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Question 15 Write down the null and alternative hypothesis to test for first-order autocorrelation. Question 16 Calculate the Durbin-Watson test statistic of autocorrelation? Use two decimal places and show clear steps for calculating the test statistic in Excel. Answers without supporting Excel calculation will be marked as Zero. Answer:

          Question 15
Write down the null and alternative hypothesis to test for first-order autocorrelation.
Question 16
Calculate the Durbin-Watson test statistic of autocorrelation? Use two decimal places and show clear steps for calculating the test statistic in Excel. Answers without supporting Excel calculation will be marked as Zero.
Answer:
        
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Question 15
Write down the null and alternative hypothesis to test for first-order autocorrelation.
Question 16
Calculate the Durbin-Watson test statistic of autocorrelation? Use two decimal places and show clear steps for calculating the test statistic in Excel. Answers without supporting Excel calculation will be marked as Zero.
Answer:

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Elementary Statistics a Step by Step Approach
Elementary Statistics a Step by Step Approach
Allan G. Bluman 9th Edition
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The null hypothesis for the Durbin-Watson test is H0: ρ = 0, and the alternative hypothesis is Ha: ρ ≠ 0. To calculate the Durbin-Watson test statistic in Excel, follow these steps: 1. Calculate the first-order differences of the data. 2. Square the first-order differences. 3. Sum the squared first-order differences. 4. Divide the sum of squared first-order differences by the sum of squared data. 5. The result is the Durbin-Watson test statistic. Round to two decimal places.
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Transcript

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00:01 First state the hypothesis null hypothesis for the test of correlation in the residuals is that there is no autocorrelation present in the residuals the alternate hypothesis is that the autocorrelation present in the residuals second is test statistics the test statistics used to test for autocorrelation is the q statistics the q statistics calculated as the sum of the squared autocorrelations up to a certain log third is decision rule to determine whether to reject or fail the to reject the null hypothesis will compare the calculated q statistic to the critical value from the chi -square distribution so the critical value is determined based on the desired level of significance and degrees of freedom which is equal to the number of lags being tested for this decision if the calculated q statistics is greater than the critical value we reject the null hypothesis and conclude that there is evidence of auto correlation in the residuals if the calculated q statistics is less than or equal to the critical value we fail to reject the null hypothesis and conclude that there is no evidence of autocorrelation the residual first step is conclusion.
01:45 So based on the provided e views outputs we can see that the q statistics for each log is significantly greater than 0 with values of 0 .000 so this indicates that there is evidence of autocorrelation in the residuals therefore we reject the null hypothesis and conclude that the residuals do not follow a white noise process...
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