Gambling Behavior in the United States: A Data-Driven Learning Guide

Application

Gambling Behavior

To measure whether respondents had ever gambled and whether they had gambled in the past year, we created two new variables, EVERGAMB and YEARGAMB. EVERGAMB was coded as "1" if respondents reported having ever done at least one of 11 different types of gambling (see variables B1_, B4_, B7_, B10_, B13_, B16_, B19_, B22_, B25_, B28_, and B30_), and "0" if they had not done any kind of gambling. YEARGAMB was coded in the same way by using variables measuring gambling activity in the past year (see variables B3_, B6_, B9_, B12_, B15_, B18_, B21_, B24_, B27_, B29_, and B31_).

To begin the exercise, determine the percentage of people who have ever gambled. Look at the frequency distribution of EVERGAMB . What percentage of sample respondents has ever gambled? Is it higher or lower than you expected?

Next, consider gambling behavior in the past year by looking at the frequency distribution of YEARGAMB Compare the percentage of people who say they have not gambled in the past year to the percentage who have never gambled. Is there a difference?

Now consider the different types of gambling people may do. Limiting your sample to respondents who have ever gambled, what percentage have ever gambled in a non-tribal casino? How about in an Indian or tribal casino? An on-track or off-track betting facility? A lottery? How many have gambled on bingo or private games (dice, poker, pool, etc)? What percentage have ever gambled in a store/bar/restaurant (video poker, pull-tabs, etc), or in an unlicensed facility? Which type of gambling appears to be most popular?

Characteristics of Gamblers

Now that you have an idea of gambling behavior, think about the characteristics of gamblers themselves. First consider age. For ease of analysis, we recoded age (A2_R) into three categories: ages 18-29, 30-49, and ages 50 and older. We called the new variable, "AGE3."

Run a crosstab of EVERGAMB and AGE3. In which age group did the largest percentage of respondents report ever gambling?

Now look at gambling behavior in the past year alone, limiting the sample to only those who have ever gambled. What differences do you see in the table of YEARGAMB and AGE3 compared with the previous analysis? Is the age pattern different for gambling in the past year than for lifetime gambling?

Does gambling behavior differ by gender? Run a crosstab of EVERGAMB and A1_ . Are men or women more likely to have ever gambled?

Now consider the relationship between gambling and income. Run a crosstab of EVERGAMB and INCOME . How does gambling behavior differ by income group?

Try the analysis again with YEARGAMB and INCOME . How might you explain the difference between the pattern shown in this analysis and the crosstab of lifetime gambling and income?

Next think about the relationship between gambling behavior and race/ethnicity. Run a crosstab of EVERGAMB and RACETH . Looking at the bar chart, what racial/ethnic group has the highest percentage of lifetime gambling? What racial/ethnic group has the lowest percentage?

Because racial/ethnic group is often closely related to income level, and you have seen in previous analyses that income level is related to gambling behavior, income group might be a confounding variable in the relationship between racial/ethnic group and gambling behavior. Rerun the crosstab of EVERGAMB and RACETH, limiting the sample to only those respondents in the three highest income groups (excluding those in the $24,000 and under group). Does the relationship between race/ethnicity and gambling behavior change when the lowest income group is excluded from the sample? Is income a confounding variable in the relationship between race/ethnicity and gambling behavior?

Problem Gambling

The variable "EVERPROB" was included in the study to count the number of gambling problems respondents report ever having. Gambling problems include items such as stealing money to gamble, being unable to stop thinking about gambling, lying about gambling losses, etc (for a full list see variables D1_ through D19_).

We recoded EVERPROB into two categories: ever had one or more gambling problem, or never had a gambling problem. We called the new variable "LIFEPROB".

Look at the frequency distribution of LIFEPROB . What percentage of gamblers have ever had a gambling problem?

Does the percentage reporting a gambling problem vary by age? Run a crosstab of LIFEPROB and AGE3 . What do you see? Are the results as you expected?

Finally, look at the crosstab of LIFEPROB and INCOME . What does the bar chart show? Does problem gambling vary by income?

Note: The online data analysis system (DAS) used on this site uses a system called Survey Documentation and Analysis (SDA), developed and maintained by the Computer-assisted Survey Methods Program (CSM) at the University of California, Berkeley. Documentation for DAS/SDA can be found on their Web site.

Goal & Concept - Dataset - Application - Interpretation & Summary - Bibliography