Saint Louis University, School of Public Health Kate Beatty, MPH and Caroline Geremakis, MPH

What you need to participate in this introduction:

Open the Intro to SPSS Data set Open the Intro to SPSS Codebook Follow along with each Tegrity Module Each module varies in time

Use the Intro to SPSS power point slides as a guide and a reference tool

2

Course Outline - Tegrity

Follow the course outline through Tegrity modules The Tegrity sessions will be available in the SPSS folder You can also access Tegrity on the right hand side you will see a link to Tegrity There are 6 SPSS Orientation modules that are to be viewed This slide deck is a supplement to the module – with step by step instructions and screenshots of SPSS actions to be used as a reference and a guide It is important to view the Tergity sessions in order to familiarize yourself with the SPSS interface

3

Course Outline / Modules

Module 1: Introduction to the SPSS environment.

8 minutes

Module 2: Who is in my dataset?

12 minutes

Module 3: What variables are in my dataset? “The first look”. 38 minutes

Module 4: Data management & Syntax: When and how? (2 parts)

Part 1: 28 minutes Part 2: 18 minutes

Module 5: Organizing and Displaying your Results.

26 minutes

4

Be sure to maximize the screen in Tegrity:

5

Introduction to the SPSS environment.

6

What is SPSS?

SPSS is a computer program used for survey authoring and development, data mining, text analytics, statistical analysis, and collaboration and deployment. Statistics included in the grad pack software: Descriptive statistics:

Cross tabulation, Frequencies, Descriptives, Explore, Descriptive Ratio Statistics

Bivariate statistics:

Means, t-test, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests

Prediction for numerical outcomes:

Linear regression, logistic regression

7

Pull-down menus versus icons

Most SPSS commands you will use regularly can be found in the pull down menus (or corresponding icons) along the top of the screen.

These work similar to any other Windows-based program (like Microsoft Word or Excel).

8

Commonly used SPSS commands

Folder File Edit View Data Transform Analyze Graphs Window Help 9

Commands Create a new file, open an existing file, save a file, print, exit SPSS Copy, paste Switch between variable and data view (see data view versus variable view) Commands to manipulate the contents of the dataset (insert variable, insert cases, sort cases) Commands to manipulate the contents of variables in the dataset (compute, recode) Commands to perform statistical analysis of your dataset (descriptive statistics, compare means) Commands to create graphs of your data (bar, pie, histogram, boxplot) Switch between SPSS windows if multiple windows open (e.g., data, syntax, and output) Where to find the SPSS online help utility

Types of SPSS files

Data files:

Actual dataset information including variable names, variable labels, and most importantly the actual data. These files have the ending “.sav”.

Syntax files:

Can be used to save the commands run in SPSS to manipulate variables or examine relationships between them. Can also be annotated to allow for easy understanding and recreation of analysis steps. These files have the ending “.sps”.

Output files:

Contain the results of your analysis. These files have the ending “.spv”. 10

SPSS data format

Row:

Each row represents a case in your dataset. The number in the grey box down the left side of the datasheet corresponds to the case number for a particular entry in your dataset. Typically, a unique identification number (e.g., caseid or id) will be given to each case in a dataset to maintain the relationship between variables when they are sorted.

Column:

Each column represents a variable in your dataset. For example, the second column provides the AGE for each individual (or row) in the dataset. 11...