Question

In: Statistics and Probability

Suppose you are testing a regression model for the presence of heteroskedasticity and the p-value is...

  1. Suppose you are testing a regression model for the presence of heteroskedasticity and the p-value is 0.00. Provide the null and alternative hypotheses, the rejection rule and interpret the result.

  2. Suppose you are testing for serial correlation and using the Serial Correlation LM text where the p-value is 0.8415. Provide the null and alternative hypotheses, the rejection rule and interpret the result.

Solutions

Expert Solution

(a)

Question:

Suppose you are testing a regression model for the presence of heteroskedasticity and the p-value is 0.00. Provide the null and alternative hypotheses, the rejection rule and interpret the result.

By Breusch - Pagen test for heteroskedasticity in linear regression, we have:

H0: Null Hypothesis: . (There is no significant heteroskedasticity in linear regression,)

where

HA: Alternative Hypothesis: (At least one of the is not 0). (There is a significant heteroskedasticity in linear regression,)

The Test Statistic is given by:

= n R2 k

where

n = the Sample Size

R = Coefficient of Determination based on a possible linear regression

k = number of independent variables.

The degrees of freedom is based on the number of independent variables instead of the sample size.

Rejection Region:

Reject H0 if calculated value of is greater than critical value of corresponding to significance level and the degrees of freedom which is based on the number of independent variables instead of the sample size.

Since p - value = 0.00 is less than = 0.05, the difference is significant. Reject null hypothesis.

Conclusion:
The data support the claim that there is a significant heteroskedasticity in linear regression,

(b)

Question:

Suppose you are testing for serial correlation and using the Serial Correlation LM text where the p-value is 0.8415. Provide the null and alternative hypotheses, the rejection rule and interpret the result.

H0: Null Hypothesis: (There is no serial correlation )

HA: Alternative Hypothesis: (At least one of the is not 0) (There is serial correlation ) (There is serial correlation ) (Claim)

Rejection Region:

Reject H0 if Calculated value of F is greater than critical value of F based on degrees of freedom and significance level .

Since p value = 0.8415 is greater than = 0.05, the difference is not significant. Fail to rejectnull hypothesis.

Conclusion:

The data support the claim that there is serial correlation


Related Solutions

Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type...
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type vs level of measurement ANOVA and Multiple Regression Outliers vs Influencers
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type...
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type vs level of measurement ANOVA and Multiple Regression Outliers vs Influencers Based on question 1e above, do you think the following scatter plots contain any outliers or any influential data points? Justify your answers on each plot. (iii)                                                                                          (iv) (i)                                                                                            (ii)      
Suppose you run a regression and the Serial Correlation LM Test, has a p-value of 0.0000....
Suppose you run a regression and the Serial Correlation LM Test, has a p-value of 0.0000. How would you interpret the results using an F-test?
Suppose you estimate a simple linear regression model and obtain a t-value for the slope coefficient...
Suppose you estimate a simple linear regression model and obtain a t-value for the slope coefficient of -3.1. Based on this, explain which of the following statements are correct or wrong: a) A 95% confidence interval for the true slope would exclude 0. b) It is possible that the point estimate for the slope is b_1=4. c) At the 10% level of significance you fail to reject the null hypothesis that the true slope is equal to 0. d) The...
(a) What is the relationship of the p-value and hypothesis testing? (b) What is a p-value...
(a) What is the relationship of the p-value and hypothesis testing? (b) What is a p-value threshold of 0.05 mean? (in words) (c) Why do you think that a p-value of 0.05 is used so often as a threshold? What is a situation when that value would be too large (i.e. a value much lower than 0.05 should be used)?
(a) What is the relationship of the p-value and hypothesis testing? (b) What is a p-value...
(a) What is the relationship of the p-value and hypothesis testing? (b) What is a p-value threshold of 0.05 mean? (in words) (c) Why do you think that a p-value of 0.05 is used so often as a threshold? What is a situation when that value would be too large (i.e. a value much lower than 0.05 should be used)?
Suppose that you are testing the hypotheses H0​: p=0.18 vs. HA​: p=/ 0.18. A sample of...
Suppose that you are testing the hypotheses H0​: p=0.18 vs. HA​: p=/ 0.18. A sample of size 150 results in a sample proportion of 0.25. ​a) Construct a 99​% confidence interval for p. ​ b) Based on the confidence​ interval, can you reject H0 at a =0.01​? Explain. ​c) What is the difference between the standard error and standard deviation of the sample​ proportion? ​d) Which is used in computing the confidence​ interval?
Can any linear regression model be checked for model adequacy by statistical testing for lack of...
Can any linear regression model be checked for model adequacy by statistical testing for lack of fit or goodness of fit? Why or why not? Please provide your answer with detailed justification (i.e., by mathematical proof or by showing a numerical example)
How do you perform Hypothesis Testing on a regression model using an ANOVA table below. This...
How do you perform Hypothesis Testing on a regression model using an ANOVA table below. This is to show the significance of the 4 independent variables. ANOVA df SS MS F Significance F Regression 3 17643.17 5881.05 22.21 0.00001376 Residual 14 3706.59 264.75 Total 17 21349.76
Suppose you will use a simple regression model to test the hypothesis H0 : beta1 =...
Suppose you will use a simple regression model to test the hypothesis H0 : beta1 = 0 H1 : beta1 not equal to 0 when the sample size is 25, SST = 128,000, and the correlation between X and Y is 0.69. Find F test statistics.?
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT