b. Using a = 0.05, test for overall significance.There exists significant relationship.c. Did the estimated regression equation provide a good fit to the data? Explain.|, because the R, value is lowerthan 0.50.Yesd. Use the t test and a = 0.05 to test Ho : B1 = 0 and Ho : B2 = 0. Use t table.For B1, the p-value is between 0.01 and 0.02 v, so rejectv Ho : B1 = 0.For B2, the p-value is between 0.05 and 0.10, so do not rejectv Ho : B2 = 0. The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA.ŷ = -1.41 + 0.0235x1 + 0.00486x2where¤1 = high-school grade point average12 = SAT mathemathics scorey = final college grade point averageRound test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations.a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVAdfMSSignificance FRegression1.76209ResidualTotal91.88CoefficientsStandard Errort Statp-valueIntercept-1.40530.4848X10.0234670.0086666X20.004860.001077

Solution: Given information: k= 2 independent variables n= 10 observation Sum of square of…

The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and hi ŷ = -1.41 + 0.0235¤1 + 0.00486x2 where I1 = high-school grade point average 12 = SAT mathemathics score y = final college grade point average Round test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df MS F Significance F Regression 1.76209 Residual Total 9 1.88 Coefficients Standard Error t Stat P-value Intercept -1.4053 0.4848 X1 0.023467 0.0086666 X2 0.00486 0.001077

The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and hi ŷ = -1.41 + 0.0235¤1 + 0.00486x2 where I1 = high-school grade point average 12 = SAT mathemathics score y = final college grade point average Round test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df MS F Significance F Regression 1.76209 Residual Total 9 1.88 Coefficients Standard Error t Stat P-value Intercept -1.4053 0.4848 X1 0.023467 0.0086666 X2 0.00486 0.001077

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%

b. Using a = 0.05, test for overall significance.
There exists significant relationship.
c. Did the estimated regression equation provide a good fit to the data? Explain.
|, because the R, value is lower
than 0.50.
Yes
d. Use the t test and a = 0.05 to test Ho : B1 = 0 and Ho : B2 = 0. Use t table.
For B1, the p-value is between 0.01 and 0.02 v, so reject
v Ho : B1 = 0.
For B2, the p-value is between 0.05 and 0.10
, so do not reject
v Ho : B2 = 0.

The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA.
ŷ = -1.41 + 0.0235x1 + 0.00486x2
where
¤1 = high-school grade point average
12 = SAT mathemathics score
y = final college grade point average
Round test statistic values to 2 decimal places and all other values to 4 decimal places. Do not round your intermediate calculations.
a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
df
MS
Significance F
Regression
1.76209
Residual
Total
9
1.88
Coefficients
Standard Error
t Stat
p-value
Intercept
-1.4053
0.4848
X1
0.023467
0.0086666
X2
0.00486
0.001077

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