Exercise 8. Attitude on Government Reaction to COVID-19 and the Presidential Vote

Step A. Create Table 8A

Another example of a conditional relationship involves the relationship between attitudes about the federal government’s reaction to the COVID-19 pandemic and the presidential vote. Biden and Trump disagreed on this issue. Biden argued that the government’s response to the pandemic under the Trump administration was inadequate and too slow. Trump argued that his quick and decisive action against the pandemic saved American lives. Therefore, we might hypothesize that this was an issue that would have influenced how people voted, with the expectation that those who thought the federal government’s response to the COVID-19 pandemic was too slow would vote for Biden. To see if this is so, create Table 8A, a two-variable table that examines the relationship between feelings on whether the government acted too quickly, too slowly, or just about right (H05) and presidential vote (A02). To simplify the table, recode H05 use the recoded version of A02 that excludes the minor party voters, as you have in previous exercises.

H05 has five response categories, ranging from the federal government acted much too quick to much too slow. To simplify this variable, recode it so that “much too quick” and “somewhat too quick” are a single category of “too quick,” and do the same for “somewhat too slow” and “much too slow.” The category of “about right” should be kept separate. Therefore, the recoded H05 should be 1=too quick; 2=about right; 3=too slow.

Step B. Interpret Table 8A

If you ran Table 8A as suggested, you should have a table with three columns and two rows. Opinion on whether the federal government reacted too quickly or too slowly (the independent variable) should be on the top of the table (the column variable), and the two-party presidential vote (the dependent variable) should be on the side of the table (the row variable). Percentages should be calculated by column (i.e., they should sum to 100% for each column). In reading your table, take care to interpret the percentages properly, remembering that they are column percentages, not row percentages.

You should attempt to answer these questions to see if you are able to read the table and interpret the data correctly:

  1. What percentage of voters who thought the government reacted too slowly to COVID-19 cast a ballot for Biden (or Trump)? What about voters who thought the response was too quick, or just about right?
  2. Overall, how strong is the relationship between these two variables? How does it compare to other relationships that you examined in previous exercises?

Step C. Create and interpret Table 8B

The initial hypothesis above was that voters who thought the government reaction to COVID-19 was too slow would be more likely to vote for Biden and those who thought the reaction was too quick or just about right would be more likely to vote for Trump. But, was this a politically-based calculation or an opinion based on the information provided by scientists and virologists? Indeed, as it turns out, there was a significant portion of the voting public that did not think science should be very important for making decisions about COVID-19. Please look at variable H08, which asks how important science should be for decisions about COVIDovid-19.

Create Frequency Table 8B (Note: to create a frequency table for a single variable, enter the variable name in the box for the row variable and leave the column variable blank; be sure to use the weighted data.)

H08 is a measure the respondent’s perception how important science should be for decisions about COVID-19. About half of the respondents (51%) said science should be extremely important, and another 26% said science should be very important. However, this leaves almost a quarter of the respondents (23%) who said science should be only moderately important, a little important, or not at all important.

Step C. Simplify the table

As you can see, not every voter saw the role of science in decisions about COVID-19 as very important, or extremely important. This might lead us to hypothesize that the relationship between views on the federal government’s reaction to COVID-19 and the vote will be much stronger for voters who did not think science was very/extremely important. To test that hypothesis, you should create Table 8C with views on the federal government’s reaction to COVID-19 as the independent variable, presidential vote as the dependent variable, and the importance of science as the control variable (H08). To simplify the tables, recode H08 so that they have just two categories, very important and not very important.

Variable H08 has five response categories. If we did not recode this variable, our tables would be very complicated, and there would be too few respondents in many of the columns. Looking at Table 8B, we can see that about a quarter of the respondents were in the first three categories of H08 (not at all important, a little important, and moderately important). If we want to dichotomize this variable into “very important” and “not very important” categories, it seems most logical to combine the first three categories into the “not very important” category, and the last two categories into the “very important” category.

Step D. Interpret Table 8C

If you generated the tables as we have suggested, you should have a table with two sub-tables. Your first sub-table should show the relationship between views on the federal government’s reaction to COVID-19 and the presidential vote while controlling for views on the importance of science in making decisions about COVID-19. As we can see, the inclusion of this control variable does change the strength of the relationship compared to the relationship in Table 8A.

Using the sub-tables, you should be able to answer these questions to see if you are able to understand the data and interpret the table:

  1. For respondents who thought that science was very important in making decisions about COVID-19, is there a relationship between the respondent’s view on the government’s reaction to COVID-19 and his or her vote? How strong is this relationship compared to the relationship in Table 8A?
  2. For respondents who thought that science was not very important in making decisions about COVID-19, is there a relationship between the respondent’s view on the government’s reaction to COVID-19 and his or her vote? How strong is this relationship compared to the relationship in Table 8A?

Overall, can you explain how the relationship between the federal government’s response to COVID-19 and presidential vote depends on what the voter thinks about the role of science in determining how to handle the pandemic?