This document outlines a statistical analysis project involving daily stock price data from 2008-2009. Students are instructed to choose an index from the ASX, analyze the daily change in closing price for 2008 using descriptive statistics and statistical inference, and explore the relationship between daily volume and turnover for the same index in 2009 using regression. The project is split into two parts worth 15% of the overall course assessment. Detailed instructions are provided on statistical tasks to complete, reporting requirements, and grading criteria.
Elementary Data Analysis with MS Excel_Day-5Redwan Ferdous
This event took place on 16th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-5, Hypothesis, Statistics, Regression Analysis, T-Test, Z-test, P-Test, ANOVA, Goal Seek, Pivot Chart, Dashboard, Slicer, Solver, Data Analysis Toolpak, and peripheral items were discussed.
This document discusses time-series forecasting and index numbers. It begins by outlining the chapter goals, which are to develop basic forecasting models, identify time-series components, use smoothing and trend-based forecasting models, forecast seasonal data, and compute index numbers. The document then explains key concepts like time-series plots and components, moving averages, exponential smoothing, trend-based forecasting using linear, quadratic and exponential models, and model selection criteria. Examples are provided throughout to illustrate time-series smoothing and forecasting techniques.
This chapter discusses decision making under uncertainty. It describes the basic steps in decision making as listing alternative actions, uncertain events, determining payoffs, and adopting decision criteria. It introduces payoff tables and decision trees as methods to display this information. Expected monetary value and expected opportunity loss are presented as decision criteria that aim to maximize expected payoff or minimize expected loss. The value of perfect information is defined as the expected gain from knowing the outcome with certainty compared to the best action under uncertainty. Finally, it discusses how to account for risk by considering the variability of payoffs through measures like variance and standard deviation.
RS Trainings: is a brand and providing quality online and offline trainings for students in world wide. Rs Trainings providing Best DataScience online training in Hyderabad
Statistical Applications in Quality and Productivity ManagementYesica Adicondro
This chapter discusses quality management tools such as Total Quality Management, Six Sigma, and control charts. It introduces Deming's 14 Points for quality management and the Shewhart-Deming cycle. Six Sigma uses the DMAIC model to reduce defects. Control charts monitor process variation and distinguish common from special causes. The p chart is for proportions while the X and R charts monitor process averages and ranges for numeric data.
Elementary Data Analysis with MS Excel_Day-4Redwan Ferdous
This event took place on 12th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-4, the MS Excel Data Tab, View and Review tab as well as Developer Tab of Horizontal top ribbon was discussed. As well as different Quick analysis tools, What-if Analysis, Data Table, Scenario Manager, Pareto Chart was also discussed.
This document provides instructions for using descriptive statistics, filtering, advanced filtering, pivot tables, and other data analysis tools in Excel. It explains how to compute descriptive statistics using functions or the Data Analysis ToolPak. It also demonstrates how to filter datasets, use advanced filtering to extract subsets of records, create and format pivot tables to summarize data, add and modify fields, and link pivot table cells to external formulas.
This document provides information about Microsoft Office 2007, math editing capabilities, and Microsoft Producer.
The Office 2007 section discusses the new interface with the ribbon and home tab, new file format, potential support issues, and licensing changes. It encourages providing feedback as an early adopter.
The math editing section outlines eight infrastructures like LaTeX, Unicode, and MathML that enable better math display and editing. It discusses complexities like spacing, notation variations, and input methods. New features include formula autobuildup and specialized math fonts.
The Microsoft Producer section gives an overview of the tool for creating media-rich presentations. It outlines the process of importing files, using the new presentation wizard, synchronizing slides with
Elementary Data Analysis with MS Excel_Day-5Redwan Ferdous
This event took place on 16th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-5, Hypothesis, Statistics, Regression Analysis, T-Test, Z-test, P-Test, ANOVA, Goal Seek, Pivot Chart, Dashboard, Slicer, Solver, Data Analysis Toolpak, and peripheral items were discussed.
This document discusses time-series forecasting and index numbers. It begins by outlining the chapter goals, which are to develop basic forecasting models, identify time-series components, use smoothing and trend-based forecasting models, forecast seasonal data, and compute index numbers. The document then explains key concepts like time-series plots and components, moving averages, exponential smoothing, trend-based forecasting using linear, quadratic and exponential models, and model selection criteria. Examples are provided throughout to illustrate time-series smoothing and forecasting techniques.
This chapter discusses decision making under uncertainty. It describes the basic steps in decision making as listing alternative actions, uncertain events, determining payoffs, and adopting decision criteria. It introduces payoff tables and decision trees as methods to display this information. Expected monetary value and expected opportunity loss are presented as decision criteria that aim to maximize expected payoff or minimize expected loss. The value of perfect information is defined as the expected gain from knowing the outcome with certainty compared to the best action under uncertainty. Finally, it discusses how to account for risk by considering the variability of payoffs through measures like variance and standard deviation.
RS Trainings: is a brand and providing quality online and offline trainings for students in world wide. Rs Trainings providing Best DataScience online training in Hyderabad
Statistical Applications in Quality and Productivity ManagementYesica Adicondro
This chapter discusses quality management tools such as Total Quality Management, Six Sigma, and control charts. It introduces Deming's 14 Points for quality management and the Shewhart-Deming cycle. Six Sigma uses the DMAIC model to reduce defects. Control charts monitor process variation and distinguish common from special causes. The p chart is for proportions while the X and R charts monitor process averages and ranges for numeric data.
Elementary Data Analysis with MS Excel_Day-4Redwan Ferdous
This event took place on 12th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-4, the MS Excel Data Tab, View and Review tab as well as Developer Tab of Horizontal top ribbon was discussed. As well as different Quick analysis tools, What-if Analysis, Data Table, Scenario Manager, Pareto Chart was also discussed.
This document provides instructions for using descriptive statistics, filtering, advanced filtering, pivot tables, and other data analysis tools in Excel. It explains how to compute descriptive statistics using functions or the Data Analysis ToolPak. It also demonstrates how to filter datasets, use advanced filtering to extract subsets of records, create and format pivot tables to summarize data, add and modify fields, and link pivot table cells to external formulas.
This document provides information about Microsoft Office 2007, math editing capabilities, and Microsoft Producer.
The Office 2007 section discusses the new interface with the ribbon and home tab, new file format, potential support issues, and licensing changes. It encourages providing feedback as an early adopter.
The math editing section outlines eight infrastructures like LaTeX, Unicode, and MathML that enable better math display and editing. It discusses complexities like spacing, notation variations, and input methods. New features include formula autobuildup and specialized math fonts.
The Microsoft Producer section gives an overview of the tool for creating media-rich presentations. It outlines the process of importing files, using the new presentation wizard, synchronizing slides with
This chapter discusses different types of charts that can be used to visualize quantitative data in Excel. It covers basic chart types like line, column, and pie charts, as well as more advanced types like radar and bubble charts. The chapter also explores chart sub-types and how to combine multiple chart types into a single dashboard chart to analyze business data. The objectives are to determine the appropriate chart type for different situations, modify charts effectively, and create advanced visualizations like management dashboards.
