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A statistics practitioner in a large university is investigating the factors that affect salary of professors. He wondered if evaluations by students are related to salaries. To this end, he collected 100 observations on:y = Annual salary (in dollars)x = Mean score on teaching evaluationTo accomplish his goal, he assumes the following relationship:y = β(0) + β(1)x + ε Then, using Data Analysis, he obtained the following result.R2=0.23 Coefficient Standard Error Intercept 25675.5 11393x 5321 2119Required:What are the null and alternative hypotheses, respectively?

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Complete Question

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Answer:

The null hypothesis is  [tex]H_o : \beta_1 = 0[/tex]

 The alternative hypothesis is  [tex]H_1 : \beta_1 \ne 1[/tex]

Step-by-step explanation:

From the question we are told that

        The number observations is  [tex]n = 100[/tex]

         The  annual salary (in dollars) is  y

          The  mean score on teaching evaluation is  x

          The the relationship between the y and  x is

                [tex]y = \beta_0 + \beta _1 x + \epsilon[/tex]

Where  [tex]\beta _1[/tex] is the mean of the equation so

  The null hypothesis is  [tex]H_o : \beta_1 = 0[/tex]

   The alternative hypothesis is  [tex]H_1 : \beta_1 \ne 1[/tex]

         

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