Based on the regression equation, what would be the predicted weight of a student who is 64 inches tall? Regression[DataSet2]Variables Entered/RemovedVariablesVariablesModelEnteredRemovedMethodWeight1Entera. Dependent Variable: Heightb. All requested variables entered.Model SummaryChange StatisticsAdjusted RSquareR SquareChangeSig. FChangeStd. Error ofModelR Squarethe EstimateF Changedf1df21.494a.244.2212.26127.24410.665133.003a. Predictors: (Constant), WeightANOVASum ofModelSquaresdfMean SquareFSig.1Regression54.534154.53410.665.003bResidual168.741335.113Total223.27534a. Dependent Variable: Heightb. Predictors: (Constant), Weight CoefficientsStandardizedUnstandardized CoefficientsCoefficientsModelВStd. ErrorBetaSig.1(Constant)53.6753.61114.866.000Weight.095.029.4943.266.003a. Dependent Variable: Height

Decision rule : linear relation exists if P-value < α Here P-value = 0.003 < 0.05 = α.…

Answered: Based on the regression equation, what…

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Based on the regression equation, what would be the predicted weight of a student who is 64 inches tall?

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015

1st Edition

ISBN:9781680331141

Author:HOUGHTON MIFFLIN HARCOURT

Publisher:HOUGHTON MIFFLIN HARCOURT

Chapter11: Data Analysis And Displays

Section11.3: Shapes Of Distributions

Problem 10E

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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

Based on the regression equation, what would be the predicted weight of a student who is 64 inches tall?

Regression
[DataSet2]
Variables Entered/Removed
Variables
Variables
Model
Entered
Removed
Method
Weight
1
Enter
a. Dependent Variable: Height
b. All requested variables entered.
Model Summary
Change Statistics
Adjusted R
Square
R Square
Change
Sig. F
Change
Std. Error of
Model
R Square
the Estimate
F Change
df1
df2
1
.494a
.244
.221
2.26127
.244
10.665
1
33
.003
a. Predictors: (Constant), Weight
ANOVA
Sum of
Model
Squares
df
Mean Square
F
Sig.
1
Regression
54.534
1
54.534
10.665
.003b
Residual
168.741
33
5.113
Total
223.275
34
a. Dependent Variable: Height
b. Predictors: (Constant), Weight

Coefficients
Standardized
Unstandardized Coefficients
Coefficients
Model
В
Std. Error
Beta
Sig.
1
(Constant)
53.675
3.611
14.866
.000
Weight
.095
.029
.494
3.266
.003
a. Dependent Variable: Height

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