This document provides an overview of Chapter 2 which discusses using statistical analysis tools to solve problems. It introduces statistical functions that can determine values, structure data, and count/total data based on criteria. These functions include AVERAGE, AVERAGEIF, COUNTIF, LARGE, MEDIAN, MODE.SNGL, RAND, RANDBETWEEN, RANK.EQ, ROUND, SMALL, STDEV.S, and SUMIF. The chapter also covers performing what-if analysis, goal seek, simulation, and custom formatting. Level 1 objectives focus on understanding basic statistics and using functions to calculate mean, median, mode and standard deviation. Level 2 objectives involve evaluating data rankings, extremes, and counts/
The document discusses techniques for building multiple regression models, including:
- Using quadratic and transformed terms to model nonlinear relationships
- Detecting and addressing collinearity among independent variables
- Employing stepwise regression or best-subsets approaches to select significant variables and develop the best-fitting model
This document provides learning objectives and content for a chapter on applying fundamental Excel skills and tools to problem solving. It covers three levels of objectives: (1) defining errors and correcting formatting and formulas, (2) calculating data using basic functions like SUM and AVERAGE, and (3) analyzing cell references when writing and copying formulas, including relative, absolute, and mixed references. The chapter introduces skills for writing formulas, using functions, formatting worksheets, and handling errors. It also provides examples of analyzing a budget workbook using different referencing techniques.
Leveraging IBM Cognos TM1 for Merchandise Planning at Tractor Supply Company ...QueBIT Consulting
AGENDA:
Introductions and Company Overviews
TSC Merchandise Planning Solution Overview
Prior State
Solution and Implementation
Tips & Tricks for TM1 Perspectives Templates
Q&A
This document provides an overview of a training course on using statistical functions in Microsoft Excel. The course contains 3 lessons: 1) an introduction to using statistics in Excel, 2) writing good formulas, and 3) choosing the appropriate statistical function. The document outlines the goals of the course and what will be covered in each lesson, including examples of statistical formulas, common errors, and how to use the Insert Function tool to help write formulas.
Visio 2007 can be used to diagram all phases of a project including planning, design, engineering, and implementation. It allows importing timelines, Gantt charts, and project reports from Project 2007. Diagrams like timelines, Gantt charts, process flows, and responsibility matrices can be created. Data from Project and other sources can be linked to shapes to dynamically update diagrams.
This document provides an overview of techniques for presenting numerical data in tables and charts. It discusses ordered arrays, stem-and-leaf displays, frequency distributions, histograms, polygons, ogives, bar charts, pie charts, and scatter diagrams. The chapter goals are to teach how to create and interpret these various data presentation methods using Microsoft Excel. Examples are provided for frequency distributions, histograms, polygons, and ogives to illustrate how to construct and make sense of these graphical representations of quantitative data.
The document describes the components of an Excel chart and how to create a chart using the Chart Wizard. It discusses the chart area, plot area, axes, titles, grid lines, data series, data points, labels, legends. It provides steps for using the Chart Wizard to select data and create a column chart with options to add titles, axes, gridlines, legends, and data labels. Components of a chart include the chart area, plot area, axes, titles, grid lines, data series, data points, labels, and legends.
The document provides an agenda for a training on advanced Excel skills for account managers and associates. The agenda covers reviewing basic Excel functions, creating and customizing charts, copying charts into PowerPoint, using Paste Special, working with PivotTables and PivotCharts, and exploring advanced formulas and text manipulation functions like IF, VLOOKUP, SUMIF, LEFT, RIGHT, MID, and CONCATENATE. Exercises are included throughout to help participants practice and retain the skills covered in the training.
This document outlines an agenda and presentation for an MS Excel 2007 training session for business managers and professionals. The agenda covers topics such as Excel introduction and history, techniques like named ranges and lookups, tips and tricks, templates, pivot tables, formulas, sorting and filtering, connecting Excel to databases and the web, macros, and VBA. It also provides overviews of some key Excel concepts like the ribbon interface and absolute vs. relative references. Hands-on exercises are included to reinforce topics like creating invoices from templates and using formulas with different reference types.
Advance-excel-professional-trainer-in-mumbaiUnmesh Baile
This document provides an overview of an advanced Excel training session. It discusses key topics that will be covered, including formulas, functions, formatting, importing/exporting data, and working with large spreadsheets. Objectives for the training are outlined, such as entering formulas using keyboard/point mode, applying functions like AVERAGE, MAX, MIN, and formatting techniques like conditional formatting and changing column/row sizes. Examples are provided of summarizing stock data in Excel using these skills.
This chapter discusses fundamentals of hypothesis testing for one-sample tests. It covers:
1) Formulating the null and alternative hypotheses for tests involving a single population mean or proportion.
2) Using critical value and p-value approaches to test the null hypothesis, and defining Type I and Type II errors.
3) How to perform hypothesis tests for a single population mean when the population standard deviation is known or unknown.
The document discusses pivot tables and pivot charts in Microsoft Excel. It provides instructions on how to create a basic pivot table by selecting data and dragging fields, and how to modify and filter the pivot table. It also explains how to create a pivot chart based on a pivot table and change the chart type. The document demonstrates multiple examples of advanced pivot table features like two-dimensional tables, calculated fields, and multi-level tables with multiple row and filter fields.
1) A pivot table is an interactive table that summarizes large amounts of data using calculation methods chosen by the user. It allows the data to be viewed from different perspectives by moving row and column headings.
2) The document provides steps to create a pivot table and pivot chart from sample sales data including product ID, name, price, quantity and total for each month and region.
3) Creating a pivot chart follows similar steps to a pivot table but in the wizard, "PivotChart Report" is selected instead of just "Pivot Table Report". Fields can then be dragged between areas to customize the summary and visualization.
The document provides an overview of formulas and functions in Microsoft Excel 2016. It defines formulas as sequences of values, cell references, names, functions or operators that produce a new value using an equal sign. Functions are prewritten formulas that perform operations and return values. The document describes common functions like SUM, AVERAGE, MAX, MIN, as well as date/time functions. It explains concepts like arguments, ranges, arrays, operators and cell references used in formulas.
Pivot Tables and Beyond Data Analysis in Excel 2013 - Course Technology Compu...Cengage Learning
Pivot Tables and Beyond Data Analysis in Excel 2013 - Course Technology Computing Conference
Presenter: Patrick Carey, Cengage Learning Author
Excel is sometimes called the most popular "database" in the world, not because it's a database but because it makes data so accessible that users often turn to spreadsheets for data entry. Yet for all that, Excel's tools for data analysis and modeling remain largely untapped by the average user. In this, pivot tables may be the most powerful and least utilized tool for data exploration. In this presentation we'll examine some of the new enhancements to pivot tables introduced in Excel 2013. We'll examine how to set up relationships using the Excel Data Model to summarize information across multiple data tables. And then we'll go beyond, exploring the data modeling and data visualizing tools provided by the PowerPivot and Power View add-ins, interpreting data not just numerically but through visual imagery, charts, and interactive maps.
This document provides an overview of advanced Excel skills and features. It begins by introducing pivot tables, which allow users to summarize and analyze large datasets. It then discusses various job roles that require advanced Excel skills, such as finance, HR, and analytics. Finally, it outlines the types of companies that employ advanced Excel users and the skills needed, such as automating tasks and using complex formulas.
A pivot table allows users to summarize, analyze, explore, and present large amounts of data in Excel spreadsheets more efficiently. It categorizes data into groups and calculates summaries faster than doing so manually. Pivot tables are useful for tasks like calculating data, designing reports, finding relationships within data, and formatting data in a way that makes trends easy to see. They reduce the number of steps needed for these tasks and the chances of human error.
