MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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- Scenario: A medical researcher wishes to see whether there is a relationship between a person's age, cholesterol level, and systolic blood pressure. Eight people are randomly selected. The data is listed in the table. First, find the multiple regression equation. Next, determine the coefficient of determination. Then, use the regression equation to predict a person's blood pressure reading if the person selected is 50 years old with a cholesterol reading of 220. Age Cholesterol level Blood pressure Person 1 38 220 116 Person 2 41 225 120 Person 3 45 200 123 Person 4 48 190 131 Person 5 51 250 142 Person 6 53 215 145 Person 7 57 200 148 Person 8 61 170 150 Discussion Prompts Respond to the following prompts in your initial post: 1. Identify the explanatory variables and response variable for the data. 2. What is the multiple regression equation for the data? 3. What is the coefficient of determination? 4. If a person 50 years old with a cholesterol of 220 is selected, what is that…arrow_forwardThe accompanying data are the shoe sizes and heights (in inches) of 14 men. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x=11.5 (b) x=8.0 (c) x=15.5 (d) x= Shoe Size, x Height, y8.5 66.09.0 69.09.0 67.59.5 70.510.0 70.510.0 72.010.5 71.510.5 70.011.0 71.011.0 71.511.0 73.012.0 73.012.0 74.012.5 73.5 The equation of the regression line is y= ____x +____arrow_forwardThe data show systolic and diastolic blood pressure of certain people. Find the regression equation, letting the systolic reading be the independent (x) variable. If one of these people has a systolic blood pressure of 125 mm Hg, what is the best predicted diastolic blood pressure? Systolic Diastolic Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? ŷ-+x (Round to two decimal places as needed.) What is the best predicted diastolic blood pressure? y=(Round to one decimal place as needed.) C 148 115 82 83 82 136 115 127 128 140 97 60 65 93 145 101 108arrow_forward
- A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.38 b=39.555 r2=0.693889 r=-0.833 Assume the correlation is significant, and use this to predict the number of situps a person who watches 7 hours of TV can do (to one decimal place)arrow_forwardThe age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150arrow_forwardFrom a regression equation r2= 0.39 and the slope = -2.8 What is the linear correlation coefficient r?arrow_forward
- A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.96 b=35.944 r2=0.736164 r=-0.858 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)arrow_forwardA regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.96 b=35.944 r2=0.736164 r=-0.858 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)arrow_forwardSolve attached photo.arrow_forward
- I need help with this last part of this exercise.arrow_forwardUsing the data, the mad scientist wishes to compute a regression equation to predict future Werewolf captures (he wants to do this regardless of whether the correlation above is significant—he is mad after all). Nights until the full moon (X) # of Werewolves caught (Y) 7 1 6 2 2 4 3 5 2 8 1 Calculate a regression equation to predict Werewolf captures (Ŷ) from number of nights until the full moon (X) 2 Use this regression equation to predict how many Werewolves will be caught 3 nights until the full moon. 3 Use this regression equation to predict how many Werewolves will be caught 6 nights until the full moon.arrow_forwardA regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.091 b=30.228 r2=0.698896 r=-0.836 Use this to predict the number of situps a person who watches 3.5 hours of TV can do (to one decimal place)arrow_forward
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