Introduction:

This analysis uses data from historical election results and 2024 presidential primary averages to predict the 2024 presidential election winner. This focuses on the swing states and their impact on the elections. If the swing states have a large impact on who wins the elections, then based off of the primary averages, I predict that Donald Trump will win the election. My findings show that the relationship between the majority swing state vote and the actual presidential election winner is 1, representing that the majority swing state vote will be the determinant of who wins the presidential election.

Data Description:

Chart 1

  • Percentage of Votes: The percentage of votes that were cast for either Joe Biden or Donald Trump in the 2020 election.
  • Swing States: each state that is considered to swing in the election.
  • Candidates: A character field that shows both candidates in the running for president.

Chart 2

  • Poll Percentage: This is the percentage of polling votes that were for Trump or Harris.
  • Date(Weekly): The date was created into weekly format to show the changes in polling trends for each candidate and for each swing state.

Chart 3

  • Alignment: Data that was created to determine whether the swing state majority vote was aligned with the actual winner of each year
  • Election Year: The years of the past three elections and the predicted 2024 election based off of current polling trend averages for each swing state
## 
## Call:
## lm(formula = swing_state_winner ~ actual_winner, data = elections_data3)
## 
## Residuals:
##          1          2          3          4          5          6          7 
##  6.358e-17 -9.005e-17  6.616e-18  6.616e-18 -3.081e-32  6.616e-18  6.616e-18 
## 
## Coefficients:
##                Estimate Std. Error   t value Pr(>|t|)    
## (Intercept)   1.679e-16  4.965e-17 3.381e+00   0.0197 *  
## actual_winner 1.000e+00  5.363e-17 1.865e+16   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.965e-17 on 5 degrees of freedom
## Multiple R-squared:      1,  Adjusted R-squared:      1 
## F-statistic: 3.477e+32 on 1 and 5 DF,  p-value: < 2.2e-16
## [1] "R-squared: 1"
## 
##  Pearson's product-moment correlation
## 
## data:  elections_data3$swing_state_winner and elections_data3$actual_winner
## t = 106108431, df = 5, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  1 1
## sample estimates:
## cor 
##   1

Method:

The regression model predicted that the swing states majority winner have a perfect relationship with the presidential winner. There was a very small standard error, and the r squared showed that their is no variance between the actual winner of the elections and the majority voted swing state winner. The correlation test proves a strong correlation, and the p-value is extremely small indicating the the correlation is statistically significant.

Limitations:

This analysis did not account for any outside factors that may affect the swing state voting data or the swing state votes such as economic factors, political changes within the swing states. Further research within swing state changes could improve the accuracy of the models.

References:

Sources Include: