder rub.
Required Elements:
· Describe the situation in detail; already mentioned above;
· Analyze the differences in communication, problem-solving, and leadership between the men and the women in the situation;
· Did any stereotypical notions seem to influence the behaviors of the women and the men involved in the situation? If so, explain what were they? If not, indicate so.
· Identify challenges related to gender in the situation described.
· Identify best practices that address the challenges identified.
· Devise three to five action plans that could be implemented to strengthen the behaviors of men and women in the workplace. Action plans can be implements by HR, a management or manager, CEO, or employee. Make sure to provide ideas as to why the action plan is necessary or would be useful in the workplace.
· Do not offer o.
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Instructions:
This assignment will be checked using anti-plagiarism software and returned to your instructor with an originality report.
After Completion of Lab 2, Students Must complete a one page paper on a topic of their choice from the material covered in Lab 2.
It should include your name and a topic title.
It should be 1 page, 12 pt font, double spaced.
References (with whatever format you are comfortable using)should be included at the end of your paper.
This assignment is due by the Sunday, 15 November, at 11:55pm MST. (Students with Makeup Lab approval will complete the assignment after Makeup Lab).
Please attach using one of the following formats (.doc .pdf or .txt)
Turn the paper into the "Exams, Lab Reports and Research Paper" Link For Lab 1 Report.
Grading Criteria:
Lab Report Must be at least one page. (-5 for shortness of submission).
Additional page with References (use reference format you are familiar using) (-5 for no references).
Lab Report must explain how topic is discovered, developed, and applied....not a restatement of the Lab Activity. (-5 for explaining the Lab Activity).
Turn in your Report on time. (- 5 points deducted per week for late submissions!!! )
Choose ONE of the following topics:
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-Rainbow.
-Blue Sky.
-Interference.
-Polarizers.
-Ultraviolet Light.
-Infrared Light. (IR).
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“When you’re a Spy, your job title can be anything, from Manager to Waiter, even criminal. The reason for the multitude of names? As a Spy, your job is to gather information from a range of sources, and you need to do it in any way you can. That includes putting on a disguise.
There are a few different paths that you can take to get into this career, and you can focus on a range of specialties, from technical to languages. The title “Spy” isn’t really used anymore. Instead, you’re now called a Covert Investigator or, more broadly, a CIA Agent. Whatever the title, it means you investigate and protect US interests abroad.
You investigate things like terrorism, fraud, corrupt governments, and a wide variety of other crimes. Your job is to keep Policymakers and the President of the United States aware and informed on the happenings around the world.
You can find the information you need in a lot of different ways. You might get to go undercover and pretend to be a different person, but for the most part, your job is much more routine. You carry out interviews with informants and allied Agents, analyze data, and read through research. You look for possible international problems, such as civil unrest, war, famine—anything that can cause problems for the United States.
This job involves a lot of collaboration and communication. You work with other Agents, international police forces, or informants. The informants you work with are usually average people, so the ability to speak their language is a big plus.”.
instructionss.docxjust to make sure againi need u to ext.docxdirkrplav
This document provides instructions to extend a report on the design and analysis of electrical power transmission towers from 40 to 65 pages by adding several new chapters and sections. It then provides the content for these new sections, including expanding the literature review, conclusions and recommendations section. It also includes the content for a sample transmission tower design project report, providing details on the introduction, aims, loads on towers, literature review, analysis and design of a sample 220kV transmission tower.
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Instructions:
Provide an analysis of the affects of the publics widespread interest on televised crime dramas on the manner that the criminal justice system is administered.
1 page in length
12 pt font
Double Spaced
Arial or Times New Roman
APA formatted references for any quoted or paraphrased material
.
This document contains instructions for an open book exam with multiple choice and word problems related to statistics. It provides 14 questions testing concepts like types of statistical tests to use for different data, hypotheses for statistical tests, interpreting statistical output, and correctly identifying variables and appropriate statistical analyses for different datasets. Datasets are provided in separate tabs for questions requiring calculations and analysis of real data.
InstructionsPlease answer the following question in a minimum.docxdirkrplav
Instructions:
Please answer the following question in a minimum of 500 words. Be sure to include 2 citations.
Question:
On August 31, 2010, Chickasaw Industries issued $25 million of its 30-year, 6% convertible bonds dated August 31, priced to yield 5%. The bonds are convertible at the option of the investors into 1,500,000 shares of Chickasaw's common stock. Chickasaw records interest expense at the effective rate. On August 31, 2013, investors in Chickasaw's convertible bonds tendered 20% of the bonds for conversion into common stock that had a market value of $20 per share on the date of the conversion. On January 1, 2012, Chickasaw Industries issued $40 million of its 20-year, 7% bonds dated January 1 at a price to yield 8%. On December 31, 2013, the bonds were extinguished early through acquisition in the open market by Chickasaw for $40.5 million.
Required:
1.
Using the book value method, would recording the conversion of the 6% convertible bonds into common stock affect earnings? If so, by how much? Would earnings be affected if the market value method is used? If so, by how much?
2.
Were the 7% bonds issued at face value, at a discount, or at a premium? Explain.
3.
Would the amount of interest expense for the 7% bonds be higher in the first year or second year of the term to maturity? Explain.
4.
How should gain or loss on early extinguishment of debt be determined? Does the early extinguishment of the 7% bonds result in a gain or loss? Explain.
