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Data Set 11 Height (in) Weight (lbs) 65.73 121.50 66.43 112.71 70.01 135.00 69.48 128.68 68.63 124.41 68.36 140.03 68.39 117.52 68.77 143.87 69.92 141.17

Data Set 11
Height (in) Weight (lbs)
65.73 121.50
66.43 112.71
70.01 135.00
69.48 128.68
68.63 124.41
68.36 140.03
68.39 117.52
68.77 143.87
69.92 141.17
71.56 155.94
68.45 134.01
66.71 130.10
66.68 106.23
67.94 112.05
68.90 136.19
67.29 131.24
69.57 131.32
67.67 119.53
69.04 117.00
67.97 138.53
Mean 68.375 Mean 128.851
Median 68.42 Median 130.67
No Mode No Mode

Perform a linear regression. Find the equation of the linear equation that best fits your data and calculate the correlation coefficient (R). How does this compare to your analysis in week 2?

Response Post - Instructions

In your response posts, you will discuss the results and whether or not the results show a strong correlation or not. Discuss the value of R and what it means? What is ideal? Is this a good fit? Also, give examples in the real world where linear regression would make sense? When is a linear model the ideal model? In these cases what would you expect the value of R to be?

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