This document provides an overview of key concepts in decision making covered in Chapter 16 of the textbook "Statistics for Managers Using Microsoft Excel". It begins by listing the chapter goals, which include describing decision making processes, constructing decision tables, applying expected value criteria, and accounting for risk attitudes. It then outlines the typical steps in decision making, such as listing alternatives and possible outcomes. Key decision making criteria are defined, like expected monetary value, expected opportunity loss, and value of perfect information. Examples are provided to demonstrate how to apply these concepts to make optimal decisions under uncertainty.
The document discusses plans for a new music magazine targeted at late teenagers and young adults. It will focus on indie rock music with some punk genres included. Research showed that most preferred magazine genres were sports and music, with rap, hip hop, pop, and heavy metal being the most popular music styles. The magazine will be priced between £3 to £5, in line with the price range most respondents thought magazines should cost.
This chapter discusses different types of charts that can be used to visualize quantitative data in Excel. It covers basic chart types like line, column, and pie charts, as well as more advanced types like radar and bubble charts. The chapter also explores chart sub-types and how to combine multiple chart types into a single dashboard chart to analyze business data. The objectives are to determine the appropriate chart type for different situations, modify charts effectively, and create advanced visualizations like management dashboards.
This document provides an overview of Chapter 2 which discusses using statistical analysis tools to solve problems. It introduces statistical functions that can determine values, structure data, and count/total data based on criteria. These functions include AVERAGE, AVERAGEIF, COUNTIF, LARGE, MEDIAN, MODE.SNGL, RAND, RANDBETWEEN, RANK.EQ, ROUND, SMALL, STDEV.S, and SUMIF. The chapter also covers performing what-if analysis, goal seek, simulation, and custom formatting. Level 1 objectives focus on understanding basic statistics and using functions to calculate mean, median, mode and standard deviation. Level 2 objectives involve evaluating data rankings, extremes, and counts/
The document discusses techniques for building multiple regression models, including:
- Using quadratic and transformed terms to model nonlinear relationships
- Detecting and addressing collinearity among independent variables
- Employing stepwise regression or best-subsets approaches to select significant variables and develop the best-fitting model
This document provides learning objectives and content for a chapter on applying fundamental Excel skills and tools to problem solving. It covers three levels of objectives: (1) defining errors and correcting formatting and formulas, (2) calculating data using basic functions like SUM and AVERAGE, and (3) analyzing cell references when writing and copying formulas, including relative, absolute, and mixed references. The chapter introduces skills for writing formulas, using functions, formatting worksheets, and handling errors. It also provides examples of analyzing a budget workbook using different referencing techniques.
Leveraging IBM Cognos TM1 for Merchandise Planning at Tractor Supply Company ...QueBIT Consulting
AGENDA:
Introductions and Company Overviews
TSC Merchandise Planning Solution Overview
Prior State
Solution and Implementation
Tips & Tricks for TM1 Perspectives Templates
Q&A
This document provides an overview of a training course on using statistical functions in Microsoft Excel. The course contains 3 lessons: 1) an introduction to using statistics in Excel, 2) writing good formulas, and 3) choosing the appropriate statistical function. The document outlines the goals of the course and what will be covered in each lesson, including examples of statistical formulas, common errors, and how to use the Insert Function tool to help write formulas.
Visio 2007 can be used to diagram all phases of a project including planning, design, engineering, and implementation. It allows importing timelines, Gantt charts, and project reports from Project 2007. Diagrams like timelines, Gantt charts, process flows, and responsibility matrices can be created. Data from Project and other sources can be linked to shapes to dynamically update diagrams.
This document provides an overview of techniques for presenting numerical data in tables and charts. It discusses ordered arrays, stem-and-leaf displays, frequency distributions, histograms, polygons, ogives, bar charts, pie charts, and scatter diagrams. The chapter goals are to teach how to create and interpret these various data presentation methods using Microsoft Excel. Examples are provided for frequency distributions, histograms, polygons, and ogives to illustrate how to construct and make sense of these graphical representations of quantitative data.
The document describes the components of an Excel chart and how to create a chart using the Chart Wizard. It discusses the chart area, plot area, axes, titles, grid lines, data series, data points, labels, legends. It provides steps for using the Chart Wizard to select data and create a column chart with options to add titles, axes, gridlines, legends, and data labels. Components of a chart include the chart area, plot area, axes, titles, grid lines, data series, data points, labels, and legends.
The document provides an agenda for a training on advanced Excel skills for account managers and associates. The agenda covers reviewing basic Excel functions, creating and customizing charts, copying charts into PowerPoint, using Paste Special, working with PivotTables and PivotCharts, and exploring advanced formulas and text manipulation functions like IF, VLOOKUP, SUMIF, LEFT, RIGHT, MID, and CONCATENATE. Exercises are included throughout to help participants practice and retain the skills covered in the training.
This document outlines an agenda and presentation for an MS Excel 2007 training session for business managers and professionals. The agenda covers topics such as Excel introduction and history, techniques like named ranges and lookups, tips and tricks, templates, pivot tables, formulas, sorting and filtering, connecting Excel to databases and the web, macros, and VBA. It also provides overviews of some key Excel concepts like the ribbon interface and absolute vs. relative references. Hands-on exercises are included to reinforce topics like creating invoices from templates and using formulas with different reference types.
Advance-excel-professional-trainer-in-mumbaiUnmesh Baile
This document provides an overview of an advanced Excel training session. It discusses key topics that will be covered, including formulas, functions, formatting, importing/exporting data, and working with large spreadsheets. Objectives for the training are outlined, such as entering formulas using keyboard/point mode, applying functions like AVERAGE, MAX, MIN, and formatting techniques like conditional formatting and changing column/row sizes. Examples are provided of summarizing stock data in Excel using these skills.
This chapter discusses fundamentals of hypothesis testing for one-sample tests. It covers:
1) Formulating the null and alternative hypotheses for tests involving a single population mean or proportion.
2) Using critical value and p-value approaches to test the null hypothesis, and defining Type I and Type II errors.
3) How to perform hypothesis tests for a single population mean when the population standard deviation is known or unknown.
The document discusses pivot tables and pivot charts in Microsoft Excel. It provides instructions on how to create a basic pivot table by selecting data and dragging fields, and how to modify and filter the pivot table. It also explains how to create a pivot chart based on a pivot table and change the chart type. The document demonstrates multiple examples of advanced pivot table features like two-dimensional tables, calculated fields, and multi-level tables with multiple row and filter fields.
1) A pivot table is an interactive table that summarizes large amounts of data using calculation methods chosen by the user. It allows the data to be viewed from different perspectives by moving row and column headings.
2) The document provides steps to create a pivot table and pivot chart from sample sales data including product ID, name, price, quantity and total for each month and region.
3) Creating a pivot chart follows similar steps to a pivot table but in the wizard, "PivotChart Report" is selected instead of just "Pivot Table Report". Fields can then be dragged between areas to customize the summary and visualization.
The document provides an overview of formulas and functions in Microsoft Excel 2016. It defines formulas as sequences of values, cell references, names, functions or operators that produce a new value using an equal sign. Functions are prewritten formulas that perform operations and return values. The document describes common functions like SUM, AVERAGE, MAX, MIN, as well as date/time functions. It explains concepts like arguments, ranges, arrays, operators and cell references used in formulas.