Statistics Questions to Answer.doc.rtf
2
*Note: An Excel Workbook has also been uploaded. Within that workbook are 8 XLS files which are included in 8 separate tabs. These files will be needed to answer most of the questions.This work is due Friday, September 19th
Q1)Fill in the blanks (show your work).
Variable
N
Mean
Median
TrMean
StDev
haircut
171
23.17
17.00
21.14
18.20
sleep
171
6.6477
7.0000
6.6487
0.8396
age
171
27.421
27.000
27.098
3.646
Correlations:haircut,sleep, age
haircut
sleep
sleep
-0.117
age
0.062
(1)
Covariances:haircut,sleep, age
haircut
sleep
age
haircut
(2)_
sleep
-1.79232
0.70491
age
4.12314
-0.45372
13.29226
Blank 1 =
Blank 2 =
Q2)Is the following statement correct? Explain why or why not.
“A correlation of 0 implies that no relationship exists between the two variables under study.”
Q3)Does how long children remain at the lunch table help predict how much they eat? The data in file lunchtime.xls (File is in Tab#1 of Excel Workbook) gives information on 20 toddlers observed over several months at a nursery school. “Time” is the average number of minutes a child spent at the table when lunch was served. “Calories” is the average number of calories the child consumed during lunch, calculated from careful observation of what the child ate each day.
Findthecorrelationforthesedata.
Supposeweweretorecordtimeatthetableinhoursratherthaninminutes.Howwouldthecorrelationchange?Why?
Writeasentenceortwoexplainingwhatthiscorrelationmeansfort.
InstructionsMy report is about the future of work and focuses the .docxdirkrplav
Instructions
My report is about the future of work and focuses the role of a woman. I have already done some work for this report. Down below you will see the points we spoke about in the report and why we chose this subject. More importantly, you will also see the scenario we came up with and the framing questions we created. You will need both the scenario and framing questions and write a summary about it in 600 words. I need you to do this section:
*Scenario plan: Working together the group is required to construct a future scenario using the scenario template. The completed scenario will be attached in the appendix. You will need to insert in your report a summary of your future scenario identifying the evidence/trends it is based upon, framing questions and key elements around work that are relevant to your analysis to the future of work (Approx 600 words). (The template & framing questions should be in your appendix.)Introduction
· The future of work will have an impact on women in terms of employment and job positions in an organization.
· Corporations will be equally hiring men and women based on their skills and knowledge.
· The wage gap between genders will decrease in the near future.
· Women will become more independent leading the marriage rates to drop.
· When it comes to politics, the role of a women in a less developed country will change significantly as women are now allowed to vote and become members of the parliament. Rationale
· Theme: Gender and diversity
· Why?
Coming from an Arab country, we have noticed many changes in the typical role of women all around the world. We noticed that women are starting to change their habits and lifestyle. Women are becoming highly educated, searching for independence, and working more to enhance their career path. Women are no longer categorized as the traditional housewivesScenario: Everything Will Change“Post-Fordism”
Society and culture
-Feminized values
-Women and men equally valued
-Make, do, and mend culture
-Increasing diversity
Family life
-Parents work long hours little time for kids
-Schools and institutions take greater responsibility for children
-Men contribute equally for child rearing, housework and time at work
Education
-Vocational
-Individual happiness linked to societal outcomes
The workplace
-Pay gap decrease between genders
-Equality between genders
-Even value of diversity
-Women greater presence in public, business life
-Responsible and ethical corporations
The environment
-No clean energy developed
-Wealthy nations survive while poor nations don’t do so well
Science and technology
-High surveillance of all citizens
-Innovation is highly valued
-Highly networked
-Development of new technology with few people to afford it
Politics
-Single party dominates
-Strong alliances between countries
-People vote according to policies that value social and environmental outcomes
-Women politicians increase
-Governmental regulations change regarding expatriates
Economics.
InstructionsInstructions for the Microsoft Excel TemplatesThis wor.docxdirkrplav
This document provides instructions for completing Microsoft Excel templates for a grading assignment. It explains that only the provided workbook should be submitted and that it contains the assignment details. Students should enter their name and solve problems by filling in highlighted cells with account titles, values, formulas, and text explanations. The templates are formatted to print on standard paper sizes and use standard accounting formatting like commas. Students should leverage features like split panes and lookup formulas to assist with copying data accurately. Sample templates are provided for problems on income statements, retained earnings statements, and long-term construction contracts.
InstructionsResearch and write a brief answer to the following .docxdirkrplav
Instructions:
Research and write a brief answer to the following question. Your response should be between 150-300 words. Your work should follow the conventions of Standard American English (correct grammar, punctuation, etc.). Your writing should be well ordered, logical and unified, as well as original and insightful. Furthermore, all sources used should be properly cited using APA formatting. You can find a blank assignment template in the Doc Sharing.
Question:
Continuous Quality Improvement (CQI) is a management philosophy and a management method. Identify and explain the philosophical and methodological characteristics of CQI. Select the characteristic you find most valuable and explain why.
.
Instructionsinstructions.docxFinal Lab ReportYou are requ.docxdirkrplav
Instructions/instructions.docx
Final Lab Report
You are required to write a complete laboratory report that covers all three experiments for "Lab 2: Water Quality and Contamination," using knowledge gained throughout the course. To begin, download the Final Lab Report Template and utilize this form to ensure proper formatting and inclusion of all required material. Additionally, view the Sample Final Lab Report before beginning this assignment, which will illustrate what a Final Lab Report should look like. You must use at least four scholarly sources and your lab manual to support your points. The report must be six to ten pages in length (excluding the title and reference pages) and formatted according to APA style. For information regarding APA samples and tutorials, visit the Ashford Writing Center, located within the Learning Resources tab on the left navigation toolbar.
