1. Tables One way to describe relationships is with tables. Tables depict relationships between variables. The simplest table depicts the relationship between one dependent variable and one independent variable. One dependent variable of interest to political scientists studying elections is vote choice: Some people vote for the Democratic candidate, other people vote for the Republican. Every election year the NES draws a representative sample of the American electorate to study voting behavior. All told about 1500 people are randomly sampled and interviewed. Let's treat whether a citizen voted for Republican or Democratic in a recent presidential election as our dependent variable.

2. Vote Choice by Gender Number of casesPercent of cases by IV VOTEMaleFemaleNMaleFemale% Democratic24022446453%61%56.7% Republican21214335547%39%43.3% Total452367819100%

3. Basic Rules for Constructing and Interpreting Crosstabulations 1. Determine the title: Write a clear description in which the Dependent Variable comes first, then the Independent Variable(s). EG, “Presidential Vote by Gender" Reader should be able to tell what is being compared without reading the accompanying text. Here we are looking at vote choice as a function of gender. 2. Next, Determine categories for the Dep and Ind Vars, here Vote Republican or Democratic. Vote choice is a (categorical) dichotomous variable. The Ind Var can also be broken down as a dichotomy -- Male or Female, producing a 2 by 2 table, with each "cell" -- a, b, c, or d -- showing the number of people in each category. 3. Next, Label the Columns and Rows. Here is a key question. Which should be the column variable, which the row? By convention the Independent variable (Gender) is the column variable. The DV makes up the rows – with title on left. 4. Next Important decision: Which way to calculate percentages.

4. Vote Choice by Income Low income Med income High income Vote Rep.41%49%66% Vote Dem. 59%51%34% Total100%

5. Vote Choice by Party ID VOTERepublican Independent Democrat Rep. Pres. 89%40%7% Dem. Pres. 11%60%93% Total %100%

6. Reading and Interpreting Tables Crosstabs with Controls

7. CONTROLLING for a THIRD VARIABLE Main effects: Partisanship, Income, & Gender (each of the factors influenced vote choice ) Concept called “control variables” will help us answer an important question: How do the different independent variables interact? Interactions: Gender and Party ID Gender and income Party ID and income

8. Vote by Party ID, Controlling for Gender MaleFemale Vote:RepIndDemRepIndDem Rep. 95%73%24%95%55%23% Dem.5%27%76%5%45%77% Total100%

9. Vote by Income, Controlling for Gender MaleFemale Vote:LowMedHighLowMedHigh Rep.47%61%67%38%51%65% Dem.53%38%33%62%49%35% Total100%

10. Vote by Income, Controlling for Party ID RepublicanIndependentDemocratic Vote:LowMedHighLowMedHighLowMedHigh Rep.94%93%96%56%65%71%17%25% Dem.6%7%4%44%35%29%83%75% Total N33761153463869913798 Total %100%

11. Effects of Controlling for a Third Variable: four possibilities when controlling for a 3rd Variable I. The independent effect is maintained II. The now you see it now you don’t effect III. Something from nothing effect IV. The stretch and shrink effect

12. The Independent Effect Maintained: Vote Choice by Religion ProtestantCatholic Republican58%25% Democrat42%75%

13. Vote by Religion, Controlling for Income Low IncomeHigh Income Prot.Cath.Prot.Cath. Rep.54%20%67%35% Dem.46%80%33%65%

14. Now you see it now you don’t effect Congressional Vote by Union Membership Non-Union Union Member Republican50%42% Democrat50%58%

15. Congressional Vote by Union Membership, Controlling for Income Below Median IncomeAbove Median Income Non-UnionUnionNon-UnionUnion Rep33%32%58%56% Dem67%68%42%44%

16. Attitude toward Urban Renewal by Party Identification RepublicanDemocrat Pro Urban Renewal 50%52% Anti Urban Renewal 50%48% Something from Nothing Effect

17. Attitude toward Urban Renewal by Party Identification, Controlling for Income Below Median IncomeAbove Median Income RepublicanDemocratRepublicanDemocrat Pro Urban Renewal 40%45%58%67% Anti Urban Renewal 60%55%42%33%

18. Support for Aggressive Foreign Policy by Gender MaleFemale Ease Relations 42%67% Get Tougher58%33% The Stretch and Shrink Effect

19. Support for Aggressive Foreign Policy by Gender, Controlling for Region SouthNorth MaleFemaleMaleFemale Ease30%67%58%68% Tough70%33%42%32%