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DESCRIPTIONA complete guide for beginners on how to use SPSS for research and analysis. Step by step instructions on how to define variables, run correlation analysis, establish a multiple response set, edit a chart or graph, and much more!
PASW Statistics 17 (SPSS 17) Part 1: Descriptive Statistics
PASW Statistics 17 (SPSS 17)Information Technology Services
California State University, Los Angeles www.youtube.com/mycsula
Winter 2010Table of ContentsIntroduction Part 14Downloading the Data Files4Starting PASW Statistics4The PASW Statistics Window5Data View5Variable View6Creating a Data File6Defining Variables6Data Entry8Descriptive Statistics9Frequency Analysis9Crosstabs11Data Manipulation12Select Cases12Splitting a File14Find and Replace15Reporting16Appendix17Introduction Part 218Downloading the Data Files18Null Hypothesis18Statistical Tests19Tests of Significance19Correlations19Paired-Samples T Test20Independent-Samples T Test22Multiple Response Sets23Multiple Response Frequencies24Multiple Response Crosstabs25Data Manipulation27Copying and Pasting Variable Properties27Inserting Variables and Cases29Deleting Variables and Cases30Merging Data Files30Creating the Data File for Merging30Inputting the Data in Variable View30Merging the Data Files32Appendix35Introduction Part 337Downloading the Data Files37Simple Regression37Scatter Plot37Predicting Values of Dependent Variables39Predicting This Years Sales with Simple Regression Model41Multiple Regression43Predicting Values of Dependent Variables43Predicting This Years Sales with Multiple Regression Model45Data Transformation46Computing46Polynomial Regression47Regression Analysis48Analyzing the Results48Chart Editing49Adding a Line to the Scatter Plot49Manipulating the Scales on X- and Y-axes50Adding a Title to the Chart52Adding Colors to the Chart53Filling a Background Color54Introduction Part 455Downloading the Data Files55Chi-Square55Chi-Square Test for Goodness-of-Fit55With Fixed Expected Values55With Fixed Expected Values and within a Contiguous Subset of Values58With Customized Expected Values59One-Way Analysis of Variance60Post Hoc Tests63Two-Way Analysis of Variance65Importing/Exporting Microsoft Excel and PowerPoint68Using Scripting for Redundant Statistical Analyses71Introduction Part 1PASW stands for Predictive Analytics Software. This program can be used to analyze data collected from surveys, tests, observations, etc. It can perform a variety of data analyses and presentation functions, including statistical analysis and graphical presentation of data. Among its features are modules for statistical data analysis. These include 1) descriptive statistics, such as frequencies, central tendency, plots, charts, and lists; and 2) sophisticated inferential and multivariate statistical procedures, such as analysis of variance (ANOVA), factor analysis, cluster analysis, and categorical data analysis. PASW Statistics is particularly well-suited for survey research, though by no means is it limited to just this topic of exploration.This handout (Descriptive Statistics) introduces basic skills necessary to run PASW Statistics. It includes how to create a data file and run descriptive statistics. It is especially tailored to answer three research questions formulated in the sample survey questionnaire, eventually giving users an overview of how PASW Statistics can be used for survey research. The three research questions formulated in the sample survey are as follows:1. What kind of computer do people prefer to own?2. What color do people prefer for their computer?3. Is computer color preference different between genders?Downloading the Data FilesThis handout includes sample data files that can be used for hands-on practice. The data files are stored in a self-extracting archive. The archive must be downloaded and executed in order to extract the data files. The data files used with this handout are available for download at http://www.calstatela.edu/its/training/datafiles/pasw17p1.exe. Instructions on how to download and extract the data files are available at http://www.calstatela.edu/its/docs/download.php.Starting PASW StatisticsThe following steps are for starting PASW Statistics 17 using the computers in the Open Access Labs (OALs). The steps for starting the program at home or on other computers may be slightly different.To start PASW Statistics 17:1. Click the Start button, point to All Programs, point to Course Work, point to SPSS Inc, point to PASW Statistics 17, and select PASW Statistics 17. The PASW Statistics 17 dialog box opens (see Figure 1).2. Click the Cancel button to create a new data file.