The Final Lab Report must contain the following eight sections in this order:
1. Title Page – This page must include the title of your report, your name, course name, instructor, and date submitted.
2. Abstract – This section should provide a brief summary of the methods, results, and conclusions. It should allow the reader to see what was done, how it was done, and the results. It should not exceed 200 words and should be the last part written (although it should still appear right after the title page).
3. Introduction – This section should include background information on water quality and an overview of why the experiment was conducted. It should first contain background information of similar studies previously conducted. This is accomplished by citing existing literature from similar experiments. Secondly, it should provide an objective or a reason why the experiment is being done. Why do we want to know the answer to the question we are asking? Finally, it should end with all three hypotheses from your Week Two experiments. These hypotheses should not be adjusted to reflect the “right” answer. Simply place your previous hypotheses in the report here. You do not lose points for an inaccurate hypothesis; scientists often revise their hypotheses based on scientific evidence following the experiments.
4. Materials and Methods – This section should provide a detailed description of the materials used in your experiment and how they were used. A step-by-step rundown of your experiment is necessary; however, it should be done in paragraph form, not in a list format. The description should be exact enough to allow for someone reading the report to replicate the experiment, however, it should be in your own words and not simply copied and pasted from the lab manual.
5. Results – This section should include the data and observations from the experiment. All tables and graphs should be present in this section. In addition to the tables, you must describe the data in text; however, there should be no personal opinions or discussion outside of the results located within t.
INSTRUCTIONSInstructionsPlease evaluate, display, and interpret t.docxdirkrplav
This Excel document contains instructions to evaluate, display, and interpret a dataset measuring the number of members seen in an office each week over the course of a year. The evaluator is asked to use descriptive statistics, inferential statistics, charts, tables and graphs to analyze the data and tell an easy to understand story about what the data shows to executive leadership. The dataset lists the week of the year and corresponding number of members seen for each of the 52 weeks.
InstructionsEach of your 2 replies must contain at least .docxdirkrplav
Instructions:
Each of your 2 replies must contain at least 1 or 2 paragraphs including a minimum of 200 words. One of your replies must cover a topic different than the one you discussed in your thread. Seek to understand your classmate’s thread, including the economic theory and facts he/she presented as well as his/her points of view and real-world example. Aim to communicate your own understanding of relevant facts, your values, and your perspective on the topic. Each reply must contain at least 1 citation in current APA format.
Reply to these two:
#1 Monica
Three types of Unemployment
Unemployment is divided into three categories by economist: frictional, structural, and cyclical. Frictional unemployment is unemployment due to constant changes in the economy that prevent qualified unemployed workers from being immediately matched up with existing job openings (Gwartney et al.) Structural unemployment is unemployment due to structural characteristics of the economy that make it difficult for job seekers to find employment to hire workers (Gwartney et al.) Cyclical unemployment is unemployment due to recessionary business conditions and inadequate labor demand (Gwartney et al.)
“Frictional unemployment is not as harmful to an economy as other types of unemployment, such as cyclical and structural unemployment. That's because a rise in frictional unemployment is simply an increase of workers moving toward better positions (Amadeo).”
Frictional unemployment comes from imperfect information. An example would be most businesses now when they are in the hiring process they will do a bunch of interviews and spend money trying to find the best person for that job. The people who are looking for jobs are constantly looking on the internet, the newspaper, local bulletin boards, and social media for the right job that fits them. In the county I live with I see a lot of structural unemployment. People that do have job openings require education; the ones who are unemployed have no education so they aren’t qualified. A lot of office jobs require you to have computer knowledge. Around my home town, there is very little education especially when it comes to technology. The last type of unemployment we see happening today all around the world. Businesses are cutting back and laying employees off. Where I currently work, when someone leaves, they aren’t filling the positions. We have to do more work with fewer employees.
I have a friend who lost her job and I try to encourage her to never give up and keep her faith. Philippians 4:5 states, “Do not be anxious about anything, but in everything by prayer and supplication with thanksgiving let your request be made known to God.” That is a good scripture for everyone who is unemployed to keep in mind. Times can be tough when you are looking for a job, but the Bible tells us to never give up, and pray about it.
Amadeo, K. (2014). Frictional Unemployment. US Economy. Retrieved from
http://useconomy.
InstructionsInstructions for numberguessernumberGuesser.html.docxdirkrplav
Instructions/Instructions for numberguesser/numberGuesser.html
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Instructions/Instructions for shoerental/ShoeRentalClass.html
Instructions/lab4.docx
1. Complete the Programmers Workshop on pg 313-316 (Including Detective Work). Upload the numberGuesser.html file here.
2. Complete the Object Lesson on pg 316-320 (Including Detective Work). Upload the ShoeRentalClass.html page you create here.
Introduction to Unix - POS420
Unix Lab Exercise Week 5
Job Control :
1. How to suspend the jobs running in foreground ?
Open a file in vi and press CTRL-Z to put it into background
$ vi filename
CTRL-Z
filename[New file]
[1] + Stopped vi filename
$
where 1 is the job number, + or - make the current and previous jobs.
2. How to make it run in foreground ?
You can use fg command to make it run in foreground. If more than one job is suspended, you can use fg %n where n is the number is the sequence of the process to make that process come in foreground.
$ fg %1
Now you will see vi editor again.
3. How to make it run in background ? (Only stopped jobs)
You can use bg command to make it run in background. If more than one job is suspended, you can use bg %n where n is the number is the sequence of the process to make that process come in background.
Let us suspend this job one more time.
$ vi filename
CTRL-Z
filename[New file]
[1] + Stopped vi filename
$
Let us run in background .
$ bg %1
4. Another way to suspend a job by using kill command.
Run vi in this session.
Open another connection through telnet. Now you have two sessions.
Type ps command to see what processes are running.
$ ps
PID TT STAT TIME COMMAND
5226 q7 S 0:01 -ksh (ksh) - This is new shell
6314 q7 R 0:00 ps
5487 ub S 0:00 -ksh (ksh) - This is previous shell
6312 ub S 0:00 vi filename - vi is running in previous session.
Now send a STOP signal to the process. kill -l will give you a lo\ist of signals.
$ kill -STOP 6312
Now you will see this in the other session
[1] + Stopped (signal) vi filename
To .
InstructionsI need 3 pages of the four questions. That is abo.docxdirkrplav
Instructions:
I need 3 pages of the four questions. That is about 200 words for each question. The answers MUST be articulate and to the point. I do not pay for shoddy work. Give me a paragraph for each question. Use the links given for each question as your sources. You can seek outside references as additional sources if need be. Thank you.
2. How did Hellenism spread, how far did it spread, and what effects did it have on both Greeks and those unfamiliar with Greek culture? Give some examples of Hellenistic influences on the Mediterranean world and its culture post Alexander the Great.
http://www.history.com/topics/ancient-history/peloponnesian-war http://www.metmuseum.org/toah/hd/haht/hd_haht.htm http://www.shsu.edu/~his_ncp/ArrAlex.html
3. What were the main achievements and failures of the Roman Republic? Give some examples of some of the issues that impacted Roman life and society during the Republic and discuss these. How did the crisis of leadership in the late Republic lead to civil war, particularly after the assassination of Julius Caesar?
http://www.princeton.edu/~achaney/tmve/wiki100k/docs/Roman_Republic.html http://www.class.uh.edu/mcl/classics/Rom/Livy.html
4. Augustus effectively became the first Roman Emperor in 31 BC and initiated a series of reforms that began a 200 year period of relative tranquility, peace, and prosperity for Rome and its Empire. Why were his successors, particularly after 180 AD, generally not as successful in expanding upon his achievements?
http://www.pbs.org/empires/romans/ http://www.csun.edu/~hcfll004/nicolaus.html
5. How did Christian ideas and practices respond to changing political and social circumstances in the later Roman Empire? What appeal did Christianity have for Romans at this time, and what accounted for its spread? What role did the Emperor Constantine play in its success?
http://www.tribunesandtriumphs.org/roman-empire/causes-for-the-fall-of-the-roman-empire.htm http://www.westmont.edu/~fisk/articles/TacitusAndPlinyOnTheEarlyChristians.html
.
InstructionsFor this assignment, collect data exhibiting a relat.docxdirkrplav
Instructions
For this assignment, collect data exhibiting a relatively linear trend, find the line of best fit, plot the data and the line, interpret the slope, and use the linear equation to make a prediction. Also, find r2 (coefficient of determination) and r (correlation coefficient). Discuss your findings. Your topic may be that is related to sports, your work, a hobby, or something you find interesting. If you choose, you may use the suggestions described below.
A Linear Model Example and Technology Tips are provided in separate documents.
Tasks for Linear Regression Model (LR)
(LR-1) Describe your topic, provide your data, and cite your source. Collect at least 8 data points. Label appropriately. (Highly recommended: Post this information in the Linear Model Project discussion as well as in your completed project. Include a brief informative description in the title of your posting. Each student must use different data.)
The idea with the discussion posting is two-fold: (1) To share your interesting project idea with your classmates, and (2) To give me a chance to give you a brief thumbs-up or thumbs-down about your proposed topic and data. Sometimes students get off on the wrong foot or misunderstand the intent of the project, and your posting provides an opportunity for some feedback. Remark: Students may choose similar topics, but must have different data sets. For example, several students may be interested in a particular Olympic sport, and that is fine, but they must collect different data, perhaps from different events or different gender.
(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully. Visually judge whether the data points exhibit a relatively linear trend. (If so, proceed. If not, try a different topic or data set.)
(LR-3) Find the line of best fit (regression line) and graph it on the scatterplot. State the equation of the line.
(LR-4) State the slope of the line of best fit. Carefully interpret the meaning of the slope in a sentence or two.
(LR-5) Find and state the value of r2, the coefficient of determination, and r, the correlation coefficient. Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?
(LR-6) Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.
(LR-7) Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting.
Scatterplots, Linear Regression, and Correlation [Section 1.4, starting on page 114 in the textbook]
When we have a set of data, often we would like to develop a model that fits the data.
First .
InstructionsFor this week’s assignment, you will synthesize the .docxdirkrplav
Instructions
For this week’s assignment, you will synthesize the most relevant information in the situation below, and present a solution in your own words, using your own analysis. You will not use all of the information included in the scenario. Remember it is not appropriate to cut and paste entire sections from the situation to substitute for your own analysis.
The objective of the assignment is to organize your message in a way that will be most effective in persuading the Chief Executive Officer (CEO) to take action.
