1. Introduction to SPSS
SOCI 301
Lab session

2. Statistics
Statistiscs measure patterns of individual variables and relationships between them.
Research questions, theory, testable hypotheses
data, and analytic strategies are major components of doing research.

3. SPSS IBM SPSS 20 How to access data sets? (GSS, WVS)
How to make a data set? (naming, labeling, defining variables)

4. Layout of SPSS Mainly 4 different windows: One that presents the data
One that presents information about the data structures
Another that provides the output of analyses
And another called “syntax”, a command language which allows to save and automate many common tasks
Data view window & Variable View Window
Once you have data the Data View will display the values for each observation. With the tab at the bottom you ca move to variable view. Variable View will display information about each variable in the data set.

5. Layout
MENU BAR
commonly requested procedures such as opening files, performing statistical operations and constructing graphs
File, Edit, View, Data, Transform, Analyze, Graphs, Utilities, Add-ons, Window, Help
TOOL BAR (beneath the menu bar)

6. TYPES OF VARIABLES Constructing a data set requires entering data
In data view, cases are positioned in rows, and variables are positioned in columns.
Cases are units being studied, such as people, organizations or countries.
Variables are characteristics or values being measured for these cases, such as age and gender for people.

7. Levels of Measurement
In the SPSS, you can specify the level of measurement as scale (interval or ratio), ordinal or nominal
NOMINAL: Values of a variale do not have mathematical interpretation (different categories)
e.g. Religion, sex, political party affiliation, nationality
ORDINAL: Rank order
e.g. Level of education, response categories as low middle high

8. Levels of Measurement
INTERVAL: intervals, numbers represent fixed measurement units
e.g. Temperature (Fahrenheit), indexes treated as interval measures
RATIO: absolute zero point
e.g. Years of education, age, income
Higher levels can be transformed into lower levels of measurement

9. String variables: written text (dates, currencies etc.)
Categorical variables: Ordinal, nominal variables
Scale variables: continuous variables, also called numerical variables

10. Defining and saving a new data set
Manually save or open an already constructed data
Exercise: Generate a data set about your family members. Create 4 variables indicating the person’s name, their sex, birth date and level of education.
Each family member is one case in the data set.
Open Variable View window and define variables. In the column labeled name, enter PERSON, SEX, BIRTHDT, EDYRS