# Correlations and Regression

Question description

## Height & Weight: Erroneous Data

As we discussed in chapter 10, sometimes an outlier can make or break a correlation. Data from 11 people regarding height and weight is given in the table below.

 x = height in inches y = weight in pounds 60 120 72 200 64 130 71 205 68 180 69 180 69 193 70 195 62 115 62 140 5.5 160

Question 3:

Part A

• Use software to determine the regression equation for predicting weight from height, using α = 0.05.
• What is the regression equation? Make sure you show your work and/or copy and paste your output into the body of your post.
• State the software you used to produce the regression equation.
• Clearly identify the values for the slope and the y-intercept.
• What is the expected weight for a person who is 62 inches tall?

Part B

• Use software to calculate the regression equation for predicting weight from height, excluding the last data point corresponding to a height of 5.5 inches (as the entry of 5.5 inches seems to be an error),using α = 0.05.
• What is the regression equation without the last data point? Make sure you show your work and/or copy and paste your output into the body of your post.
• Clearly identify the values for the slope and the y-intercept.
• Using the regression equation with the last data point excluded, what is the expected weight for a person who is 62 inches tall?
• Compare your results to those obtained in part A. What can you say about how excluding the outlier affected your results?

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