A multiple regression model is to be constructed to predict the heart rate in beats per minute (bpm) of a person based upon their age, weight and height. Data has been collected on 10 randomly selected individuals: Heart Rate Age Weight Height 81 51 211 71 83 41 108 69 112 48 216 69 63 34 105 69 99 47 226 66 82 37 102 64 57 23 122 62 70 27 261 67 88 24 251 72 62 38 101 61 Copy-and-paste the data into an Excel spreadsheet. Use Excel to perform all calculations. a) Calculate the multiple regression equation using all three explanatory variables. Write the equation in the answer blank. Round all of the equation coefficient values to two (2) decimal places. You may use the variables names or replace them with y, x1, x2, and x3. b) What percentage of variation in heart rates is explained by the regression model using all three variables? c) Using the 10% level of significance, which predictor variables are statistically significant predictors of heart rate? d) Remove the Height variable and re-calculate the regression equation. Write the new equation. Round to two (2) decimal places.
A multiple regression model is to be constructed to predict the heart rate in beats per minute (bpm) of a person based upon their age, weight and height. Data has been collected on 10 randomly selected individuals: Heart Rate Age Weight Height 81 51 211 71 83 41 108 69 112 48 216 69 63 34 105 69 99 47 226 66 82 37 102 64 57 23 122 62 70 27 261 67 88 24 251 72 62 38 101 61 Copy-and-paste the data into an Excel spreadsheet. Use Excel to perform all calculations. a) Calculate the multiple regression equation using all three explanatory variables. Write the equation in the answer blank. Round all of the equation coefficient values to two (2) decimal places. You may use the variables names or replace them with y, x1, x2, and x3. b) What percentage of variation in heart rates is explained by the regression model using all three variables? c) Using the 10% level of significance, which predictor variables are statistically significant predictors of heart rate? d) Remove the Height variable and re-calculate the regression equation. Write the new equation. Round to two (2) decimal places.
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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A multiple regression model is to be constructed to predict the heart rate in beats per minute (bpm) of a person based upon their age, weight and height. Data has been collected on 10 randomly selected individuals:
Heart Rate Age Weight Height
81 51 211 71
83 41 108 69
112 48 216 69
63 34 105 69
99 47 226 66
82 37 102 64
57 23 122 62
70 27 261 67
88 24 251 72
62 38 101 61
Copy-and-paste the data into an Excel spreadsheet. Use Excel to perform all calculations.
a) Calculate the multiple regression equation using all three explanatory variables. Write the equation in the answer blank. Round all of the equation coefficient values to two (2) decimal places. You may use the variables names or replace them with y, x1, x2, and x3.
b) What percentage of variation in heart rates is explained by the regression model using all three variables?
c) Using the 10% level of significance, which predictor variables are statistically significant predictors of heart rate?
d) Remove the Height variable and re-calculate the regression equation. Write the new equation. Round to two (2) decimal places.
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