Question

# Suppose you run a regression containing observations for each of the 74 kinds of cars releasted...

Suppose you run a regression containing observations for each of the 74 kinds of cars releasted in 1978 in the United States, and you regress price (in dollars) on weight (in pounds). You get the following results: βˆ 0 is -6.71, with SE 1174.4. βˆ 1 (slope coefficient on weight) is 2.04 with SE .377.

• (4 points) Say, in words, what the slope coefficient means in this case, without taking a stand on causality.

• (5 points) Suppose I give you the following information: the sum of squares total is roughly equal to 635 million, and the sum of squares explained is equal to 185 million. Please report the R2 and the correlation coefficient between price and weight. • (5 points) Use your regression model to predict what the price would be for a car that weighs 3000 pounds.

• (4 points) Use the SER to add uncertainty and make this prediction an interval.

• (5 points) Build a 95% confidence interval for the slope coefficient and report the p-value for comparing it to 0. Interpret your results.

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