Situation: Convincing the CEO to Approve a Public Relations Plan
You are the director of public relations for Easy to Be Green, the innovative new company that helps homeowners, businesses, and municipalities become more environmentally friendly. The company has been active in environmental issues in the community since its founding a few years ago and generally has good community relations. Recently EBG’s director of research, who is strongly opinionated about environmental issues, spoke in public about the environmental practices of some local companies who employ many people in the community. Lately, you’ve found that some of your local contacts seem a little less interested in EBG’s public relations initiatives, and there has even been a small drop in sales. There may be no connections between these events, but you want to be proactive about the company’s community relations.
You also want to protect the company against charges of hypocrisy. The other day you as walked through the parking lot, it occurred to you that the majority of the employees drive SUVs, pick-ups, and other kinds of gas guzzlers. This includes the CEO, whose family car is a luxury sedan. The company’s delivery and service vans are also not the most environmentally-friendly vehicles.
After a little research, you come up with a tentative plan. You have learned that a local hybrid car dealership has been offering an interesting deal. Employees of companies that buy hybrids as company vehicles can get discounts when they buy hybrids for themselves. You think that the company should consider purchasing a couple of hybrid vans and encourage employees to buy hybrids for themselves by offering substantial rebates for these purchases. You want to get the CEO’s approval before you pursue this idea any further. You anticipate that he will have significant resistance. The company vehicles are not due for replacement, and the rebates to employees could add up to quite a lot if many employees take up the offer. On the other hand, if only a few employees take up the offer, a significant environmental initiative will seem like a failure. The CEO is a risk-taker in terms of business initiatives but tends to be conservative in management practices. He might also be a little defensive about the hybrid promotion plan because of his own vehicle choices.
You feel strongly that the potential benefits of this plan—in long-term savings on gas, in goo.
Andreas Schleicher presents PISA 2022 Volume III - Creative Thinking - 18 Jun...EduSkills OECD
Andreas Schleicher, Director of Education and Skills at the OECD presents at the launch of PISA 2022 Volume III - Creative Minds, Creative Schools on 18 June 2024.
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
How Barcodes Can Be Leveraged Within Odoo 17Celine George
In this presentation, we will explore how barcodes can be leveraged within Odoo 17 to streamline our manufacturing processes. We will cover the configuration steps, how to utilize barcodes in different manufacturing scenarios, and the overall benefits of implementing this technology.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Instructions(1) Work through the pages below.(2) Use the us_demog.docx
1. Instructions:(1) Work through the pages below.(2) Use the
us_demographics.jmp data table to: (a) select a continuous
variable and generate a histogram
(b) select two continuous variables and determine the
correlation coefficient(c) generate box plots using College
Degrees as the Y, Response variable and Region as the X,
Factor variable(3) Copy and paste the results for 2 (a, b, & c) in
a Word document.
Histograms, Descriptive Statistics, and Stem and Leaf
Use to display and describe the distribution of continuous
(numeric) variables. Histograms and stem and leaf plots allow
you to quickly assess the shape, centering and spread of a
distribution. For categorical (nominal or ordinal) variables, see
the page on Bar Charts and Frequency Distributions.
Histograms and Descriptive Statistics
1. Open the JMP® data table us_demographics.jmp, select
Analyze > Distribution.
2. Click on one of the continuous variables from Select
Columns, and click Y, Columns (continuous variables have blue
triangles).
3. Click OK to generate a histogram, outlier box plot and
descriptive statistics.
· The percentiles, including quartiles and the median, are listed
under Quantiles.
· The sample mean, standard deviation and other statistics are
listed under Summary Statistics.
Example: Car Physical Data.jmp (Help > Sample Data)
2. Tips:
· To change the display from vertical to horizontal (as shown),
click on the top red triangle and select Stack.
· To change the graphical display for a variable, or to select
additional options, click on the red triangle for that variable.
· To display different summary statistics, use the red triangle
next to Summary Statistics.
· To change all future output to horizontal, go to Preferences >
Platforms > Distribution, click Stack and
Horizontal, then click OK.
Stem and Leaf Plot
To generate a stem and leaf plot, click on the red triangle for
the variable and select Stem and Leaf.
Tips:
· A key to interpret the values is at the bottom of the plot. The
top value in this example is 4300, the bottom value is 1700
(values have been rounded to the nearest 100).
· Click on values in the stem and leaf plot to select observations
in both the histogram and the data table. Or, select bars in the
histogram to select values in the stem and leaf plot and data
table.
jmp.com/learn rev 07/2012
Use to display the distribution of continuous variables. They are
also useful for comparing distributions.
3. Box Plots – One Variable
1. From the open JMP® data table, select Analyze >
Distribution.
2. Click on another continuous variable from Select Columns,
and Click Y, Columns (continuous variables have blue
triangles).
3. Click OK. An outlier box plot is displayed by default next to
the histogram (or above if horizontal layout). To display a
quantile box plot, select the option from the red triangle for the
variable.
jmp.com/learn rev 07/2012
Box Plots
The lines on the Quantile Box Plot correspond to the quantiles
in the distribution output.
Box Plots – Two Variables
The Outlier Box Plot shows the box, plus:
· IQR = the 3rd quartile minus the 1st quartile.
· Whiskers drawn to the furthest point within 1.5 x IQR from
the box.
· Potential outliers (disconnected points).
· A red bracket defining the shortest half of the data (the
densest region).
Quantile Box Plot
4. Outlier Box Plot
1. Select Analyze > Fit Y by X.
2. Click on one of the continuous variable from Select Columns
(e.g. Obese, Alcohol, etc.) and Click Y, Response.
3. Click on Region (a categorical variable and click X, Factor
(categorical variables have red or green bars).
4. Click OK. The Oneway Analysis output window will display.
5. Click on the red triangle, and select Display Options (near
the bottom of the list) > Box Plots to display quantile box
plots, or select
Quantiles to display both box plots and quantiles (shown right).
Example: Companies.jmp (Help > Sample Data)
Notes: Box plots for one or more variables can also be
generated from Graph > Graph Builder.
Use to display the relationship between two continuous
variables. Continuous variables have blue triangles.
5. Scatterplots – Two Variables
1. From the open us_demographics JMP® data table, select
Analyze > Fit Y by X.
2. Click on a continuous response (or dependent) variable in
Select Columns, and Click Y, Columns.
3. Click on a continuous predictor (or independent) variable,
and click X, Factor.
4. Click OK to generate a scatterplot.
Example: Car Physical Data.jmp (under Help > Sample Data)
Scatterplots – More than Two Variables
1. Select Graph > Scatterplot Matrix.
2. Select all continuous responses of interest, and click Y,
Columns.
3. Click OK to generate the scatterplot matrix.
Notes: Scatterplots and scatterplot matrices can also be
generated from Analyze > Multivariate Methods > Multivariate
and from Graph > Graph Builder.
Scatterplots Plots
jmp.com/learn rev 07/2012
Interactive Graphing with Graph Builder
Use Graph Builder to interactively create graphs for one or
more variables, including line plots, splines, box plots, bar
charts, histograms, mosaic plots, maps and more.
6. jmp.com/learn rev 07/2012
Drag and Drop to Visualize Data
1. From the open us_demographics JMP® data table select
Graph > Graph Builder.
2. Drag a variable from the Variables list and drop it in the
desired drop zone. In the examples (right), Weight is in the Y
zone and Height is in the X zone.
3. To add a grouping variable, drag and drop a variable in the
Group X or Group Y zone. In the example, Sex is in the Group
X zone.
4. To change the graphical display, click on a graph element
icon. Or, click and drag an icon onto a graph frame. Here, Line
of Fit has been selected.
5. Change Summary Statistics and other display options for the
selected graph elements.
6. Click the Done button (top left) when finished.
Example: Big Class.jmp (under Help > Sample Data)
Tips:
· Right-click in the graph to change graph properties.
· To replace a variable with a new variable, drag the new
variable and drop it in the center of the drop zone.
· By default, Graph Builder displays data points. If continuous
variables are in both the X and Y zones a smooth spline will
display (lambda = 0.05).
· More than one variable can be assigned to an X or Y zone, or
to a group zone. Drag a variable to either side of the existing
variable in the zone – a blue ribbon will indicate where the new
variable will be placed when dropped.
· To change the modeling type (to use different graph elements),
7. right- click on the variable and select the new data type (if
available).
Other Drop Zones:
· Drop a variable in Wrap to trellis the graph horizontally and
vertically.
· Drop a variable in Color to create a legend and color by values
of the variable.
· Drop a variable in Overlay to color and overlay graphs for
each value of the variable on one graph.
· If data has been summarized (a frequency variable exists),
drag the variable to the Freq zone.
· If a column defines a physical shape, drag the variable to
Shape to create a map (shape files must exist).
· Drop a variable in Size to scale markers or map shapes
according to the value of the size variable.
Note: Instructions also apply to the iPad® Graph Builder
Application (see jmp.com/iPad).
Use Tabulate to interactively summarize data and construct
tables of descriptive statistics.
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Summarizing Data Using Tabulate
Drag and Drop to Summarize Data
· Open the Car Physical Data table. Help>Sample Data> See an
Alphabetical List …>Car Physical Data data table select Tables
> Tabulate.
· Drag and drop variables from the column list to the drop zone
8. for rows and columns.
· Country (below, left) is in the rows drop zone – the number of
observations per country is displayed.
· Horsepower (middle) is in the columns drop zone as an
analysis column – the sum for horsepower is displayed for each
country.
· Drag and drop one or more summary statistics from the middle
panel into the results area. Mean and Std Dev are displayed for
each country (below, right).
Example: Car Physical Data.jmp (Help > Sample Data)
Tips:
· Click Undo to reverse the last change, or use Start Over to
clear the display.
· Click and drag variables in the table to rearrange, or right-
click on a variable to delete or change the format.
· To change the numeric formats (i.e., decimal places), use
Change Format at the bottom of the window and select the
desired format.
· To add new summary panels to the table, drag and drop the
new variable to the bottom or left of the table. Here, Type has
been added to the bottom of the original table.
· To add additional row or column variables, drag and drop a
new variable on either side of the current variable in the table.
Here, Type has been added next to Country and Horsepower has
been added next to Weight.
· To create a data table, click Done, then select Make Into Data
Table from the top red triangle.
9. Note: For more details, see the book Using JMP (under Help >
Books).
Random Sampling and Random Data
This page documents methods for selecting a random sample
and generating random data in JMP®.
jmp.com/learn rev 07/2012
Random Sampling
1. From the Car Physical Data JMP data table, select Tables >
Subset.
2. Specify how you’d like the sample to be selected:
· Random – sampling rate (specify the proportion).
· Random – sample size (specify the desired sample size).
