5. Not self-graded (Revision of Exercise 7.3 on p.257) An random sample is selected from an approximately normal population with an unknown standard deviation. For each the given set of hypotheses, sample size and the T-statistic, find the p-value, draw a t-curve and shade the region of which the area the p-value indicates. As it's not possible to find the precise P-values using a t-table, it suffices to give a range. (а) На : и > 0.5, п %3D 26, Т %3D 2.6 (b) На : и20.5, п %3 26, Т %3D 2.6 (с) На : и< 3, п %3D 18, Т %3D -2.2

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**Exercise 5: Hypothesis Testing Using T-Distribution**

---

**Context:**
This exercise involves conducting hypothesis tests based on a random sample drawn from an approximately normal population with an unknown standard deviation. The task is to determine the p-value for each scenario described, and visually represent this by drawing a t-curve and shading the region corresponding to the p-value.

**Instructions:**
For each set of hypotheses, sample size, and T-statistic given below, follow these steps:
1. Determine the p-value.
2. Draw a t-distribution curve.
3. Shade the region under the curve that corresponds to the p-value.

Note: Since precise p-values cannot always be determined using t-tables, providing a range suffices.

---

**Scenarios:**

(a) **Hypothesis:** \( H_A : \mu > 0.5 \)  
   **Sample Size:** \( n = 26 \)  
   **T-Statistic:** \( T = 2.6 \)

(b) **Hypothesis:** \( H_A : \mu \neq 0.5 \)  
   **Sample Size:** \( n = 26 \)  
   **T-Statistic:** \( T = 2.6 \)

(c) **Hypothesis:** \( H_A : \mu < 3 \)  
   **Sample Size:** \( n = 18 \)  
   **T-Statistic:** \( T = -2.2 \)

(d) **Hypothesis:** \( H_A : \mu < 3 \)  
   **Sample Size:** \( n = 18 \)  
   **T-Statistic:** \( T = 2.2 \)

---

**Graphical Explanation:**
For each scenario, the following should be depicted:

1. **T-Curve:**
   - The curve is symmetrical around zero and represents the t-distribution specific to the degrees of freedom corresponding to each sample size.

2. **Shaded Region:**
   - For a one-tailed test (as in cases (a) and (c)), shade the area in the direction of the alternative hypothesis.
   - For a two-tailed test (as in case (b)), shade both tails of the distribution.
   - The area shaded represents the probability related to the calculated T-statistic.

---

Using this setup, visually and analytically interpret each scenario to gain insight into the hypothesis testing framework using the t-distribution.
Transcribed Image Text:**Exercise 5: Hypothesis Testing Using T-Distribution** --- **Context:** This exercise involves conducting hypothesis tests based on a random sample drawn from an approximately normal population with an unknown standard deviation. The task is to determine the p-value for each scenario described, and visually represent this by drawing a t-curve and shading the region corresponding to the p-value. **Instructions:** For each set of hypotheses, sample size, and T-statistic given below, follow these steps: 1. Determine the p-value. 2. Draw a t-distribution curve. 3. Shade the region under the curve that corresponds to the p-value. Note: Since precise p-values cannot always be determined using t-tables, providing a range suffices. --- **Scenarios:** (a) **Hypothesis:** \( H_A : \mu > 0.5 \) **Sample Size:** \( n = 26 \) **T-Statistic:** \( T = 2.6 \) (b) **Hypothesis:** \( H_A : \mu \neq 0.5 \) **Sample Size:** \( n = 26 \) **T-Statistic:** \( T = 2.6 \) (c) **Hypothesis:** \( H_A : \mu < 3 \) **Sample Size:** \( n = 18 \) **T-Statistic:** \( T = -2.2 \) (d) **Hypothesis:** \( H_A : \mu < 3 \) **Sample Size:** \( n = 18 \) **T-Statistic:** \( T = 2.2 \) --- **Graphical Explanation:** For each scenario, the following should be depicted: 1. **T-Curve:** - The curve is symmetrical around zero and represents the t-distribution specific to the degrees of freedom corresponding to each sample size. 2. **Shaded Region:** - For a one-tailed test (as in cases (a) and (c)), shade the area in the direction of the alternative hypothesis. - For a two-tailed test (as in case (b)), shade both tails of the distribution. - The area shaded represents the probability related to the calculated T-statistic. --- Using this setup, visually and analytically interpret each scenario to gain insight into the hypothesis testing framework using the t-distribution.
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