Do the data indicate that there is a difference in the average number of completed passes for the two quarterbacks? Test using a = 0.05. (Use u, for the population mean for Alex Smith and u, for the population mean for Joe Flacco.) State the null and alternative hypotheses. O Ho: (H2 - H2) = 0 versus H: (H1 – H2) * 0 O Ho: (H, - H2) = 0 versus H: (Hq - H2) > 0 O Ho: (Hy- H2) = 0 versus H,: (H, - H2) < O O Ho: (Hy - H2) < 0 versus H,: (H, - H2) > 0 O Hạ: (Hy - H2) # 0 versus H,: (H, - H2) = 0 State the test statistic. (Round your answer to three decimal places.) State the rejection region. (If the test is one-tailed, enter NONE for the unused region. Round your answers to three decimal places.) t< State the conclusion. O H, is rejected. There is sufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. O Ho is not rejected. There insufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. O Ho is not rejected. There is sufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. O H, is rejected. There is insufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. What is the p-value for the test? (Round your answer to three decimal places.)

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9 this question has part a,b,c, and d

(b) Do the data indicate that there is a difference in the average number of completed passes for the two quarterbacks? Test using \( \alpha = 0.05 \). (Use \( \mu_1 \) for the population mean for Alex Smith and \( \mu_2 \) for the population mean for Joe Flacco.)

State the null and alternative hypotheses.

- \( H_0: (\mu_1 - \mu_2) = 0 \) versus \( H_a: (\mu_1 - \mu_2) \neq 0 \)
- \( H_0: (\mu_1 - \mu_2) = 0 \) versus \( H_a: (\mu_1 - \mu_2) < 0 \)
- \( H_0: (\mu_1 - \mu_2) = 0 \) versus \( H_a: (\mu_1 - \mu_2) > 0 \)
- \( H_0: (\mu_1 - \mu_2) \leq 0 \) versus \( H_a: (\mu_1 - \mu_2) > 0 \)
- \( H_0: (\mu_1 - \mu_2) \geq 0 \) versus \( H_a: (\mu_1 - \mu_2) < 0 \)

State the test statistic. (Round your answer to three decimal places.)
\[ t = \]

State the rejection region. (If the test is one-tailed, enter NONE for the unused region. Round your answers to three decimal places.)
- \( t > \)
- \( t < \)

State the conclusion.
- \( H_0 \) is rejected. There is sufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco.
- \( H_0 \) is not rejected. There is insufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco.
- \( H_0 \) is not rejected. There is sufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco.
- \( H_0 \) is rejected. There is insufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco.

(c) What is the p-value for the test? (Round your answer to three
Transcribed Image Text:(b) Do the data indicate that there is a difference in the average number of completed passes for the two quarterbacks? Test using \( \alpha = 0.05 \). (Use \( \mu_1 \) for the population mean for Alex Smith and \( \mu_2 \) for the population mean for Joe Flacco.) State the null and alternative hypotheses. - \( H_0: (\mu_1 - \mu_2) = 0 \) versus \( H_a: (\mu_1 - \mu_2) \neq 0 \) - \( H_0: (\mu_1 - \mu_2) = 0 \) versus \( H_a: (\mu_1 - \mu_2) < 0 \) - \( H_0: (\mu_1 - \mu_2) = 0 \) versus \( H_a: (\mu_1 - \mu_2) > 0 \) - \( H_0: (\mu_1 - \mu_2) \leq 0 \) versus \( H_a: (\mu_1 - \mu_2) > 0 \) - \( H_0: (\mu_1 - \mu_2) \geq 0 \) versus \( H_a: (\mu_1 - \mu_2) < 0 \) State the test statistic. (Round your answer to three decimal places.) \[ t = \] State the rejection region. (If the test is one-tailed, enter NONE for the unused region. Round your answers to three decimal places.) - \( t > \) - \( t < \) State the conclusion. - \( H_0 \) is rejected. There is sufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. - \( H_0 \) is not rejected. There is insufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. - \( H_0 \) is not rejected. There is sufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. - \( H_0 \) is rejected. There is insufficient evidence to indicate that the average number of completed passes is different for Alex Smith and Joe Flacco. (c) What is the p-value for the test? (Round your answer to three
### Comparison of Quarterback Performance: Alex Smith vs. Joe Flacco (2017 NFL Season)

