PSC 47410: Data Analysis Workshop  What’s the purpose of this exercise?  The workshop’s research questions:  Who supports war in America?  How consistent is support for conflict across different types of war?  Should we be considering other, related questions? If this project were to be expanded, what could else we look at… how different groups change their support over time, support for other types of conflict, varying patterns in other societies  Will you want to do your research paper on work that builds on this workshop?  You research paper assignment will ask you to either do a more complex paper on public opinion and war or to test the power of various causes of war to explain the outbreak of a conflict not considered in our class readings  How would a research paper using Pew data be different than this assignment with respect to its literature review and what methods you would need to use? PSC 4000-level Stats Workshop

Where Do You Get Survey Data?  Why are we looking at survey data from the Pew Foundation? How do we download a dataset from Pew?  Why do we have to read the methodology sheet first (it’s boring, but critical)?  What do we do with the questionnaire?  How does scientific method work?: In theory and in the real world  Can we operationalize our dependent variable(s)? Are there some questions that we can use to identify who supports war?  Do we have the independent variable(s) we need? Are there any questions that identify characteristics (e.g., gender) that we expect to be correlated with whether a person supports war?  What specific hypotheses can we explore with our survey? What specific relationships do we expect to find between our independent and dependent variables? PSC 4000-level Stats Workshop

What Do You Need to Turn In?  Your assignment has two components:  The first asks you to complete several data assignments  The second is an 1000-word analytical essay  The assignments related to SPSS ask you to:  Recode and label both new variables and their response categories  You will be asked to create dummy (1-0 value) variables. For example, you can use a question asking about religion to create a new variable called “Catholic,” where all Catholic respondents are coded 1 and all other respondents are coded zero  Calculate descriptive statistics  Mean (the average value of the response categories)  Median (the middle value for all of your observations)  Mode (the most common response if there’s no natural order to variable’s response categories)  Generate a bar graph  Do a little bivariate data analysis using SPSS’s cross-tab routine PSC 4000-level Stats Workshop

Getting Started with SPSS  Open your dataset with SPSS  Open a new syntax file  What are the four SPSS screens you will be working with?  Data editor: Data view  Data editor: Variable view  The syntax file (Why is it WAY better than just pointing and clicking all of the time? Why is this the ONLY file that you will want to save in most cases? )  The output file PSC 4000-level Stats Workshop

Recoding Data in SPSS  Why do we need to recode?  Need to drop refusals (but we want to be careful to think about what “don’t know means… e.g. if someone doesn’t know that she’s a born-again Christian, she’s not one)  Variables may not measure constructs correctly, so we need to create different categories that make sense  We’ll want to create dummy (0-1) variables  How do we recode?  Use the point and click menus at the top of the data editor  Use the “Recode Into Different Variable” option  Select variable you want to recode  Tell SPSS how you want to recode the variable  Name and label the new variable  Define values  Do not hit OK; instead, you want to paste command into syntax  Highlight the appropriate syntax and click the run (arrow) button PSC 4000-level Stats Workshop

Recoding Data: Step by Step Illustration PSC 4000-level Stats Workshop

Recoding Data: Step by Step Illustration PSC 4000-level Stats Workshop

Recoding Data: Step by Step Illustration PSC 4000-level Stats Workshop

Recoding Data: Step by Step Illustration PSC 4000-level Stats Workshop

Recoding Data: Step by Step Illustration PSC 4000-level Stats Workshop

Recoding Data: Step by Step Illustration PSC 4000-level Stats Workshop

Labeling Values in SPSS  Why do we need to label the values used for different response categories (e.g., 1=male, 0=woman)?  You may not remember how you recoded values  Labels will transfer into tables and graphs  How do we label values for our variable categories?  Use “Define Variable Properties” option  Select variable(s) with values you want to label  Tell SPSS how you want to label the values  Paste command into syntax  Highlight syntax and click run  Once you’ve got the syntax down, you may want to work much more quickly with other variables by copying and pasting that syntax and making appropriate substitutions PSC 4000-level Stats Workshop