· To select a stratified sample across another variable, check
Stratify and select the variable.
3. Under Columns, specify All columns or Selected columns.
4. Click OK to generate the random sample.
Example: Car Physical Data.jmp (Help > Sample Data)
JMP will produce a subset of the original table. To connect the
subset to the original table, select Link to original data table
before clicking OK.
10. Generating Random Data
1. Select Cols > New Column.
2. Under Column Name, assign a name for the column. We’ll
name our column Random Normal.
3. Click Column Properties, and select Formula. This takes you
to the JMP Formula Editor.
4. From Functions (grouped), scroll down to Random.
5. Select the distribution of interest. Here, we will select
Random Normal (there are many distributions to choose from).
6. Click OK. JMP will populate the new column with simulated
standard normal data.
Simulated random standard
normal data.
The fat plus next to the
variable name under the Columns panel tells us that a formula is
stored in the
Random Normal column.
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Correlation
Correlation is a measure of the linear association between two
variables. This page documents the two platforms in JMP® for
assessing correlation.
jmp.com/learn rev 07/2012
11. Correlation Between Two Variables
1. Open a data table: Help>Sample Data> See an Alphabetical
List …>Body Measurements, select Analyze > Fit Y by X.
2. Click on a continuous variable (Fore)from Select Columns,
and click Y, Response (continuous variables have blue
triangles).
3. Click on a second continuous variable (Mass), and click X,
Factor.
4. Click OK to generate a scatterplot.
5. To display the correlation, click on the red triangle and select
the Density Ellipse > 0.95.
· A 95% density ellipse, which graphically shows the
correlation, will display on the scatterplot.
· To show the correlation coefficient, click on the gray icon
next to Correlation.
Correlations Between Multiple Pairs of Variables
1. From the open Body Measurements JMP data table, select
Analyze > Multivariate Methods > Multivariate.
2. Click on two or more continuous variables from Select
Columns, and click Y, Columns.
3. Click OK to produce a scatterplot matrix with density ellipses
and a table of correlations.
· The Default estimation method allows JMP to determine the
method for estimating correlations that is most appropriate for
your data set.
Example: Body Measurements.jmp (Help > Sample Data)
Tips:
· Many additional correlation options are available under the
red triangle next to Multivariate, including:
12. · CI of Correlations.
· Inverse Correlations.
· Partial Correlations.
· Pairwise Correlations (Pearson product-moment).
· Nonparametric Correlations (including Spearman’s rho).
· Scatterplot options are available under the red triangle next
toScatterplot Matrix.
Notes: Density ellipses can also be generated from Graph >
Scatterplot Matrix and Graph > Graph Builder. For additional
information, search for “correlation” in the JMP Help.
Simple Linear Regression
Simple linear regression is used to model the relationship
between two continuous variables.
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Simple Linear Regression Using Fit Y by X
1. Open the Big Class.jmp data table, select Analyze > Fit Y by
X.
2. Click on a continuous variable from Select Columns, and
click Y, Response (continuous variables have blue triangles).
3. Select a second continuous variable, and click X, Factor.
4. Click OK to generate a scatterplot.
5. To fit a regression line, click on the red triangle and selectFit
Line.
By default, JMP will provide the following results:
· The regression equation (under Linear Fit).
· The Summary of Fit.
· Lack of Fit (if the data table includes replicates of X values).
· The ANOVA table.
13. · The parameter estimates.
Additional options, such as residual plots and confidence
curves, are available from the red triangle next to Linear Fit
(directly under the graph).
Tips:
· For other fit options, such as polynomial, transformation (fit
special) and spline, use the top red triangle.
· To add a legend, change markers, or make other changes to the
graphical display, right-click on the graph.
· To fit separate lines for categories of a grouping variable,
click on the top red triangle, select Group By, and choose a
grouping variable. Then, click on the top red triangle and select
Fit Line.
JMP will fit separate lines and provide results for each level of
the grouping variable.
Example: Big Class.jmp (Help > Sample Data)
This page documents two methods for calculating standardized
values (z-scores) in JMP®.
Method 1 (Save Standardized)
1. From an open JMP data table, select Analyze > Distribution.
2. Select one or more continuous variables from Select Columns
and click Y, Columns.
3. Click OK to generate a histogram and descriptive statistics.
4. Click on the red triangle for the variable, and select Save >
Standardized – a new column, Std Variable Name, will be saved
to the data table.
14. The column Std height contains z-scores for height.
Save the data table to save this new column.
Method 2 (Create Formula with Formula Editor)
1.
From an open JMP data table, select Cols > New Column.
Under Column Name, assign name for the column. We’ll name
our column Standardized.
Click Column Properties, and select Formula. This takes you to
the JMP Formula Editor.
Keypad
Functions
A standardized value is in the form:
Create the formula, and click OK. This will populate the column
in the data table with standardized values for the variable.
To create the formula for the standardized value:
1. Click on the variable under Table Columns.
2. Click “-”on your keyboard (or the minus sign on the keypad).
3. Select Statistical > Col Mean under Functions (grouped).
Then, click on the variable under Table Columns.
4. Click on the outer gray box, and click “/” on your keyboard
(or the divide-by sign on the keypad).
5. Select Statistical > Col Std Dev under Functions (grouped).
Then, click again on the variable name.
2.
3.
15. 4.
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Finding Standardized Values (z-Scores)
This page documents one method for finding the area under the
lower tail of the curve (cumulative probability) in JMP® for one
value or for multiple values of a normally distributed
continuous variable.
