Thesis Statement

I am comparing polling trends from August to October for the 2020 election and the current election, focusing on how voter preferences have shifted over these critical months. This analysis aims to evaluate the effectiveness of pollsters by examining their grades and the accuracy of their predictions. Based on historical data and current polling trends I believe that the pollsters with the highest grades will have also have the highest transparency scores. I believe this due to the fact that the people like to understand and know what is going on and that is how the pollsters receive high grades. I believe based on the data I collect and the trends that Donald Trump will win.

General Data

The current pollster graph is showing what the average support for either party for August to October and where the pollsters are leaning right now. Currently, it is very close for most pollsters and it is not showing a clear winner.

This historical pollster graph from 2020 is also showing the average support for each party for the months of August to October. While the current graph is showing a very close and tight race through these months, the 2020 election is showing something very different as the democratic party is winning by a wide margin for almost every pollster.

Regression Model

## 
## Call:
## lm(formula = transparency_score ~ numeric_grade, data = currentPollster_analysis)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.2138 -1.1910  0.5647  1.2635  3.2066 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     1.1060     0.6491   1.704   0.0922 .  
## numeric_grade   2.4431     0.2689   9.086 5.37e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.895 on 81 degrees of freedom
## Multiple R-squared:  0.5048, Adjusted R-squared:  0.4986 
## F-statistic: 82.55 on 1 and 81 DF,  p-value: 5.372e-14

Looking at the regression model and the statistics returned from the summary, it indicates that there is a strong significant relationship between transparency score and numeric grade. Meaning that one has a direct impact on the others success.

These graphs are showing current pollster data for both democrats and republicans. It is there numerical grade on the x axis and the support percentage on the Y. I did this to accurately show what each pollster was saying in regards to who they believe was winning. I did a gradient scale to show which ones had the highest transparency score.

This is the same chart as the last one except it is showing the 2020 election with the complete results. This shows the clear correlation between the grade rating and the transparency score as it is better transparency scores the further right you go except for a few random outliers.

Limitations

I could’ve overall grabbed more data and compared it to another election year to truly see the trend.

Discussions

Overall, I would say my prediction was correct as the pollsters with the highest transparency score tended to be correct and the percentage of support was higher for Trump than Kamala. Based off the data collected from 2020 and 2024 the trends indicated a massive shift in the voter population towards Trump which is why I believed he would win. I am happy with my results overall as the grade does correspond with the transparency score and the ones with the highest score do show a higher percentage for Trump.

References