Research Study: Exit Polls versus Election Results

RDD selections except for Oregon, which used both RDD and some followup calling. Absentee or early voters were asked the same questions as voters at the polling place on Election Day. Results from the phone poll were combined with results from voters interviewed at the polling places. The combination reflects approximately the correct proportion of absenteeearly voters and Election Day voters. The first step in addressing the discrepancies between the exit poll results and actual election tabulation numbers would be to examine the results for all states, not just those thought to be crucial in determining the outcome of the election. These data are not readily available. Next we would have to make certain that voter fraud was not the cause for the discrepancies. That is the job of the state voter commissions. What can go wrong with exit polls? A number of possibilities exist, including the following: 1. Nonresponse: How are the results adjusted for sampled voters refusing to complete the survey? How are the RDD results adjusted for those screening their calls and refusing to participate? 2. Wording of the questions on the survey: How were the questions asked? Were they worded in an unbiased neutral way without leading questions?

3.

Timing of the exit poll: Were the polls conducted throughout the day at each polling station or just during one time frame? 4. Interviewer bias: Were the interviewers unbiased in the way they approached sampled voters? 5. Influence of election officials: Did the election officials at location evenly enforce election laws at the polling booths? Did the officials have an impact on the exit pollsters? 6. Voter validity: Did those voters who agreed to be polled, give accurate answers to the questions asked? 7. Agreement with similar pre-election Surveys: Finally, when the exit polls were obtained, did they agree with the most recent pre-election surveys? If not, why not? Raising these issues is not meant to say that exit polls cannot be of use in predict- ing actual election results, but they should be used with discretion and with safe- guards to mitigate the issues we have addressed as well as other potential problems. But, in the end, it is absolutely essential that no exit poll results be made public until the polls across the country are closed. Otherwise, there is a significant, seri- ous chance that potential voters may be influenced by the results, thus affecting their vote or, worse, causing them to decide not to vote based on the conclusions derived from the exit polls.

2.7 Summary

The first step in Learning from Data involves defining the problem. This was dis- cussed in Chapter 1. Next, we discussed intelligent data gathering, which involves specifying the objectives of the data-gathering exercise, identifying the variables of interest, and choosing an appropriate design for the survey or experimental study. In this chapter, we discussed various survey designs and experimental designs for scientific studies. Armed with a basic understanding of some design considerations for conducting surveys or scientific studies, you can address how to collect data on the variables of interest in order to address the stated objectives of the data- gathering exercise. We also drew a distinction between observational and experimental studies in terms of the inferences conclusions that can be drawn from the sample data. Differences found between treatment groups from an observational study are said to be associated with the use of the treatments; on the other hand, differences found between treatments in a scientific study are said to be due to the treatments. In the next chapter, we will examine the methods for summarizing the data we collect.

2.8 Exercises

2.2 Observational Studies 2.1 In the following descriptions of a study, confounding is present. Describe the explanatory and confounding variable in the study and how the confounding may invalidate the conclusions of the study. Furthermore, suggest how you would change the study to eliminate the effect of the confounding variable.

a. A prospective study is conducted to study the relationship between incidence of

lung cancer and level of alcohol drinking. The drinking status of 5,000 subjects is determined and the health of the subjects is then followed for 10 years. The results are given below. Lung Cancer Drinking Status Yes No Total Heavy Drinker 50 2150 2200 Light Drinker 30 2770 2800 Total 80 4920 5000

b. A study was conducted to examine the possible relationship between coronary disease

and obesity. The study found that the proportion of obese persons having developed coronary disease was much higher than the proportion of nonobese persons. A medical researcher states that the population of obese persons generally have higher incidences of hypertension and diabetes than the population of nonobese persons. 2.2 In the following descriptions of a study, confounding is present. Describe the explanatory and confounding variable in the study and how the confounding may invalidate the conclusions of the study. Furthermore, suggest how you would change the study to eliminate the effect of the confounding variable.

a. A hospital introduces a new screening procedure to identify patients suffering from

a stroke so that a new blood clot medication can be given to the patient during the crucial period of 12 hours after stroke begins. The procedure appears to be very suc- cessful because in the first year of its implementation there is a higher rate of total recovery by the patients in comparison to the rate in the previous year for patients admitted to the hospital.

b. A high school mathematics teacher is convinced that a new software program will

improve math scores for students taking the SAT. As a method of evaluating her theory, she offers the students an opportunity to use the software on the school’s computers during a 1-hour period after school. The teacher concludes the software