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2.2 total points one of the Interesting development of the Cold and the politication of the vaccine to explore the development we look at the

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2.2 total points one of the Interesting development of the Cold and the politication of the vaccine to explore the development we look at the following out based on data for all 50 state. The explanatory variable is the percent of the cast for Democratic presidente Biden in the 2016 election. The responsible is the percent of the state's adult population who is fully vaccinated as of November 17. As an ample, the data point representing Ohlois (45.24 525) Use the output to answer the following questions for the entire problem you can assume that resonations are met coefficients: Estimate std. Erort value pret Cintercept) 24.61108 2.72840 9.02 6.622-12 *** percent vote 0.67964 0.05593 12.15 2.96-15 *** Signif. codes: O **** 0.001 0.01 0.05 0.11 Residual standard error: 4.055 on 45 degrees of freedom Multiple R-squared: 0.7547 Adjusted r-squared: 0.7495 statistic: 147.7 on 1 and 48 DF. D-value: 2.955-16 d. 1 pt) What percent of the variation in vaccination rates can be explained by the linear relationship between percent of the vote for Biden and vaccination rates? (4 pts) Calculate a 95% confidence interval for the true mean vaccination rate for a state (like Ohio) that cast 45.24% of its votes for Biden. You can use the facts that 47.69 and sex = 5256. You do not have to interpret the interval In order to get a model with better predictive power, we can add other variables. The output below is from a multiple linear regression that adds two additional explanatory variables to the previous model: the percent of a state's population that self-identifies as white, and the median age of the state's population, both estimated from the Census Bureau. Use this output to answer the following Coefficients: Estimate Std. Error t value Pr(it!) (Intercept) 4.50851 7.87838 0.572 0.570 percent_vote 0.76989 0.05521 13.946

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