Pivot Tables and Beyond Data Analysis in Excel 2013 - Course Technology Compu...Cengage Learning
Pivot Tables and Beyond Data Analysis in Excel 2013 - Course Technology Computing Conference
Presenter: Patrick Carey, Cengage Learning Author
Excel is sometimes called the most popular "database" in the world, not because it's a database but because it makes data so accessible that users often turn to spreadsheets for data entry. Yet for all that, Excel's tools for data analysis and modeling remain largely untapped by the average user. In this, pivot tables may be the most powerful and least utilized tool for data exploration. In this presentation we'll examine some of the new enhancements to pivot tables introduced in Excel 2013. We'll examine how to set up relationships using the Excel Data Model to summarize information across multiple data tables. And then we'll go beyond, exploring the data modeling and data visualizing tools provided by the PowerPivot and Power View add-ins, interpreting data not just numerically but through visual imagery, charts, and interactive maps.
This document provides an overview of advanced Excel skills and features. It begins by introducing pivot tables, which allow users to summarize and analyze large datasets. It then discusses various job roles that require advanced Excel skills, such as finance, HR, and analytics. Finally, it outlines the types of companies that employ advanced Excel users and the skills needed, such as automating tasks and using complex formulas.
A pivot table allows users to summarize, analyze, explore, and present large amounts of data in Excel spreadsheets more efficiently. It categorizes data into groups and calculates summaries faster than doing so manually. Pivot tables are useful for tasks like calculating data, designing reports, finding relationships within data, and formatting data in a way that makes trends easy to see. They reduce the number of steps needed for these tasks and the chances of human error.
This document provides an overview of key concepts in decision making covered in Chapter 16 of the textbook "Statistics for Managers Using Microsoft Excel". It begins by listing the chapter goals, which include describing decision making processes, constructing decision tables, applying expected value criteria, and accounting for risk attitudes. It then outlines the typical steps in decision making, such as listing alternatives and possible outcomes. Key decision making criteria are defined, like expected monetary value, expected opportunity loss, and value of perfect information. Examples are provided to demonstrate how to apply these concepts to make optimal decisions under uncertainty.
The document discusses plans for a new music magazine targeted at late teenagers and young adults. It will focus on indie rock music with some punk genres included. Research showed that most preferred magazine genres were sports and music, with rap, hip hop, pop, and heavy metal being the most popular music styles. The magazine will be priced between £3 to £5, in line with the price range most respondents thought magazines should cost.
This document summarizes a research report that compares the brands Shan and National for recipe masala mixes in Pakistan. The report analyzed data from 80 respondents through a questionnaire. Key findings include:
- Shan was the most recalled brand at 46.3%, compared to National at 12.5%
- TV ads were the most effective promotion at 80% awareness
- 68.8% of respondents use Shan most frequently, compared to 28.8% for National
- Biryani masala mix was the most commonly used product at 51.2% usage
- Taste and aroma were considered the most important brand aspect by 65% of respondents.
This document describes the results of a statistical survey project conducted by Jonathan Peñate and Arnold Gonzalez. It includes the survey questions, sample sizes, means, standard deviations, and confidence intervals calculated for various survey questions. It also includes hypothesis tests comparing results to larger studies and testing for differences in responses between groups. The confidence intervals and hypothesis tests indicate there is no strong evidence of differences in the means or proportions compared.
This document appears to be a statistics project analyzing data from an survey given to students. It includes the survey questions, confidence intervals calculated for various questions, and hypothesis tests conducted. Confidence intervals are provided for means of questions regarding grade, age, number of siblings, people in household, and days of homework. Confidence intervals are also given for proportions of questions regarding gender, preferred sports to watch, phone type, food preference, and activities preference. A hypothesis test is described for number of homework days and a test comparing video game preference between males and females. Links to related larger studies are also provided.
This document appears to be a statistical research paper analyzing survey results from JRU students regarding their preferences for president in the 2010 Philippine election. It includes the following key points:
1. The paper aims to determine JRU students' preferences for president as well as differences between male and female students.
2. 250 JRU students were surveyed, with 115 male students and 135 female students.
3. The most common age for both male and female students was 20 years old.
4. The paper includes statistical analysis to test differences in preferences and perceptions between male and female students.
This document defines key concepts related to data arrays and frequency distributions. It discusses how data can be systematically arranged in arrays and organized into classes for grouped data. Different types of statistical data and concepts like population, sample, ungrouped vs grouped data are also defined. The document concludes by explaining methods to form frequency distributions, calculate class boundaries, relative frequencies, cumulative frequencies, and other metrics.
This document provides guidelines for a mathematics statistics project. The project requires students to organize and present information using tables, graphs, diagrams and appropriate notation. Students must demonstrate understanding of practical mathematics applications and use technology. They should use appropriate statistical methods, form a logical argument supported by evidence, and analyze personal research within a 1500 word limit. The project introduction should describe the topic and steps. Students must collect and logically organize relevant data, perform both simple and complex mathematical processes, interpret results, discuss validity, and communicate their work clearly. Example project ideas are provided.
The document discusses a study on the types of electronic gadgets used by industrial design students at the University of Santo Tomas. It aims to determine the most common gadgets, how long students use them, and if they have brand preferences. The methodology involves surveying 30 students about the gadgets they use, brands, and how the gadgets help with their studies. Preliminary results found that 12 students use 3 gadgets, 14 are comfortable with 3 brands, and gadgets are mostly used for 6-12 hours per day for research and schoolwork, with Apple being the most popular brand.
This is an example of a logical step on a statistical investigation. A group of students as research team came up with a problem statement, did data gathering, presented and analyzed the data and then interpreted the results...
I heard about this contest from this website, as I have had uploaded my Cyprus education presentation months ago.
Ay202122 oct sem bta ms excel proj specs finalMark Kor
This document outlines the requirements for an individual Excel project assignment worth 35% of the grade in a business technology and analytics course. Students must select one of six topic areas and use real public datasets from Singapore government data portals to create Excel worksheets analyzing their chosen topic. The assignment involves demonstrating basic and advanced Excel skills like formatting, formulas, charts, pivot tables, and creativity. Students will submit a draft for feedback and the final project is due by the end of the semester. The project will be assessed based on introduction, datasets, formatting, formulas, charts, pivot tables, and creativity used.
This document provides instructions for presenting diagrams, visual data, tables, and graphs in a laboratory report. It explains how to draw diagrams using Microsoft Word's drawing tools to clearly and accurately represent experimental setups. It also demonstrates how to create a scatter graph using Microsoft Excel to present results visually and how to properly format the graph, including labeling axes and adding a trendline equation. The goal is to help students learn best practices for incorporating visual elements into the results section of a lab report.
This document provides an overview and guidelines for the final project in ACC 690, which involves creating an Excel spreadsheet model to consolidate the financial statements of a parent company and subsidiary. The project has three milestones, where students will submit portions of the model in Modules 5, 8, and 10. The model must show consolidation entries, final income statement and balance sheet in local currency, and then translate the statements to US dollars using provided exchange rates. Requirements include preparing a visually pleasing report for the supervisor and using Excel features like macros.
This project for an accounting cost course challenges students to analyze the SEC 10-K report of a publicly traded US manufacturing corporation. Students will prepare a paper analyzing financial statements, compare to a non-manufacturing company, and identify opportunities. They will also create a spreadsheet with key financial metrics and ratios. Finally, students give a presentation identifying analysis, ratios, cost of goods sold, product line profitability, and recommendations. The goal is for students to review, interpret, and report on a corporation using its SEC filing.
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 1 of 3
STAT200 Introduction to Statistics
Assignment #2: Descriptive Statistics Analysis and Writeup
Assignment #2: Descriptive Statistics Analysis and Writeup
In the first assignment (Assignment #1: Descriptive Statistics Analysis Data Plan), you developed a
scenario about annual household expenditures and a plan for analyzing the data using descriptive
statistic methods. The purpose of this assignment is to carry out the descriptive statistics analysis plan
and write up the results. The expected outcome of this assignment is a two to three page write-up of
the findings from your analysis as well as a recommendation.
