State whether the standardized test statistic t indicates that you should reject the null hypothesis. Explain. (a) t=2.221 (b) t=0 (c) t= - 2.121 (d) t= -2.245 te-2.183 (a) For t=2.221, should you reject or fail to reject the null hypothesis? O A. Fail to reject Ho, becauset< -2.183. O B. Reject Ho, because t> -2.183. OC. Reject Ho, because t< - 2.183. O D. Fail to reject Ho, becauset> -2.183. (b) For t= 0, should you reject or fail to reject the null hypothesis?
State whether the standardized test statistic t indicates that you should reject the null hypothesis. Explain. (a) t=2.221 (b) t=0 (c) t= - 2.121 (d) t= -2.245 te-2.183 (a) For t=2.221, should you reject or fail to reject the null hypothesis? O A. Fail to reject Ho, becauset< -2.183. O B. Reject Ho, because t> -2.183. OC. Reject Ho, because t< - 2.183. O D. Fail to reject Ho, becauset> -2.183. (b) For t= 0, should you reject or fail to reject the null hypothesis?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:**Transcription of Educational Content:**
**Topic: Hypothesis Testing with Standardized Test Statistics**
State whether the standardized test statistic \( t \) indicates that you should reject the null hypothesis. Explain.
Given values:
- (a) \( t = 2.221 \)
- (b) \( t = 0 \)
- (c) \( t = -2.121 \)
- (d) \( t = -2.245 \)
**Questions:**
(a) For \( t = 2.221 \), should you reject or fail to reject the null hypothesis?
- **A.** Fail to reject \( H_0 \), because \( t < 2.183 \).
- **B.** Reject \( H_0 \), because \( t > 2.183 \).
- **C.** Reject \( H_0 \), because \( t < -2.183 \).
- **D.** Fail to reject \( H_0 \), because \( t > -2.183 \).
(b) For \( t = 0 \), should you reject or fail to reject the null hypothesis?
**Graph Explanation:**
The graph illustrates a standard normal distribution curve. The critical value is marked at \( t_0 = -2.183 \). The shaded region indicates the rejection area in a two-tailed hypothesis test, which visually displays where the values of \( t \) would lead to rejecting the null hypothesis. The curve shows that one critical value lies left on the horizontal axis, implying this is likely a left-tailed or two-tailed test. Values of \( t \) falling into this region would suggest rejecting the null hypothesis, depending on the specific hypothesis and significance level.

Transcribed Image Text:### Understanding the Standardized Test Statistic and Null Hypothesis Rejection
This exercise involves determining whether specific standardized test statistics (\( t \)) indicate the rejection of the null hypothesis. Let's analyze each provided scenario.
#### Question:
State whether the standardized test statistic indicates that you should reject the null hypothesis. Explain.
#### Options:
(a) \( t = 2.221 \)
(b) \( t = 0 \)
(c) \( t = -2.121 \)
(d) \( t = -2.245 \)
The accompanying graph is a standard bell curve with a critical value \( t_0 = -2.183 \). This value marks the threshold for rejection of the null hypothesis on the left tail of the distribution.
#### Evaluation:
- For \( t = 2.221 \): Since \( 2.221 > -2.183 \), we do not reject the null hypothesis.
- For \( t = 0 \): Since \( 0 > -2.183 \), we do not reject the null hypothesis.
- For \( t = -2.121 \): Since \(-2.121 > -2.183 \), we do not reject the null hypothesis.
- For \( t = -2.245 \): Since \(-2.245 < -2.183 \), we reject the null hypothesis.
#### Analysis for Part (b):
For \( t = 0 \), should you reject or fail to reject the null hypothesis?
- **Options:**
- A. Fail to reject \( H_0 \), because \( t > -2.183 \).
- B. Fail to reject \( H_0 \), because \( t < -2.183 \).
- C. Reject \( H_0 \), because \( t < -2.183 \).
- D. Reject \( H_0 \), because \( t > -2.183 \).
**Correct Choice:** A. Fail to reject \( H_0 \), because \( t > -2.183 \).
#### Analysis for Part (c):
For \( t = -2.121 \), should you reject or fail to reject the null hypothesis?
- Click to select your answer.
With a critical value of \( t_0 = -2.183 \), the conclusion for each scenario above assists in determining the decision regarding the null hypothesis based on the comparison of the calculated \( t \)-value against
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