Consider the following data set. d)  testing at a 5% significance level, can you say that the intercept (β0) is not zero? How does this conclusion agree with the plot in b)? e)  Assume that the first data point is an outlier (e.g. the value was misrecorded). Remove the outlier, and redo parts b)-d). Plot the new data set and the new regression line. Comment on the difference. Also comment on the difference between the results of the tests in c) and d), if any.

If the linear correlation between two variables is negative, what can be said about the slope of the regression line? ..... Choose the correct answer below. A. More information is needed B. Negative C. Positive

Is there a relationship between the weight and price of a mountain​ bike? The following data set gives the weights and prices for ten mountain bikes. Let the expanatory variable x be the weight in pounds and the response variable y be the​ bike's price.   Weight​ (LB) 32 33 29 29 34 37 28 30 34 30   Price​ ($) 980 350 430 710 930 160 590 530 180 1090     a. Construct a scatterplot. Interpret. b. Find the regression equation. Interpret the slope in context. Does the​ y-intercept have contextual​ meaning? c. You decide to purchase a mountain bike that weighs 33 pounds. What is the predicted price for the​ bike? a. Which scatterplot below correctly shows the​ data?     A.       254001200xy         A coordinate system has a horizontal x-axis labeled from 25 to 40 in increments of 1 and a vertical y-axis labeled from 0 to 1200 in increments of 50. A cluster of plotted points that form a line that falls from left to…

Data on the price​ ($1000s) and the size​ (1000 ft2 sqaured) for 156 randomly selected houses that have been sold is summarized in the accompanying regression output and plots. Complete parts a and b ​a) Check the assumptions and conditions for inference. Select all that apply.     A. The residuals look random.   B. The residuals are nearly normal.   C. The scatterplot looks straight enough.   D. The residual plot and the scatterplot show consistent variability.   E. None of the assumptions and conditions for inference are satisfied.