Figure 1 - PASW Statistics 17 Dialog BoxThe PASW Statistics WindowThe Data Editor window opens with two view tabs: Data View and Variable View. The Data View is used for data input, and the Variable View is used for adding variables and defining variable properties (e.g., modifying attributes of variables). As displayed in Figure 2, the Data Editor window includes several components. The Title bar displays the name of the current file and the application. The Menu bar allows you to access various commands that are grouped according to function. The Toolbar provides shortcuts to commonly used menu commands.
Figure 2 - PASW Statistics Data Editor WindowData View
When PASW Statistics is launched, the Data Editor window opens in Data View, which looks similar to a Microsoft Excel spreadsheet (which is just an array of rows and columns). The difference is that the rows and columns in Data View are referred to as cases and variables, respectively (see Table 1). Table 1 - Elements in Data ViewElementDescription
VariableEach column represents a variable. Any survey questionnaire item or test item can be a variable. Commonly defined variable types are numeric or string. When defining variables as numeric, users need to specify decimal places. Variable names can be up to 256 characters long and must start with a letter. Make variable names meaningful and easily recognizable.
Each row represents a case. The participants in the study can be cases. For example, if 100 participants are involved in your study, then 100 cases (or rows) of information should be generated. Responses to the question items should be entered consistently from left to right for each participant.
A cell is an intersection between cases and variables. Each response to a survey question should be entered in a cell for each participant according to the defined variable data types.
Variable ViewVariable View is where variables are defined by assigning variable names and specifying the attributes, such as data type (String, Date, Numeric, etc.), value labels, and measurement scales (Nominal, Ordinal, or Scale). Users can think of Variable View as the backbone structure for the Data View; data cannot be entered nor viewed without first defining variables in Variable View (see Table 2).Table 2 - Elements in Variable View
PASW Statistics will initially give a default variable name (var00001) that users can change. It is recommended to assign a brief and meaningful name to variables (e.g., Name, Gender, and GPA).
The variable type determines how the cases are entered. Generally, text-based characters are of String type and number-based characters are of Numeric type. For example, if a user has a variable called Name, then its variable type should be String. Similarly, a variable named GPA should be a Numeric type with (normally two) decimal places.
Value labels allow users to describe what the variable name stands for. For example, if a variable has been defined as Fav, most likely others may not know what it stands for. To avoid misinterpretation, value labels can be utilized to clearly define variable names.
Creating a Data File
Creating a new PASW Statistics data file consists of two stages: (1) defining variables and (2) entering the data. Defining the variables involves multiple processes and requires careful planning. Once the variables have been defined, the data can then be added.
First, variable names based on your research questionnaire need to be assigned. If variable names are not assigned, PASW Statistics will assign default names that may not be recognizable. Second, the Type attribute should be specified for each variable. If necessary, assign labels to values to help all users of the file understand the data better.To define variables (example):1. Click the Variable View tab at the lower left corner of the Data Editor window (see Figure 3).
2. Type [Name] in the first cell under the Name column and press the [Enter] key.3. Under the Type column, click the ellipses button . The Variable Type dialog box opens (see Figure 4).
4. Select the String option.
5. Click the OK button.
Figure 3 - Variable View Tab
Figure 4 - Variable Type Dialog Box
6. Type [Gender] in row two under the Name column.7. Activate the cell in row two under the Decimals column and change the entry to 0 using the spin box.8. Type [What is your gender?] in row two under the Label column. 9. Click the ellipses button in row two under the Values column. The Value Labels dialog box opens (see Figure 5).10. Type  in the Value: box.
11. Type [female] in the Label: box.12. Click the Add button.13. Repeat steps 10-12 using a value of  and a label of [male].
Figure 5 - Value Labels Dialog Box (Gender)14. Click the OK button.
15. Type [GPA] in row three under the Name column and press the [Enter] key.16. Type [Age] in row four under the Name column.17. Click row four under the Decimals column and change the entry to 0 using the spin box.18. Type [What is your age?] in row four under the Label column.19. In row four under the Values column, click the ellipses button. The Value Labels dialog box opens (see Figure 6).
20. Type  in the Value: box.
21. Type [19 or you