This document provides an overview of SPSS and how to perform basic analyses in it. It discusses the four main windows in SPSS: the data editor, output viewer, syntax editor, and script window. It then covers how to open and manage data files, define variables, sort and transform data. The document concludes by demonstrating how to conduct frequency analyses, descriptive statistics, linear regression analyses, and plot regression lines in SPSS through both the graphical user interface and syntax editor.
Statistical Package for Social Science (SPSS)sspink
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This presentation includes the introduction of SPSS is basic features of Spss, how to input data manually, descriptive statistics and how to perform t-test, Anova and Chi-Square.
Statistical Package for Social Science (SPSS)sspink
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This presentation includes the introduction of SPSS is basic features of Spss, how to input data manually, descriptive statistics and how to perform t-test, Anova and Chi-Square.
This presentation is about Basic Statistics-related to types of Data-Qualitative and Quantitative, and its Examples in everyday life- By: Dr. Farhana Shaheen
This is a very basic guide to SPSS. It is aimed at total novices wishing to understand the basic layout of the package and how to generate some simple tables and graphs
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
This presentation is about Basic Statistics-related to types of Data-Qualitative and Quantitative, and its Examples in everyday life- By: Dr. Farhana Shaheen
This is a very basic guide to SPSS. It is aimed at total novices wishing to understand the basic layout of the package and how to generate some simple tables and graphs
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
Indicateur d'arrivĂŠe de d'eau/ DĂŠtecteur de pluie Adad Med ChĂŠrif
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A brief introduction for beginners. Topic included: background history of SPSS, some basics but effective data management techniques, frequency distribution, descriptive statistics, hypothesis testing rule, association test/ contingency table test. All these statistical topics are explained with easy hands on example with basic data-set. This slide also provide a short but effective understanding about p-value, which is very important for statistical decision making
SPSS is widely used program for statistical analysis in social sciences, particularly in education and research. However, because of its potential, it is also widely used by market researchers, health-care researchers, survey organizations, governments and, most notably, data miners and big data professionals.
Dev Dives: Train smarter, not harder â active learning and UiPath LLMs for do...UiPathCommunity
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https://arxiv.org/abs/2306.08302
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After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more âmechanicalâ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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Session Overviewâ
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
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- Demonstration of InfluxDB and Grafana using a practice web application
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2. The course content
ďAbout the four-windows in SPSS
ďThe basics of managing data files
ďThe basic analysis in SPSS
3. Introduction: What is SPSS?
ďOriginally it is an acronym of Statistical
Package for the Social Science but now it
stands for Statistical Product and Service
Solutions
ďOne of the most popular statistical
packages which can perform highly
complex data manipulation and analysis
with simple instructions
4.
5. The Four Windows: Data Editor
ďData Editor
Spreadsheet-like system for defining, entering, editing,
and displaying data. Extension of the saved file will be
âsav.â
6. The Four Windows: Output Viewer
ďOutput Viewer
Displays output and errors. Extension of the saved file will
be âspv.â
7. The Four Windows: Syntax editor
ďSyntax Editor
Text editor for syntax composition. Extension of the
saved file will be âsps.â
8. The Four Windows: Script Window
ďScript Window
Provides the opportunity to write full-blown programs,
in a BASIC-like language. Text editor for syntax
composition. Extension of the saved file will be âsbs.â
11. Opening SPSS
ďThe default window will have the data editor
ďThere are two sheets in the window:
1. Data view 2. Variable view
12. Data View window
ďThe Data View window
This sheet is visible when you first open the Data Editor
and this sheet contains the data
ďClick on the tab labeled Variable View
Click
13. Variable View window
ďThis sheet contains information about the data set that is stored
with the dataset
ďName
ď The first character of the variable name must be alphabetic
ď Variable names must be unique, and have to be less than 64
characters.
ď Spaces are NOT allowed.
14. Variable View window: Type
ďType
ď Click on the âtypeâ box. The two basic types of variables
that you will use are numeric and string. This column
enables you to specify the type of variable.
15. Variable View window: Width
ďWidth
ďWidth allows you to determine the number of
characters SPSS will allow to be entered for the
variable
16. Variable View window: Decimals
ďDecimals
ďNumber of decimals
ďIt has to be less than or equal to 16
ď3.14159265
18. Variable View window: Values
ďValues
ďThis is used and to suggest which numbers
represent which categories when the
variable represents a category
19. Defining the value labels
ďClick the cell in the values column as shown below
ďFor the value, and the label, you can put up to 60
characters.
ďAfter defining the values click add and then click OK.
Click
20. Practice 1
ďHow would you put the following information into SPSS?
Value = 1 represents Male and Value = 2 represents Female
Name Gender Height
JAUNITA 2 5.4
SALLY 2 5.3
DONNA 2 5.6
SABRINA 2 5.7
JOHN 1 5.7
MARK 1 6
ERIC 1 6.4
BRUCE 1 5.9
23. Saving the data
ďTo save the data file you created simply click âfileâ and
click âsave as.â You can save the file in different forms
by clicking âSave as type.â
Click
25. Sorting the data (contâd)
ďDouble Click âName of the students.â Then click
ok.
Click
Click
26. Practice 2
ďHow would you sort the data by the
âHeightâ of students in descending order?
ďAnswer
ďClick data, sort cases, double click âheight of
students,â click âdescending,â and finally click ok.
28. Transforming data (contâd)
ďExample: Adding a new variable named âlnheightâ which is
the natural log of height
ď Type in lnheight in the âTarget Variableâ box. Then type in
âln(height)â in the âNumeric Expressionâ box. Click OK
Click
30. Practice 3
ďCreate a new variable named âsqrtheightâ
which is the square root of height.
ďAnswer
31.
32. The basic analysis of SPSS that will
be introduced in this class
ďFrequencies
ďThis analysis produces frequency tables showing
frequency counts and percentages of the values of
individual variables.
ďDescriptives
ďThis analysis shows the maximum, minimum,
mean, and standard deviation of the variables
ďLinear regression analysis
ďLinear Regression estimates the coefficients of the
linear equation
33. Opening the sample data
ďOpen âEmployee data.savâ from the SPSS
ďGo to âFile,â âOpen,â and Click Data
34. Opening the sample data
ďGo to Program Files,â âSPSSInc,â âSPSS16,â and
âSamplesâ folder.
ďOpen âEmployee Data.savâ file
36. Frequencies
ďClick gender and put it into the variable box.
ďClick âCharts.â
ďThen click âBar chartsâ and click âContinue.â
Click Click
39. Using the Syntax editor
ďClick âAnalyze,â âDescriptive statistics,â then
click âFrequencies.â
ďPut âGenderâ in the Variable(s) box.
ďThen click âCharts,â âBar charts,â and click
âContinue.â
ďClick âPaste.â
Click
40. Using the Syntax editor
ďHighlight the commands in the Syntax editor
and then click the run icon.
ďYou can do the same thing by right clicking the
highlighted area and then by clicking âRun
Currentâ
Click
Right
Click!
41. Practice 4
ďDo a frequency analysis on the
variable âminorityâ
ďCreate pie charts for it
ďDo the same analysis using the
syntax editor
44. Descriptives
ďClick âAnalyze,â âDescriptive statistics,â then
click âDescriptivesâŚâ
ďClick âEducational levelâ and âBeginning
Salary,â and put it into the variable box.
ďClick Options
Click
45. Descriptives
ďThe options allows you to analyze other
descriptive statistics besides the mean and Std.
ďClick âvarianceâ and âkurtosisâ
ďFinally click âContinueâ
Click
Click
48. Regression Analysis
ďFor example letâs analyze the model
ďPut âBeginning Salaryâ as Dependent and âEducational Levelâ as
Independent.
ξββ ++= edusalbegin 10
Click
Click
50. Plotting the regression line
ďClick âGraphs,â âLegacy Dialogs,â
âInteractive,â and âScatterplotâ from the
main menu.
51. Plotting the regression line
ďDrag âCurrent Salaryâ into the vertical axis box
and âBeginning Salaryâ in the horizontal axis box.
ďClick âFitâ bar. Make sure the Method is
regression in the Fit box. Then click âOKâ.
Click
Set this to
Regression!
52.
53. Practice 5ďFind out whether or not the previous experience
of workers has any affect on their beginning
salary?
ďTake the variable âsalbegin,â and âprevexpâ as
dependent and independent variables
respectively.
ďPlot the regression line for the above analysis
using the âscatter plotâ menu.