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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