10. Below is computer output from the least squares regression analysis on the body mass index, BMI, and percent body fat for 10 randomly selected adult males. Which of the following represents the 95% confidence interval for the slope of the regression line relating BMI and percent body fat for the population of adult males? Predictor Constant Сoef SE Coef 2.786 -20.096 -7.213 0.000 BMI 1.695 0.2280 7.432 0.000 S = 3.195 R-Sq = 87.3% R-Sq(adj)=86.8% %3D

10. Below is computer output from the least squares regression analysis on the body mass index, BMI, and percent body fat for 10 randomly selected adult males. Which of the following represents the 95% confidence interval for the slope of the regression line relating BMI and percent body fat for the population of adult males? Predictor Constant Сoef SE Coef 2.786 -20.096 -7.213 0.000 BMI 1.695 0.2280 7.432 0.000 S = 3.195 R-Sq = 87.3% R-Sq(adj)=86.8% %3D

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

10. Below is computer output from the least squares regression analysis on the
body mass index, BMI, and percent body fat for 10 randomly selected adult
males. Which of the following represents the 95% confidence interval for the
slope of the regression line relating BMI and percent body fat for the population
of adult males?
Predictor
Coef
SE Coef
P
Constant
-20.096
2.786
-7.213
0.000
BMI
1.695
0.2280
7.432
0.000
S = 3.195
R-Sq = 87.3%
R-Sq(adj)=86.8%
%3D
(A) –20.096 ± 2.21(2.786)
(B) 1.695 ± 7.432(0.2280)
(C) 1.695 ±2.306(0.2280)
(D) 1.695 ± 2.262(0.2280)
(E) 1.695 ± 2.228(0.2280)

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