A simple linear regression model was created based on 25 samples. The 95% confidence interval for the estimate of β1 is (1.5, 5.9). Find the F-statistic for the model. Report your answer in 3 decimal places.

A car lot wants to predict the # of car accessories they need to sell monthly based on the number of cars sold. The car lot owner randomly selects 12 months of data. The simple linear regression equation is ý = 14 - 2x. The coefficient of determination is 0.6364. What is the correlation coefficient to describe the relationship between these two variables? Multiple Choice

When should a regression model not be used to make a prediction?

The​ least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a​ bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Predict the median income of a region in which 30​% of adults 25 years and older have at least a​ bachelor's degree.

The table below shows the amounts of crude oil​ (in thousands of barrels per​ day) produced by a country and the amounts of crude oil​ (in thousands of barrels per​ day) imported by a​ country, for the last seven years. Construct and interpret a 98​% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,464 thousand barrels per day. The equation of the regression line is y=-1.106x+15,759.462   Oil_produced,_x    Oil_imported,_y5,816    9,3455,741    9,1245,660    9,6325,405    10,0095,155    10,1685,059    10,1055,015    10,055

Use the shoe print lengths and heights shown below to find the regression​ equation, letting shoe print lengths be the predictor​ (x) variable. Then find the best predicted height of a male who has a shoe print length of 28.5 cm. Would the result be helpful to police crime scene investigators in trying to describe the​ male? Use a significance level of α=0.05.   Shoe Print​ (cm) 29.1   29.1   31.8   31.9   27.5     Foot Length​ (cm) 25.7   25.4   27.9   26.7   25.1     Height​ (cm) 175.4   177.8   185.2   175.4   173.2           The best predicted height is enter your response here cm. ​(Round to two decimal places as​ needed.) Would the result be​ helpful?     A. ​No, because the description would be the same regardless of shoe print length.   B. ​Yes, because the description would be based on an actual shoe print length.   C. ​Yes, because the correlation is​ strong, so the predicted…

A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.614 b=32.79 r2=0.808201 r=0.899 Use this to predict the final exam score of a student who studies 1 hours per week, and please round your answer to a whole number.