Find the Area Under a Normal Curve (One Value)
Caret
1. Select File > New > Data Table - the new table will have one
column.
2. Add one row - select Rows > Add Rows, and type “1.”
3. Right-click on Column 1, and select Formula to access the
formula editor.
4. Under Functions (grouped), select Probability > Normal
Distribution. This will give the following formula:
5. Click the caret on the keypad twice to add fields for the mean
and standard deviation.
6. In the fields provided, type the value of x, the mean, and the
standard deviation.
7. Click OK. JMP will populate the row in the data table with
the cumulative probability value (the area under the lower tail
of the normal curve).
Note: To find the area in the upper tail, or the area between two
16. values, use the following formulas:
· Upper tail:
· Between two values:
Find the Area Under a Normal Curve (Multiple Values)
1. Open an existing data table (File > Open), or open a new data
table (File > New > Data Table) and create a column containing
the values of interest.
2. Select Cols > New Column to create an additional column,
and rename the column. We’ll name our columnProb Height.
3. Click Column Properties, and select Formula to access the
JMP Formula Editor.
4. Follow steps 4 and 5 above.
5. Click on the box containing “x,” and from Table Columns,
select the variable name.
6. Type the mean and standard deviation in the fields provided.
7. Click OK. JMP will populate the column with cumulative
probability values for each value of the variable.
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Finding the Area Under a Normal Curve
This page documents some ways to assess normality for a
continuous (quantitative) variable.
1. Open the Car Physical Data JMP® data table, select Analyze
> Distribution.
2. Select one or more continuous variables from Select Columns
and click Y, Columns.
3. Click OK to generate a histogram and descriptive statistics (a
horizontal layout is shown below).
17. Example: Car Physical Data.jmp (Help > Sample Data)
Normal Quantile Plot
Click on the red triangle for the variable (Weight, in this
example), and select Normal Quantile Plot.
If the data more or less follows a straight
line (fat pen test), we can conclude that the data came from a
normal distribution.
For this example, we would conclude the
distribution is approximately normal.
Fitting a Normal Distribution
1. Select Continuous Fit > Normal from the lower red triangle.
2. In the resulting output, click on the red triangle for Fitted
Normal and select Goodness of Fit.
Interpretation (using a significance level of 0.05):
· Prob<W is the p-value for this test.
18. · Our p-value is 0.5681.
· A p-value less than 0.05 would indicate that the underlying
distribution is not normal.
· We do not have sufficient evidence to conclude that the
underlying distribution is not normally distributed.
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Assessing Normality
198
Performing Contingency Analysis
Chapter 6
3
Performing Contingency AnalysisUsing the Fit Y by X or
Contingency Platform
(1) Click on the Help tab in JMP and select Sample Data.
(2) Click on the following option: See an Alphabetical List of
all Sample Data Files
(3) Click on the Car Poll.jmp sample data table
Make an attempt to answer the following questions and if you
find that you will take more than 60 seconds then look at the
section below on Contingency Table.
(1) What is the number of cars that are both large and come
from America?
19. (2) What is the percentage of all cars that are both large and
come from America?
(3) What is the percentage of large cars that come from
America?
(4) What is the percentage of American cars that are large?
Contingency Table
The Contingency Table is a two-way frequency table. There is a
row for each factor level and a column for each response level.
To produce the plot shown in Figure 6.1, follow the instructions
in the example below:
The Contingency or Fit Y by X platform lets you explore the
distribution of a categorical (nominal or ordinal) variable Y
across the levels of a second categorical variable X. The
Contingency platform is the categorical by categorical
personality of the Fit Y by X platform. The analysis results
include a mosaic plot, frequency counts, and proportions.
Figure 6.1 A Contingency Table
Example of Contingency Analysis
This example uses the Car Poll.jmp sample data table, which
contains data collected from car polls. The data includes aspects
about the individual polled, such as their sex, marital status,
and age. The data also includes aspects about the car that they
own, such as the country of origin, the size, and the type.
Examine the relationship between car sizes (small, medium, and
large) and the cars’ country of origin.
1. Using the open Car Poll.jmp sample data table.
2. Select Analyze > Fit Y by X.
20. 3. Select size and click Y, Response.
4. Select country and click X, Factor.
5. Click OK.
The following table explains the conclusions that you can make
about these cars using the Contingency Table.
Number Description Label in Table
36 Number of cars that are both large and come from America
Count
11.88% Percentage of all cars that are both large and come
from America (36/303)a.
85.71% Percentage of large cars that come from America
(36/42)b
31.30% Percentage of American cars that are large (36/115)c.
Total%
Col%
Row%
Mosaic Plot
The mosaic plot is a graphical representation of the two-way
frequency table or Contingency Table. A mosaic plot is divided
into rectangles, so that the area of each rectangle is proportional
to the proportions of the Y variable in each level of the X
21. variable
Note the following about the mosaic plot in the Figure above:
· The proportions on the x-axis represent the number of
observations for each level of the X variable, which is country.
· The proportions on the y-axis at right represent the overall
proportions of Small, Medium, and Large cars for the combined
levels (American, European, and Japanese).
·
From the mosaic plot and legend in the Figure above, notice the
following:
· Very few Japanese cars fall into the Large size category.
· The majority of the European cars fall into the Small and
Medium size categories.
· The majority of the American cars fall into the Large and
Medium size categories.