3.) The World Bank collects information on the life expectancy of a person in each country ("Life expectancy at," 2013) and the fertility rate per woman in the country ("Fertility rate," 2013). The data for 24 randomly selected countries for the year 2011 are in table # 10.1.7. Create a scatter plot of the data and find a linear regression equation between fertility rate and life expectancy. Then use the regression equation to find the life expectancy for a country that has a fertility rate of 2.7 and for a country with fertility rate of 8.1. Which life expectancy that you calculated do you think is closer to the true life expectancy? Why? Table # 10.1.7: Data of Fertility Rates versus Life Expectancy Lif Fertility Rate e 1.7 5.8 2.2 2.1 1.8 2.0 2.6 2.8 1.4 2.6 1.5 6.9 2.4 1.5 2.5 1.4 2.9 2.1 4.7 6.8 5.2 4.2 1.5 3.9 Expectan су 77.2 55.4 69.9 76.4 75.0 78.2 73.0 70.8 82.6 68.9 81.0 54.2 67.1 73.3 74.2 80.7 72.1 78.3 62.9 54.4 55.9 66.0 76.0 72.3

Ariel was running analyses over and over in census data and came across a correlation between weight and debt (r=.78). Independent variable is weight and dependent variable is debt. b) Curious Ariel noted some statistics on these weight (M=160lb, SD=15lb) and debt (M=196k, SD=20k). If Ariel wanted to calculate a regression equation, what would her slope and intercept be?

A box office analyst seeks to predict opening weekend box office gross for movies. Toward this​ goal, the analyst plans to use online trailer views as a predictor. For each of the 66 ​movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross​ (in millions of​ dollars) are collected and stored in the accompanying table. A linear regression was performed on these​ data, and the result is the linear regression equation Yi=−0.840+1.4108Xi. Determine the coefficient of​ determination,r2​,and interpret its meaning. Determine the standard error of the estimate. How useful do you think this regression model is for predicting opening weekend box office​ gross? Can you think of other variables that might explain the variation in opening weekend box office​ gross?

A box office analyst seeks to predict opening weekend box office gross for movies. Toward this​ goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross​ (in millions of​ dollars) are collected and stored in the accompanying table. A linear regression was performed on these​ data, and the result is the linear regression equation Yi=−1.254+1.3968Xi.   Complete parts​ (a) through​ (d). a. Determine the coefficient of​ determination,r2​,and interpret its meaning. b. Determine the standard error of the estimate.   c. How useful do you think this regression model is for predicting opening weekend box office​ gross?   d. Can you think of other variables that might explain the variation in opening weekend box office​ gross?