ext Y Calibri ▼ - 12 + B I U A. C ² ㅗㅗㅗㅗ로 State the critical values for a one-sample t test given the following con Two-tailed test, a = .01, n = 20 i. ii. One-tailed test, lower-tail critical, a = .05, df = 19 3 4

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**Title: Determining Critical Values for a One-Sample t-Test**

In this exercise, we will determine the critical values for a one-sample t-test under specific conditions. Understanding the critical values is essential for hypothesis testing and helps determine the statistical significance.

### Conditions:

1. **Two-tailed Test**
   - Significance level (α): 0.01
   - Sample size (n): 20

2. **One-tailed Test (Lower-Tail Critical)**
   - Significance level (α): 0.05
   - Degrees of freedom (df): 19

### Explanation:

- **Two-tailed Test**: This test checks for departures in both directions from the hypothesized value. The significance level is divided between the two tails of the distribution.

- **One-tailed Test (Lower-Tail)**: This test checks for a departure in only one direction. The entire significance level is applied to one tail of the distribution.

For both tests, it is important to use statistical tables or software to find the exact critical values based on the given conditions.
Transcribed Image Text:**Title: Determining Critical Values for a One-Sample t-Test** In this exercise, we will determine the critical values for a one-sample t-test under specific conditions. Understanding the critical values is essential for hypothesis testing and helps determine the statistical significance. ### Conditions: 1. **Two-tailed Test** - Significance level (α): 0.01 - Sample size (n): 20 2. **One-tailed Test (Lower-Tail Critical)** - Significance level (α): 0.05 - Degrees of freedom (df): 19 ### Explanation: - **Two-tailed Test**: This test checks for departures in both directions from the hypothesized value. The significance level is divided between the two tails of the distribution. - **One-tailed Test (Lower-Tail)**: This test checks for a departure in only one direction. The entire significance level is applied to one tail of the distribution. For both tests, it is important to use statistical tables or software to find the exact critical values based on the given conditions.
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