Assignment Steps:
Step #1: Review Feedback from Your Instructor
Before performing any analysis, please make sure to review your instructor’s feedback on Assignment
#1: Descriptive Statistics Data Analysis Plan. Based on the feedback, modify variables, tables, and
selected statistics, graphs, and tables, if needed.
Step #2: Perform Descriptive Statistic Analysis
Task 1: Look at the dataset.
• (Re)Familiarize yourself with the variables. Review Table 1: Variables Selected for the
Analysis you generated for the first assignment as well as your instructor’s feedback. In
addition, look at the data dictionary contained in the data set for information about the
variables.
• Select the variables you need for the analysis.
Task 2: Complete your data analysis, as outlined in your first assignment, with any needed
modifications, based on your instructor’s feedback.
• Calculate Measures of Central Tendency and Variability. Use the information from
Assignment #1 - Table 2. Numerical Summaries of the Selected Variables. Here again,
be sure to see your instructor’s feedback and incorporate into the analysis.
• Prepare Graphs and/or Tables. Use the information from Assignment #1 - Table 3.
Type of Graphs and/or Tables for Selected Variables. Here again, be sure to see your
instructor’s feedback and incorporate into the analysis.
STAT200: Assignment #2 - Descriptive Statistics Analysis and Writeup - Instructions
Page 2 of 3
Step #3: Write-up findings using the Provided Template
For this part of the assignment, write a short 2-3 page write-up of the process you followed and the
findings from your analysis. You will describe, in words, the statistical analysis used and present the
results in both statistical/text and graphic formats.
Here are the main sections for this assignment:
✓ Identifying Information. Fill in information on name, class, instructor, and date.
✓ Introduction. For this section, use the same scenario you submitted for the first assignment and
modified using your instructor’s feedback, if needed. Include Table 1 (Table 1: Variables
Selected for the Analysis) you used in Assignment #1 to show the variables you selected for the
analysis.
✓ Data .
COM 3135 Proposal AssignmentMANAGERIAL PROPOSAL INSTRUCTI.docxmccormicknadine86
COM 3135: Proposal Assignment
MANAGERIAL PROPOSAL INSTRUCTIONS
Learning outcomes
- Employ Toulmin's CDW model to craft a persuasive message to internal
stakeholders
- Construct a clear, convincing and impactful written managerial message
Deliverables
1. A written proposal: Write a persuasive proposal to the school dean and top
management, as an email message or an email attachment. You need to convince
the readership that a problem exists and that your solution will work.
2. An analysis of the argumentation: Write an explanation of how you have utilized
Toulmin’s CDW model (Roger’s article: ‘Building a case and arguing with
sophistication’)
Situation
- FIU has been undergoing huge changes recently and management is keen to receive
feedback from all stakeholders - faculty, staff, students - on how operations at the
FIU could be further improved.
- You are part of a student working group that has been formed to assess the present
situation in the school and propose ways in which FIU processes could be
enhanced.
- In other words, you need to identify an operational problem and develop a
workable solution to the problem. You can select a pressing issue that you would
like to have addressed.
- Examples of areas in which you might develop proposals:
1. FIU branding study abroad
2. Food services
3. Registration procedures
4. Library services
5. Sports facilities
6. Cooperation with businesses
7. Organization of studies
8. Housing
�1
https://owl.purdue.edu/owl/general_writing/academic_writing/historical_perspectives_on_argumentation/toulmin_argument.html
COM 3135: Proposal Assignment
Plan and write a proposal for action/change.
You will need to:
1. state (and summarize) the problem
2. identify explicitly the outcomes and benefits of your proposal
3. provide a convincing recommendation with supporting evidence which shows that
your recommendation is feasible
Request action
- Use Toulmin’s Claim-Data-Warrant communication model and the persuasive writing
guidelines.
- You will also need to pay attention to effective managerial writing.
- Properly format your proposal. Include a cover page.
�2
https://owl.purdue.edu/owl/subject_specific_writing/writing_in_engineering/indot_workshop_resources_for_engineers/documents/20080628094326_727.pdf
InstructionsExcel Skills | Exercises | Pivot Tableswww.excel-skills.comInstructionsVersions: Excel 2010 & Excel 2007Our practical Excel exercises are much more than just exercises! We design our exercises in such a way that they provide the user with a mapping of the Excel features that can be used in order to complete the appropriate task in the most efficient manner possible. We also reference each step in each exercise to the appropriate tutorial that needs to be studied in order to be able to complete the step.The solutions to our comprehensive exercises are only available to customers who have purchased either a full or training ...
Bogdan SalackiECON - 420R-Script for HW 4library(readxl).docxmoirarandell
Bogdan Salacki
ECON - 420
R-Script for HW 4
library(readxl)
Growth_1_ <- read_excel("~/Downloads/Growth (1).xlsx")
View(Growth_1_)
#a. In preparation a scatter plot, the columns growth and trade share have to be secluded
growth<-Growth_1_$growth
tradeshare<-Growth_1_$tradeshare
# When you see the values, the plot function can be put into effect
plot(growth,tradeshare)
#Based on the scatter plot, the data looks like to have a positive correaltion/relationship.
#b. Yes, Malta looks like detached because it is the only plot with the largest tradeshare compared with the rest of the data.
#c. To find regression of the data use code below:
reg1<-lm(growth~tradeshare)
#Then, summarize the data using: summary(reg1)
#slope for tradeshare= 2.3064
#estimated intercept for growth= 0.6403
#When tradeshare = 0.5 the regression equation is: 0.6403 + 2.3064 (0.5)= 1.7935
#When tradeshare = 1, the regression equation is: 0.6403 +2.3064 (1)= 2.9467
#e. To plot the regression line on the scatter plot, use the code abline(Reg1), and it will reveal a line for the data.
#f. Malta is shown in the scatter plot to the right, farthest away from the remaining data. A reason for Malta having such a large tradeshare could be that it's imports/exports are very different from the other countries in the data thus, affecting the size or amount of it. Malta's import/exports could be of the goods that are transported a lot faster or a lot slower than the rest of the countries being analyzed. Because of that, and also because Malta was determined to be differing from all other members, it cannot be included in the analysis.
Sheet1Content meets or exceeds criteria, is accurate and shows an extraordinary understanding through rich examples and explanations. Content meets criteria with minimal errors, is accurate and shows a clear understanding through appropriate examples and explanations. Content shows a basic understanding of key ideas, yet includes some inaccuracies.Content was not included or incomplete, and/or extremely inaccurate CriteriaPoints PossibleEarned PointsA+AA-B+BB-C+CC-D+DD-FOther100%95%91%87%85%81%77%75%71%67%65%61%0%TOTAL1000ExemplaryCompetentProgressingInsufficient/Not Evident>0% & <61%12002250335041005100N/AN/AAssignment Title:Module 06 Course Project - Final Project Proposal and Project PresentationPage Length Required:5-9 Pages (required APA components e.g. cover page, swot chart, direct quotes and reference page do not count toward page requirement)Rubric CriteriaPointsDescription120Completes Final Written Project Proposal on how the Annual Convention should be be planned and delivered using the modules from previous weeks. Follows the suggested Project outline: Project Selection, WBS, Scope statement, Communications plan, Risk analysis, Project Budget, Project Schedule, Resource Plan
225The final report is a minimum of 5 pages and significantly emphasizes project management. Included appendixes, charts, and tables. Note: Unreasonably sized app.