The table below shows the number of completed passes for Alex Smith, quarterback for the Kansas City Chiefs, and Joe Flacco, quarterback for the Baltimore Ravens, during the 2017 NFL season.

| Alex Smith | Joe Flacco |
|------------|------------|
| 25         | 27         |
| 27         | 29         |
| 23         | 25         |
| 29         | 34         |
| 23         | 31         |
| 34         | 24         |
| 23         | 34         |
| 19         | 10         |
| 27         | 8          |
| 25         | 26         |
| 23         | 29         |
| 22         | 29         |
| 19         | 9          |
| 25         | 31         |
| 29         | 28         |
| 20         | 29         |

#### Statistical Analysis using 2-Sample T-Test

The following analysis uses a TI-84 Plus calculator to perform a 2-sample t-test to compare the means of two independent samples:

- \( H_0: \mu_1 = \mu_2 \)
- \( H_a: \mu_1 \neq \mu_2 \)
- t = 0.352034901
- p = 0.7497465338
- df = 22
- \( \bar{x}_1 = 22.73333333 \)
- \( \bar{x}_2 = 22 \)
- \( s_{x1} = 4.633060973 \)
- \( s_{x2} = 7.589466384 \)

#### Consideration for Variance

(a) The TI-84 Plus analysis uses the pooled estimate of \(\sigma^2\). Is the assumption of equal variances reasonable? Why or why not?

- Yes, because the ratio of the larger variance to smaller variance is less than 3.
- No, because the ratio of the larger variance to smaller variance is more than 3.
- No, because the ratio of the larger variance to smaller variance is not equal to 1.
- No, because the ratio of the larger variance to smaller variance is less than 3.
- No, because the ratio
Transcribed Image Text:### Comparison of Quarterback Performance: Alex Smith vs. Joe Flacco (2017 NFL Season) The table below shows the number of completed passes for Alex Smith, quarterback for the Kansas City Chiefs, and Joe Flacco, quarterback for the Baltimore Ravens, during the 2017 NFL season. | Alex Smith | Joe Flacco | |------------|------------| | 25 | 27 | | 27 | 29 | | 23 | 25 | | 29 | 34 | | 23 | 31 | | 34 | 24 | | 23 | 34 | | 19 | 10 | | 27 | 8 | | 25 | 26 | | 23 | 29 | | 22 | 29 | | 19 | 9 | | 25 | 31 | | 29 | 28 | | 20 | 29 | #### Statistical Analysis using 2-Sample T-Test The following analysis uses a TI-84 Plus calculator to perform a 2-sample t-test to compare the means of two independent samples: - \( H_0: \mu_1 = \mu_2 \) - \( H_a: \mu_1 \neq \mu_2 \) - t = 0.352034901 - p = 0.7497465338 - df = 22 - \( \bar{x}_1 = 22.73333333 \) - \( \bar{x}_2 = 22 \) - \( s_{x1} = 4.633060973 \) - \( s_{x2} = 7.589466384 \) #### Consideration for Variance (a) The TI-84 Plus analysis uses the pooled estimate of \(\sigma^2\). Is the assumption of equal variances reasonable? Why or why not? - Yes, because the ratio of the larger variance to smaller variance is less than 3. - No, because the ratio of the larger variance to smaller variance is more than 3. - No, because the ratio of the larger variance to smaller variance is not equal to 1. - No, because the ratio of the larger variance to smaller variance is less than 3. - No, because the ratio
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