Maximum difference maxdiff2 4c considering that the

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#maximum difference max(diff2) ``` **4c** Considering that the average discrepancy between reported voting and actual voting is almost 20%, the huge discrepancy demonstrates that many people did not vote despite their provided data. ####Q5 **5a** ```{r} data$diff2 <- data$ANES - data$turnout model3 <- lm(data$diff2 ~ data$year)
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plot(data$year,data$diff2, ylab = "Difference between ANES and VEP-based estimate of a turnout", xlab = "year", main = "Difference between ANES and VEP-based estimate of a turnout") ``` ####Q6 ```{r} model3 <- lm(data$diff2 ~ data$year) plot(data$year,data$diff2, type="b",pch=10, col="red", ylab = "Difference between ANES and VEP-based estimate of a turnout", xlab = "year", main = "Difference between ANES and VEP-based estimate of a turnout") ``` ####Q7 **7a** ```{r} model3 <- lm(data$diff2 ~ data$year) plot(data$year,data$diff2, pch=10, ylab = "Difference between ANES and VEP-based estimate of a turnout", xlab = "year", main = "Difference between ANES and VEP-based estimate of a turnout") abline(model3, col = "#00bfff") ``` **7b** The regression line demonstrates that the self-reporting bias over time has gone up. The first line tracks the pattern of self-reporting bias over time. **7c** There is a positive increase of self-reporting bias over time. ####Bonus The difference between VAP and VEP has less error because it doesn't rely on the human element of self-reporting; rather, it uses population data to determine a clear upward trend. ANES is endogenous because the factors contributing to a true or false report of voting pattern can also be affecting the actual voting pattern.
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