ECOM1000 – Project Part 2 Final Report ECOM1000 AnalyticEvonCanales257
ECOM1000 – Project Part 2: Final Report
ECOM1000: Analytics for Decision Making Page | 1
Faculty of Business and Law | School Accounting, Economics and Finance
CRICOS Provider Code 00301J
Curtin University, Semester 2, 2021
ECOM1000 Project
Part 2 (35%) – Final Report
The country representatives have accepted your proposal. Please go ahead with carrying
out the activities/tasks mentioned in the proposal (part 1). In addition to the activities
stated in part 1, the representatives would also like you to include the following items in
your report:
1. Explore the relationship across a pair of different aspects of the country over time.
For example, is there a relationship between the population and the environment
indicators over time? Can this relationship be quantified? Note, that your choice
of aspects could be influenced by the available data.
2. Construct a confidence interval for one of the aspects. Please state all
assumptions clearly and provide an interpretation of the interval.
3. Are there any legal or privacy issues with the data that is being used in the report?
Please provide some details/justification.
The three requests above must be incorporated into the methodology section i.e. update
the methodology section from part 1. As before, we are expected to apply the knowledge
from the unit modules to address these requests.
One of the main features of the final report is the results of the analysis. For this section
you are expected to produce a dashboard using the data for your country. The dashboard
is simply a collection of different types of graphs (similar to the ones in our tutorial/lab
work). The emphasis is presenting the data using different types of plots such as time
series plots, scatter plots, histograms, box plots and/or cumulative percentage charts.
Ensure that the plot type is matched well with the data that is being used. In addition to
this, results should also include numerical data summaries as well as the analysis
pertaining to the first two requests.
Lastly, it is very important that we provide brief commentary on all plots/results of the
analysis. The commentary is expected to be based on the content covered in the unit.
The final report should contain the following components:
Title page – update from part 1
Cover letter – update from part 1: This should now also include an updated
statement about what the report is about. It should explicitly state any changes (if
applicable) that you have made since the original proposal.
Tables of contents – update from part 1
Executive summary – A brief outline/summary of what the report contains. This
summary must be between 0.75 to 1 page maximum. This summary must NOT
contain any plots and/or tables. It is strongly advised that this section be written
at the end once all the other sections have been finalis ...
Communicating information from a screen or piece of paper easily and accurately often requires as much planning in the layout as it does in the collation / creation of results.
Even simple ad-hoc pieces of work and analysis will benefit from consistent and clear formatting.
What’s the secret?
While there’s no single “right” format, there are general principles and Excel shortcuts that can assist you.
This white paper sets out some key principles you can apply to your next Excel model, report or dashboard.
This document provides guidance and practice for annotating charts in PowerPoint for an exam. It includes:
1. Typical exam question wording asking for technical analysis of index and share charts.
2. Advice on using lines and text boxes in PowerPoint to annotate charts, including formatting options.
3. Examples of annotated index and share charts and blank practice charts for the reader to annotate.
The document discusses recommendations for engineers conducting structural calculations using various software programs like STAAD, SAP2000, RISA, and SFrame. It recommends standardizing loads and load cases, using relevant information in the main report, and moving output files to appendices. It also recommends using Excel as a notepad for calculations and Word to extensively annotate and include graphics. The document provides an example outline for organizing calculation sections and subsections with indexes, revision sheets, introduction, and reference drawings.
Report format template sample from assignmentsupport.com essay writing services https://writeessayuk.com/
The document provides guidelines for submitting the final report for an EE 402 course, including:
- Reports must be submitted electronically in Microsoft Word or PDF/HTML format.
- The report should include sections on the problem, background, objectives, design approach, design documentation, test plan and results.
- The report must follow specific formatting guidelines for style, layout, headings, tables, figures, and references.
- Permission is required to use copyrighted materials from other sources.
1
ACC ACF 2400 – Semester 2, 2017
Individual Assignment 1:
Building a Business Dashboard
Overview
A business dashboard is ‘a style of reporting that depicts KPIs, operational or strategic information with
intuitive and interactive displays’ (Turban et al., 2015 p. 380). It is a single screen snapshot of how a
business, department, or process is performing. The design varies considerably from one application
to another, and even between businesses, but a common feature of a dashboard is that it uses graphs,
coloured text, and symbols to show the viewer, at a glance, the current status. A dashboard should
only contain information that actually influences performance. Many dashboards are interactive
because it can be difficult to show every important detail at once.
You are an employee at Australian Electronics Pty Ltd. You have been assigned the task of designing
a report that will be used by managers involved in purchasing, sales, and inventory management.
Your boss, Mary Smith, suggest including at least four (4) ratios. Regarding the ratios, Mary thinks
that Inventory Turnover and Sales Growth are a must.
This is an individual assignment. There is no fixed answer, so be creative!! The spreadsheet must
perform ratio analysis to show the current status of the inventory holdings and sales. Marks are
awarded according to how well the dashboard meets the requirements specified in the rubric.
A data set is supplied with this guide in Moodle (ACC ACF 2400_s2 2017_Inventory Statistics.xlsx). The
Inventory Statistics data set contains four sheets: sales value, sales quantity, the quantity of inventory
on hand, and the quantity purchased. You should use all sheets in your calculations, but may need to
restructure some data on a separate calculation sheet to ensure data is in the format you need.
Instructions on how to build a complex interactive scorecard have been published in different journals
such as the Journal of Accountancy
(http://www.journalofaccountancy.com/issues/2011/feb/20092427.html), but you do not have to
build such a complex system if your spreadsheeting skills are not well developed.
The table below contrasts two different approaches. The example on the left shows 7 ratios in a non-
interactive dashboard, with three graphs and one table of numbers. It is clearly not an inventory
management dashboard, but if the design features included were tailored to the inventory
management context, it would likely earn a pass (providing instructions, the input sheet, and the
calculations sheet are acceptable).
The example on the right, however, is from the Dashboard your Scorecard article. It is also not an
inventory management dashboard and does not show ratios, and so is not acceptable, but illustrates
elements that will earn higher marks:
• It is interactive (note the drop-down box in the bottom right graph to select the person shown);
• It uses conditional for ...
reportDescription.docxETME 4143LThermodynamics and Heat Tran.docxdebishakespeare
reportDescription.docx
ETME 4143L
Thermodynamics and Heat Transfer Laboratory
Formal Report
Assignment Description
The purpose of the formal report is to comprehensively communicate results of your experiment using your pre-lab report as a draft. Formal reports must include the following sections.
The instructor will conduct a preliminary review of each report to evaluate technical writing skills. Upon the discretion of the instructor, reports that do not significantly satisfy the criteria outlined in the Technical Writing Evaluation Checklist will earn a grade of 50 with no further consideration.
Cover Page (5 points)
The formal report requires a specific cover page which is available on Moodle.
Table of Contents (5 points)
The Table of Contents lists all section and sub-section titles and the page numbers that correspond to the beginning of every section and sub-section. Its format should conform to that specified in the Chicago Manual of Style.
Overall Report Quality (10 points)
A technical report should be written with an emphasis placed on format, presentation of tables and figures, and overall writing skills. See document titled Technical Writing Evaluation Checklist for more detail.
Summary (15 points)
The Summary is limited to 300 words and does not include nor reference tables, graphs, or figures that may be included in the body of your report. Its purpose is to communicate key messages excerpted from other sections of your report, which is why it is written last. It must explain why the experiment was conducted, its scientific and/or practical relevance, results of calculations, and a brief discussion and conclusion about the results.This section must stand alone.You must assume that it is the only part of the report that will actually be read by your supervisor or client.
The Summary section must briefly answer each of the following questions:
· What was the purpose of the experiment?
· What is its scientific and/or practical relevance?
· How was the experimentconducted? What equipment was used?
· What engineering assumptions were made when analyzing sampledata?
· What are the key results based on experimentaldata? Include specific values with units of measure.
· Do results fall within expected ranges? Justify based on theory or research.
· What are some possible limitations or sources of error associated with the experiment and/or data analysis?
· What conclusions or recommendations should be made based on experimental resultsand why?
The order of these questions may change depending on how you structure this section of the report. Be sure to change to past tense verbs and report actual experimental data and results prior to cutting and pasting from your pre-lab report.
Introduction (10 points)
This section provides a comprehensive description of the engineering theory, practical applications, and contemporary issues associated with the experiment. It first briefly reiterates the purpose of the experiment and ...
USE ATTACHMENTSYou have made it to the final project, in w.docxgibbonshay
**USE ATTACHMENTS**
You have made it to the final project, in which you are putting all your data together and providing the story and analysis as if you actually performed the research. This assignment will provide you the experience of statistics in the research process.
Create
a 10- to 15-slide presentation, including detailed speaker notes, discussing your statistics project data analyses.
Include
the following in your presentation:
An introduction that includes the data and variables: This information is provided on the information tab of the Microsoft® Excel® data set.
A description and results of each analysis
The descriptive statistics
The
t-
test or ANOVA
The bivariate correlations
A conceptual summary of the results stating what they tell you about the data
Format
any citations in your presentation according to APA guidelines.
...
Financial Modelling Course including an Excel Financial Model TemplateAurelien Domont, MBA
Go to www.slidebooks.com to Download and Reuse Now a Financial Modelling Course including an Excel Financial Model Template| Created By ex-Deloitte Consultants & Investment Bankers.
Financial Modelling Course including an Excel Financial Model Template
Statistical Project Specification
1. MAT10251 STATISTICAL ANALYSIS
Data Analysis Project
This project leads you through a statistical analysis of the daily change in the closing
price of an ASX (Australian Securities Exchange) Index for 2008 and 2009. Also, the
project investigates, for the same index, the relationship between the daily volume of
shares traded and the daily turnover for 2008.
Data obtained from Sydney Morning Herald at http://business.smh.com.au/ , October
2008, January 2009 and September 2009
Part A covers Topics 1, 5, 6 and 7 and Part B Topics 8 to 11 of the unit.
It is suggested that you work on this project throughout the semester.
The data for this project can be accessed from the MAT10251 website on MySCU
To obtain your data
(1) Click on the 'Assessment Items'.
(2) Click on the ‘Data for Data Analysis Project’. This will download an Excel file.
(3) Save this as a new Excel file.
You are expected to use Excel when completing the project. Your findings and
conclusions should be submitted as a word document into which your Excel outputs
have been copied.
You should submit your project online using Project Submission.
Each part (A and B) of the project should be presented as a three to five page Word file
with Excel output embedded. The given cover sheets should be included as the first
pages.
Furthermore, each part is required to have an appendix, which should be a single
document in one of the following formats:
• Excel with added comments, make sure that this file is formatted so that each
worksheet can be printed as a single page.
• Word with Excel output embedded
• Handwritten with Excel which has been scanned and submitted as a pdf file.
However, for ease of marking please also include your appendix at the end of your
report. If necessary, cut and paste it into your Word file.
Note If you do not have Excel, you may use another computer spreadsheet or
statistical software package.
.
MAT10251: Statistical Analysis Project 2009
2. STUDENT NAME:
STUDENT ID NUMBER:
MAT10251 – Statistical Analysis
Data Analysis Project
Part A
Please use this cover page when submitting your project
Complete the summary table below.
Choice
Index
Value: 15%
PLEASE ENSURE YOU KEEP A COPY OF YOUR PROJECT
MAT10251: Statistical Analysis Project 2009
3. MAT10251 STATISTICAL ANALYSIS
Data Analysis Project – Part A
(Marked out of 30 but worth 15% of final assessment)
Choose an index, and fill in the summary table on the cover page.
For this index in Part A we will explore the “Change in Price” data for 2008 and 2009
Statistical Working
The following statistical tasks should appear as an appendix to your report. This
should include all necessary steps and appropriate Excel output.
The appendix should be a single document in one of the following formats:
• Excel with added comments; make sure that this file is formatted so that each
worksheet can be printed as a single page.
• Word with Excel output embedded
• Handwritten with Excel which has been scanned and submitted as a pdf file
However, for ease of marking please also include your appendix at the end of your
report. If necessary, cut and paste it into your Word file.
Descriptive Statistics (4 marks)
For your chosen index, analyse the daily change in the closing price for 2008 by using
the data in the “Change in Price” column for 2008 to
• Plot the data graphically – only need to submit one graph, but no penalty if you
submit more.
• Calculate the summary statistics for the daily change in closing price for 2008.
Statistical Inference (16 marks)
For your chosen index use the data in the “Change in Price” column for 2008 and/or
2009 and appropriate statistical inference techniques to answer the following:
• What was the average daily change in closing price of your chosen index in
2008?
• On the majority of days during 2008, did your chosen index fall in price?
• For your chosen index, is there a difference in the average daily change in
closing price between 2008 and 2009?
MAT10251: Statistical Analysis Project 2009
4. Notes
• You do not need to repeat any Excel calculations by hand. However, make sure
that you define your random variables and include any steps not given by
Excel. For example, in a hypothesis test include the null and alternative
hypotheses, along with the decision to reject or not reject the null hypothesis.
• Mention any assumptions you are required to make to answer the above.
• Comment on why the test/confidence interval has been chosen
• Make sure you interpret your confidence interval/s and write a conclusion to
your hypothesis test/s.
Report (10 marks)
Present your graph, statistics, and calculations in a brief report or business memo,
along with your interpretations and conclusions.
This should be three to five pages with a maximum of 1000 words. The report should
be submitted as a Word file with Excel output embedded with the given cover pages as
the first two pages.
Make sure you:
• Describe your samples and populations
• Include your graph.
• Discuss the shape, centre and dispersion of your graph/s. What conclusions can
you reach about the distribution or pattern of the daily change in the closing
price of your chosen index?
• Discuss and interpret the summary statistics. In particular, present conclusions
about the centre and variability of the daily change in the closing price of your
index for 2008.
• Include any necessary assumptions needed for your hypothesis test/s and
confidence interval/s. If assumptions are made how likely they are to be correct
and if not correct how would this affect the results? If no assumptions are
necessary mention this and why.
• Present the results of your hypothesis test/s and confidence interval/s without
unnecessary statistical jargon.
• Comment on the level of significance or confidence level chosen and how this
relates to the reliability of your conclusions.
MAT10251: Statistical Analysis Project 2009
5. Marking Criteria – Part A
See the marking and feedback sheet for allocation of marks.
Statistical Calculation
• To obtain full marks graph must be correct, including correct labels on both axes
and a title. Marks will be deducted if:
o Graph incorrect
o Excel not used
o Axes incorrectly or not labelled
o No title
o Scale on axes distorts graphs.
• To obtain full marks for the summary statistics copy the output table of the
Descriptive Statistics command in Data Analysis. You may delete unnecessary
statistics in this table.
