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Consider the excel output attached and answer the following... A) Us the t-statistic approach to test for linear relationship between Y and X at 5% significance level. Identify the test statistic in the regression output and show how it is calculated. Hypothesis:             Null Hypothesis:         H0: ___ 0 (no linear relationship exists) Alternative Hypothesis: HA: B1 ≠ 0 (linear relationship exists)- Two tail   Test-statistic:      Level of Significance:                 _______________________________ Critical value of test statistic:  _______________________________ Decision Rule:      Decision:   Conclusion:           B) Use is p-value approach to test of the existence of a linear relationship between a Y and X at 5% significance level (use the regression table values rather than calculations). Hypothesis:               Null Hypothesis:            H0: ___________________________________   Alternative Hypothesis: HA: _____________________________________   p-value =       Decision Rule:            Decision:     Conclusion:

Consider the excel output attached and answer the following... A) Us the t-statistic approach to test for linear relationship between Y and X at 5% significance level. Identify the test statistic in the regression output and show how it is calculated. Hypothesis:             Null Hypothesis:         H0: ___ 0 (no linear relationship exists) Alternative Hypothesis: HA: B1 ≠ 0 (linear relationship exists)- Two tail   Test-statistic:      Level of Significance:                 _______________________________ Critical value of test statistic:  _______________________________ Decision Rule:      Decision:   Conclusion:           B) Use is p-value approach to test of the existence of a linear relationship between a Y and X at 5% significance level (use the regression table values rather than calculations). Hypothesis:               Null Hypothesis:            H0: ___________________________________   Alternative Hypothesis: HA: _____________________________________   p-value =       Decision Rule:            Decision:     Conclusion:

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter5: Inverse, Exponential, And Logarithmic Functions
Section5.6: Exponential And Logarithmic Equations
Problem 67E
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Consider the excel output attached and answer the following...

A)

  1. Us the t-statistic approach to test for linear relationship between Y and X at 5% significance level. Identify the test statistic in the regression output and show how it is calculated.

Hypothesis:

            Null Hypothesis:         H0: ___ 0 (no linear relationship exists)

Alternative Hypothesis: HA: B1 ≠ 0 (linear relationship exists)- Two tail

 

Test-statistic: 

 

 

Level of Significance:                 _______________________________

Critical value of test statistic:  _______________________________

Decision Rule: 

 

 

Decision:  

Conclusion:  

 

 

 

 

B)

  1. Use is p-value approach to test of the existence of a linear relationship between a Y and X at 5% significance level (use the regression table values rather than calculations).

Hypothesis:

 

            Null Hypothesis:            H0: ___________________________________

 

Alternative Hypothesis: HA: _____________________________________

 

p-value =  

 

 

Decision Rule:   

 

 

 

 

Decision:

 

 

Conclusion:  

 

SUMMARY OUTPUT 60 Regression Statistics Multiple R R Square 50 0.7969 40 0.6351 > 30 Adjusted R Square 0.5742 20 Standard Error 5.7674 10 Observations 8 6. ANOVA df MS Significance F Regression Residual 1 347.2951681 347.2952 10.44079 0.017883022 6 199.5798319 33.26331 Total 7 546.875 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 23.025 5.099 4.516 0.004 10.549 35.501 4.832 1.495 3.231 0.018 1.173 8.491
Transcribed Image Text:SUMMARY OUTPUT 60 Regression Statistics Multiple R R Square 50 0.7969 40 0.6351 > 30 Adjusted R Square 0.5742 20 Standard Error 5.7674 10 Observations 8 6. ANOVA df MS Significance F Regression Residual 1 347.2951681 347.2952 10.44079 0.017883022 6 199.5798319 33.26331 Total 7 546.875 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 23.025 5.099 4.516 0.004 10.549 35.501 4.832 1.495 3.231 0.018 1.173 8.491
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