(1 point) In order to compare the means of two populations, independent random samples of 266 observations are selected from each population, with the following results: Sample 1 Sample 2 x1 = 1 x2 = 0 S1 = 105 s2 = 130 (a) Use a 97 % confidence interval to estimate the difference between the population means (µ1 – µ2). - -21.235 < (H1 – H2) < 23.235 (b) Test the null hypothesis: Ho : (µ1 – µ2) = 0 versus the alternative hypothesis: H. : (µj - H2) # 0. Using a = 0.03, give the following: (i) the test statistic z = (ii) the positive critical z score 2.176 (iii) the negative critical z score -2.176 The final conclustion is A. There is not sufficient evidence to reject the null hypothesis that (u1 – µ2) = 0. B. We can reject the null hypothesis that (u1 – µ2) = 0 and accept that (u1 – µ2) # 0. (c) Test the null hypothesis: Ho : (µ1 – µ2) = 21 versus the alternative hypothesis: H. : (µ1 - H2) # 21. Using a = 0.03, give the following: (i) the test statistic z = -1.952 (ii) the positive critical z score 2.176 (iii) the negative critical z score -2.176

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In order to compare the means of two populations, independent random samples of 266 observations are selected from each population, with the following results:

- **Sample 1:** 
  - \(\bar{x}_1 = 1\)
  - \(s_1 = 105\)

- **Sample 2:** 
  - \(\bar{x}_2 = 0\)
  - \(s_2 = 130\)

### (a) Use a 97% confidence interval to estimate the difference between the population means \((\mu_1 - \mu_2)\).

\[
-21.235 \leq (\mu_1 - \mu_2) \leq 23.235
\]

### (b) Test the null hypothesis: 

\[
H_0 : (\mu_1 - \mu_2) = 0
\]

versus the alternative hypothesis:

\[
H_a : (\mu_1 - \mu_2) \neq 0
\]

Using \(\alpha = 0.03\), provide the following:

- (i) the test statistic \(z =\)

- (ii) the positive critical \(z\) score: \(2.176\)

- (iii) the negative critical \(z\) score: \(-2.176\)

**The final conclusion is:**

- **A. There is not sufficient evidence to reject the null hypothesis that \((\mu_1 - \mu_2) = 0\).**
- B. We can reject the null hypothesis that \((\mu_1 - \mu_2) = 0\) and accept that \((\mu_1 - \mu_2) \neq 0\).

### (c) Test the null hypothesis: 

\[
H_0 : (\mu_1 - \mu_2) = 21
\]

versus the alternative hypothesis:

\[
H_a : (\mu_1 - \mu_2) \neq 21
\]

Using \(\alpha = 0.03\), provide the following:

- (i) the test statistic \(z = -1.952\)

- (ii) the positive critical \(z\) score: \(2.176\)

- (iii) the negative critical \(z\) score: \(-2.176\)
Transcribed Image Text:In order to compare the means of two populations, independent random samples of 266 observations are selected from each population, with the following results: - **Sample 1:** - \(\bar{x}_1 = 1\) - \(s_1 = 105\) - **Sample 2:** - \(\bar{x}_2 = 0\) - \(s_2 = 130\) ### (a) Use a 97% confidence interval to estimate the difference between the population means \((\mu_1 - \mu_2)\). \[ -21.235 \leq (\mu_1 - \mu_2) \leq 23.235 \] ### (b) Test the null hypothesis: \[ H_0 : (\mu_1 - \mu_2) = 0 \] versus the alternative hypothesis: \[ H_a : (\mu_1 - \mu_2) \neq 0 \] Using \(\alpha = 0.03\), provide the following: - (i) the test statistic \(z =\) - (ii) the positive critical \(z\) score: \(2.176\) - (iii) the negative critical \(z\) score: \(-2.176\) **The final conclusion is:** - **A. There is not sufficient evidence to reject the null hypothesis that \((\mu_1 - \mu_2) = 0\).** - B. We can reject the null hypothesis that \((\mu_1 - \mu_2) = 0\) and accept that \((\mu_1 - \mu_2) \neq 0\). ### (c) Test the null hypothesis: \[ H_0 : (\mu_1 - \mu_2) = 21 \] versus the alternative hypothesis: \[ H_a : (\mu_1 - \mu_2) \neq 21 \] Using \(\alpha = 0.03\), provide the following: - (i) the test statistic \(z = -1.952\) - (ii) the positive critical \(z\) score: \(2.176\) - (iii) the negative critical \(z\) score: \(-2.176\)
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