• Marks will be deducted if this table is incorrect, so check:
o Your sample size
o Whether you are calculating sample statistics or population parameters.
• For the confidence interval/s and hypothesis test/s marks will be given for:
o Choice of appropriate statistical technique/s.
o Random variable defined
o Correct hypotheses for a test
o Correct statistical calculations, including Excel
o Correct interpretation of results.
MAT10251: Statistical Analysis Project 2009
6. Report
• Maximum 1000 words and 5 pages - marks will be deducted if this is greatly
exceeded.
• To obtain full marks report must:
o Be well structured
o Clearly communicate the results of the Excel output in language appropriate
for your audience
o Include your conclusions in the context of the data.
o Include appropriate graphs and tables to summarise your results.
• Marks will be deducted if:
o There is little or no comment on, or interpretation of, the Excel output
o Unnecessary statistical jargon and equations appear
o Report is confusing or not readable
o Report is handwritten
• Marks will not be deducted for minor spelling and grammatical errors. However,
marks will be deducted for spelling and grammatical errors that affect the
readability of the report.
• As there is no specified format for the report, no marks will be given or deducted
for format.
Notes
• You should not need to read beyond the study guide and textbooks to complete the
project.
• You probably will not need to reference, but if you do use any consistent
referencing style.
MAT10251: Statistical Analysis Project 2009
7. STUDENT NAME:
STUDENT ID NUMBER:
MAT10251 – Statistical Analysis
Data Analysis Project
Part B
Please use this cover page when submitting your project
Complete the summary table below.
Choice
Index
Value: 15%
PLEASE ENSURE YOU KEEP A COPY OF YOUR PROJECT
8. MAT10251 STATISTICAL ANALYSIS
Data Analysis Project – Part B
(Marked out of 30 but worth 15% of final assessment)
Choose an index, and fill in the summary table on the cover page.
In Part B we will further explore the “Change in Price” data for 2009, as well as
exploring the “Volume millions”’ and “Turnover A$ million”. data for 2009.
Statistical Working
The following statistical tasks should appear as an appendix to your report. This
should include all necessary steps and appropriate Excel output.
The appendix should be a single document in one of the following formats:
• Excel with added comments; make sure that this file is formatted so that each
worksheet can be printed as a single page.
• Word with Excel output embedded
• Handwritten with Excel which has been scanned and submitted as a pdf file
However, for ease of marking please also include your appendix at the end of your
report. If necessary, cut and paste it into your Word file.
Further Statistical Inference (11 marks)
• Assuming that the daily change in closing price is normal for all indices, is there a
difference in daily change in closing price in the five indices for 2009?
• For your chosen index, check the normality assumption above.
Notes.
• Use Excel for statistical calculations. You do not need to repeat any Excel
calculations by hand. However, make sure that you define your random variables
and include any steps, including null and alternative hypothesis, not given by
Excel.
• Mention any assumptions you must make.
• Make sure you write a conclusion to your hypothesis tests.
9. Regression and Correlation (7 marks)
For your given index, investigate the relationship between the volume of trade and the
daily turnover in 2009 by using the data in the “Volume millions”’ and “Turnover A$
million” columns for 2009 to
• Plotting the data graphically
• Calculating the least squares regression line, correlation coefficient and coefficient
of determination.
• Assume on a given day during 2009 that 600,000,000 shares of your chosen index
were traded. Using an appropriate interval estimate the turnover on this day.
Notes:
• Use Excel for statistical calculations. You do not need to repeat any Excel
calculations by hand. However, make sure that you define your random variables
and include any steps not given by Excel.
• Mention any assumptions you need to make.
• Comment on why an interval has been chosen
• Make sure you write a conclusion to your interval
Report (12 marks)
(10 marks)
Present your graphs, statistics, and calculations in a brief report or business memo,
along with your interpretations and conclusions.
This should be three to five pages with a maximum of 1000 words. Furthermore, the
report should be submitted as a Word file with Excel output embedded with the given
cover pages as the first two pages.
Make sure you:
• Include any necessary assumptions needed for your tests and interval
• If assumptions are made how likely, they are to be correct and if not correct how
would this affect the results? If no assumptions are necessary mention this and why.
• Mention any concerns you have about the validity of results due to violations of
required conditions.
• Present the results of your tests without unnecessary statistical jargon.
• Comment on the level of significance and how this relates to the reliability of your
conclusions.
• Include your graph.
• Explain your choice of independent and dependent variable when exploring the
relationship between daily volume of trade and turnover.
10. • Discuss any apparent relationship between the daily volume of trade and turnover.
Comment on the strength, shape and sign of the relationship. Is this relationship
what you would have expected?
• Use the least squares regression line to estimate daily turnover from volume of
trade. Give an expression for estimated daily turnover in the report.
• Interpret the value of the gradient of the least squares regression line. What
conclusions can you draw about the value of a typical share traded in 2008?
• Interpret the value of the vertical intercept of the least squares regression line. Is
this value valid? Explain. If the value is not valid, theoretically what should the
value of the vertical intercept be?.
• Discuss and interpret the values of correlation coefficient and coefficient of
determination. In particular, are these values consistent with your graph?
• Mention any concerns you may have about the validity of your results due do a non-
linear relationship, extreme values etc.
(2 marks)
Furthermore, assume that after you submitted your report for Part A, that you obtained
the population data for 2008, which enabled you to calculate the population parameters
for 2008, mean daily change in closing price and proportion of days index fell during
2008. These parameters will be available on MySCU after Part A is submitted.
Include in you report a comment on the value of these parameters and your
conclusions in Part A. In particular,
• Did your confidence interval contain the population parameter?
• Did you make the right decision in your hypothesis test? If not was the error Type
I or Type II?
11. Marking Criteria – Part B
See the marking and feedback sheet for allocation of marks.
Statistical Calculation
• For the tests and interval marks will be given for:
o Choice of appropriate statistical technique/s.
o Random variable/s defined
o Correct hypotheses for a test
o Correct statistical calculations, including Excel
o Correct interpretation of results.
• To obtain full marks graph must be correct, including correct labels on both axes
and a title. Marks will be deducted if;
o Graph incorrect
o Excel not used
o Axes incorrectly or not labelled
o Incorrect independent and dependent variables
o No title
o Scale on axes distorts graphs.
• To obtain full marks for the least squares regression line, correlation coefficient
and coefficient of determination, you can use either:
o The Regression command in Data Analysis and copy resultant table into
report.
o Or insert a trendline on a scatter diagram, with both the equation and r 2
value showing, you will then need to manually calculate value of r.
• Marks will be deducted if Excel is not used and also for incorrect equations or
coefficients, so check:
o Your independent and dependent variables
o Your sample size
12. Report
• Maximum 1000 words and 5 pages - marks will be deducted if this is greatly
exceeded.
• Also, to obtain full marks report must:
o Be well structured and analysed
o Clearly communicate the results of the Excel output in language appropriate
for your audience
o Include your conclusions in the context of the data.
o Include appropriate graphs and tables to summarise your results.
• Marks will be deducted if:
o There is little or no comment on, or interpretation of, the Excel output
o Unnecessary statistical jargon and equations appear
o Report is confusing or not readable
o Report is handwritten
• Marks will not be deducted for minor spelling and grammatical errors. However,
marks will be deducted for spelling and grammatical errors that affect the
readability of the report.
• As there is no specified format for the report, no marks will be given or deducted
for format.
Notes
• You should not need to read beyond the study guide and textbooks to complete the
project.
• You probably will not need to reference, but if you do use any consistent
referencing style.