COVID-19 pandemic

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Scenario 1

In the recent COVID-19 pandemic, a local precinct observed that of the 75 people who voted, 25 identified as republican, 30 were democrat, and 20 were “other”. Is this similar to pre-pandemic voting based on political party affiliations? At that same precinct, pre-pandemic voting based on political party affiliation was: 35% republican, 44% democrats, and 21% “other”. Enter in the 75 data points and expected values into SPSS to conduct the appropriate statistical test.

1. Name the the variable of interest in the scenario. How many levels does it have, and what are they?

ANSWER

2. Calculate the expected frequencies for each of the levels of your variable. Clearly label each group and show all work involving your calculations.

 

Sample Solution

The variable of interest in the scenario is political party affiliation. It has three levels:

  • Republican
  • Democrat
  • Other

2. Calculate the expected frequencies for each of the levels of your variable. Clearly label each group and show all work involving your calculations.

To calculate the expected frequencies, we use the following formula:

Expected frequency = (Row total * Column total) / Total number of observations

Row total: The total number of observations in each row. Column total: The total number of observations in each column. Total number of observations: The total number of observations in the table.

Pre-pandemic voting based on political party affiliation:

| Political party affiliation | Observed frequency | Expected frequency |
|---|---|---|
| Republican | 25 | 26.25 |
| Democrat | 30 | 33 |
| Other | 20 | 15.75 |
| Total | 75 | 75 |

Calculations:

Expected frequency for Republicans: (75 * 35%) / 75 = 26.25
Expected frequency for Democrats: (75 * 44%) / 75 = 33
Expected frequency for Others: (75 * 21%) / 75 = 15.75

Therefore, the expected frequencies for each of the levels of the variable are:

  • Republican: 26.25
  • Democrat: 33
  • Other: 15.75

Conclusion

Once we have calculated the expected frequencies, we can use them to conduct a chi-square test of independence to determine if there is a significant difference between the pre-pandemic and post-pandemic voting patterns.

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