In many fast food restaurants, there is a strong correlation between a menu item's fat content (measured in grams) and its calorie content. We want to investigate this relationship. Using all of the food menu items at a well-known fast food restaurant, the fat content and calorie content were measured. We decide to fit the least-squares regression line to the data, with fat content (x) as the explanatory variable and calorie content (y) as the response variable. A scatterplot of the data (with regression line included) and a summary of the data are provided. One of the menu items is a hamburger with 107 grams of fat and 1410 calories. r = 0.979 (correlation between x and y) x = 40.35 grams (mean of the values of x) y = 662.88 calories (mean of the values of y) Sx = 27.99 grams (standard deviation of the values of x) sy = 324.90 calories (standard deviation of the values of y) 20 40 60 80 100 120 Fatigrams) The slope of the least-squares regression line is: O 0.979. O 16.08. O 11,36. O -11,36.
In many fast food restaurants, there is a strong correlation between a menu item's fat content (measured in grams) and its calorie content. We want to investigate this relationship. Using all of the food menu items at a well-known fast food restaurant, the fat content and calorie content were measured. We decide to fit the least-squares regression line to the data, with fat content (x) as the explanatory variable and calorie content (y) as the response variable. A scatterplot of the data (with regression line included) and a summary of the data are provided. One of the menu items is a hamburger with 107 grams of fat and 1410 calories. r = 0.979 (correlation between x and y) x = 40.35 grams (mean of the values of x) y = 662.88 calories (mean of the values of y) Sx = 27.99 grams (standard deviation of the values of x) sy = 324.90 calories (standard deviation of the values of y) 20 40 60 80 100 120 Fatigrams) The slope of the least-squares regression line is: O 0.979. O 16.08. O 11,36. O -11,36.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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
Transcribed Image Text:In
many
fast food restaurants, there is a strong correlation between a menu item's fat content (measured in grams) and
its calorie content. We want to investigate this relationship. Using all of the food menu items at a well-known fast food
restaurant, the fat content and calorie content were measured. We decide to fit the least-squares regression line to the
data, with fat content (x) as the explanatory variable and calorie content (y) as the response variable. A scatterplot of the
data (with regression line included) and a summary of the data are provided. One of the menu items is a hamburger with
107 grams of fat and 1410 calories.
r = 0.979 (correlation between x and y)
x = 40.35 grams (mean of the values of x)
y = 662.88 calories (mean of the values of y)
Sx =
27.99 grams (standard deviation of the values of x)
Sy
324.90 calories (standard deviation of the values of y)
20
40
60
80
100
120
Fat(grams)
The slope of the least-squares regression line is:
0.979.
16.08.
O 11.36.
O -11.36.
00S
000L
009
Calories
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