In a simple linear regression based on 30 observations, it is found that b1 = 3.57 and se(b1) = 1.36. Consider the hypotheses:H0: β1 = 0 and HA: β1 ≠ 0.a. Calculate the value of the test statistic. (Round your answer to 3 decimal places.)   b. Find the p-value.   [Hint: The test statistic has a t-distribution with df = 30 – 2. Refer to Chapter 9 of the formula sheet to get the appropriate p-value.] p-value < 0.01 0.01   p-value < 0.02   p-value   0.10   0.05   p-value < 0.10   0.02   p-value < 0.05   c. At the 5% significance level, what is the conclusion? Is the explanatory variable statistically significant? Reject H0; the explanatory variable is significant. Reject H0; the explanatory variable is not significant. Do not reject H0; the explanatory variable is significant. Do not reject H0; the explanatory variable is not significant.

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In a simple linear regression based on 30 observations, it is found that b1 = 3.57 and se(b1) = 1.36. Consider the hypotheses:

H0: β1 = 0 and HA: β1 ≠ 0.

a. Calculate the value of the test statistic. (Round your answer to 3 decimal places.)

 



b. Find the p-value.

 

[Hint: The test statistic has a t-distribution with df = 30 – 2. Refer to Chapter 9 of the formula sheet to get the appropriate p-value.]

  • p-value < 0.01
  • 0.01
     
    p-value < 0.02
     
  • p-value
     
    0.10
     
  • 0.05
     
    p-value < 0.10
     
  • 0.02
     
    p-value < 0.05
     



c. At the 5% significance level, what is the conclusion? Is the explanatory variable statistically significant?

  • Reject H0; the explanatory variable is significant.
  • Reject H0; the explanatory variable is not significant.
  • Do not reject H0; the explanatory variable is significant.
  • Do not reject H0; the explanatory variable is not significant.
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