Last semester, I was interested in the result of 2020 American presidential election, so I built a logistic regression to see how predictor variables, such as race, sex, work class, education level, state, age, affect the probability of a person voting for Trump in the 2020 American Presidential Election.
The model is:
Next, we employed the model to the census data to predict the proportion of voters in each group. In addition, we grabbed the raw survey data from the website called Vote For Study Group, and we also grabbed the census data from the website called IPUMS USA. There are six variables in the model: race, sex, age, education level, work class, and state. Afterward, with these values, we weighed the proportion of voting for Trump with the corresponding population of each variable group. Then, we summed up these values. Finally, we divided the sum by the total population size. The result of 44.424% is the predicted proportion voting.
In conclusion, the estimated proportion of voting for Donald Trump is approximately 44.424%, and the estimated proportion of voting for Joe Biden is approximately 55.576%. Based on the analysis, we find that the proportion of Trump-voting is lower than the proportion voting for Biden. Therefore, Trump is less likely to win.
Now, we knew that Biden won the election. My prediction has correctly reveal the result.
Wow, your prediction is great, it is a perfect prediction of Biden will win.
ReplyDeleteYes, the prediction is amazing!
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