Supposed that you were asked to examine the relationship between the height of children and their parents. To conduct such a study, you have collected data from 110 college students, and estimated the following relationship: Studenth_hat=19.6 + 0.73 × Midparh, R2 = 0.45, SER = 2.0 (7.2) (0.10) where Studenth is the height of students in inches, and Midparh is the average of the parental heights. Values in parentheses are heteroskedasticity robust standard errors. Both variables were adjusted so that the average female height was equal to the average male height.) If children, on average, were expected to be of the same height as their parents, then this would imply two hypotheses, one for the slope and one for the intercept.

Supposed that you were asked to examine the relationship between the height of children and their parents. To conduct such a study, you have collected data from 110 college students, and estimated the following relationship: Studenth_hat=19.6 + 0.73 × Midparh, R2 = 0.45, SER = 2.0 (7.2) (0.10) where Studenth is the height of students in inches, and Midparh is the average of the parental heights. Values in parentheses are heteroskedasticity robust standard errors. Both variables were adjusted so that the average female height was equal to the average male height.) If children, on average, were expected to be of the same height as their parents, then this would imply two hypotheses, one for the slope and one for the intercept.

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

100%

Supposed that you were asked to examine the relationship between the height of children and their
parents. To conduct such a study, you have collected data from 110 college students, and estimated
the following relationship:
Studenth_hat=19.6 + 0.73 × Midparh, R2 = 0.45, SER = 2.0
(7.2) (0.10)
where Studenth is the height of students in inches, and Midparh is the average of the parental
heights. Values in parentheses are heteroskedasticity robust standard errors. Both variables were
adjusted so that the average female height was equal to the average male height.)
If children, on average, were expected to be of the same height as their parents, then this would
imply two hypotheses, one for the slope and one for the intercept.
We reject the null hypothesis for the slope at 1% and we reject the null hypothesis for the intercept at 5%.
We do not reject the null hypothesis for the slope at 1% and we reject the null hypothesis for the intercept at
5%.
We reject the null hypothesis for the slope at 1% and we do not reject the null hypothesis for the intercept at
5%.
We do not reject the null hypothesis for the slope at 1% and we do not reject the null hypothesis for the
intercept at 5%.

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