Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. Weused linear regression to explore the relationship between the number of calories and amountof carbohydrates (in grams) Starbucks food menu items contain. The estimated regressionequation with carbohydrates as the response variable and the calories as the explanatoryvariable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below.variable minQ1 medianQ3maxmeansdn missingcalories80 300350 420500338.8105.4 77carbohydrates163145598044.916.6 77 16. Which of the following is a true statement regarding the slope?a. There is a positive association between calorie and carbohydrate content; however, becausethe slope is small the association between calories and carbohydrates is weak.b. A food item that has 100 calories above average is expected to have carbohydrates 1.1grams over average.c. Because the lowest calorie content of food observed is 80, and 0.11 calories is well belowthis lowest value, this is extrapolation and cannot be trusted.d. All statements are true.e. None of the above statements are true.

Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 +0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77

Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 +0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We
used linear regression to explore the relationship between the number of calories and amount
of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression
equation with carbohydrates as the response variable and the calories as the explanatory
variable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below.
variable min
Q1 median
Q3
max
mean
sd
n missing
calories
80 300
350 420
500
338.8
105.4 77
carbohydrates
16
31
45
59
80
44.9
16.6 77

16. Which of the following is a true statement regarding the slope?
a. There is a positive association between calorie and carbohydrate content; however, because
the slope is small the association between calories and carbohydrates is weak.
b. A food item that has 100 calories above average is expected to have carbohydrates 1.1
grams over average.
c. Because the lowest calorie content of food observed is 80, and 0.11 calories is well below
this lowest value, this is extrapolation and cannot be trusted.
d. All statements are true.
e. None of the above statements are true.

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