Creating Value Labels for Response Categories: Step by Step Illustration PSC 4000-level Stats Workshop

Creating Value Labels for Response Categories: Step by Step Illustration PSC 4000-level Stats Workshop

Creating Value Labels for Response Categories: Step by Step Illustration PSC 4000-level Stats Workshop

Creating Value Labels for Response Categories: Step by Step Illustration PSC 4000-level Stats Workshop

Creating Value Labels for Response Categories: Step by Step Illustration PSC 4000-level Stats Workshop

Descriptive Statistics in SPSS  What descriptive statistics may interest us?  Frequencies  Mean (the average), Medians (the middle observation), and Mode (rarely used)  How do we compute descriptive statistics?  Use “Descriptive Statistics” option  Select “Frequencies”  Select variable(s) that you want to analyze  Select “Statistics”  Select the statistics you want to view  Option 1 (if you will need the results later): click the paste command to create syntax; highlight the syntax and click run  Option 2 (if you are using the results right now): click OK and the syntax won’t be pasted into your syntax file, but the output will be created PSC 4000-level Stats Workshop

Descriptive Statistics: Step by Step Illustration PSC 4000-level Stats Workshop

Descriptive Statistics PSC 4000-level Stats Workshop

Descriptive Statistics: Step by Step Illustration PSC 4000-level Stats Workshop

Descriptive Statistics: Step by Step Illustration PSC 4000-level Stats Workshop

Descriptive Statistics: Step by Step Illustration PSC 4000-level Stats Workshop

Descriptive Statistics: Step by Step Illustration PSC 4000-level Stats Workshop

Descriptive Statistics: Step by Step Illustration PSC 4000-level Stats Workshop

Graphing in SPSS  What kinds of graphs might we create?  Bar  Line  Histogram  How do we compute descriptive statistics?  Use “Descriptive Statistics” option  Select “Frequencies”  Select variable(s) that you want to analyze  Select “Charts”  Select the charts you want to view; check the “percentage” option in most cases so that your charts will be more readable  Paste command into syntax  Highlight syntax and click run PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Creating Graphs PSC 4000-level Stats Workshop

Bivariate Analysis in SPSS  What types of bivariate analysis might we conduct?  Correlation  Crosstabs (this is your best option for tables that will make sense to a general audience)  Significance tests  How do we conduct bivariate analysis?  Use options in the “Analyze” menu  Select variable(s) that you want analyze  Tell SPSS how you want to analyze the values  Paste command into syntax  Highlight syntax and click run PSC 4000-level Stats Workshop

Calculating Correlation PSC 4000-level Stats Workshop

Calculating Correlation PSC 4000-level Stats Workshop

Calculating Correlation PSC 4000-level Stats Workshop

Calculating Correlation PSC 4000-level Stats Workshop

Calculating Correlation PSC 4000-level Stats Workshop

Guidelines for Correlation  Less than.1: Very weak relationship .1 to.2: Weak relationship .2 to.3: Moderate relationship  Above.4: Strong relationship PSC 4000-level Stats Workshop

Review: Variable Types  Categorical  Represent categories or names (e.g. gender, religion)  Ordinal  Rank ordered indicators (e.g. agree, strongly agree)  Interval  Ordered values where all unit increases are roughly equivalent (e.g. age) PSC 4000-level Stats Workshop

Calculating Significance  Crosstabs will allow you to see relationships between two variables in more detail  Put dependent variable in the rows  Put independent variable in the columns  Can also test association:  Categorical/categorical: Lambda, Cramer’s V  Categorical/ordinal: Cramer’s V  Ordinal/ordinal: Gamma, Tau-B (same number of categories)  Categorical/Interval: Eta  Ordinal/Interval: Spearman’s Rho  Interval/Interval: Pearson’s R PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop

Crosstabs and Tests of Significance PSC 4000-level Stats Workshop