The test statistic of z-2.13 is obtained when testing the claim that p <0.15. a. Using a significance level of a= 0.01, find the critical value(s). b. Should we reject Ho or should we fail to reject Ho? Click here to view.page 1 of the standard normal distribution table Click here to view page 2 of the standard normal.distribution table. a. The critical value(s) is/are z (Round to two decimal places as needed. Use a comma to separate answers as needed.)

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The test statistic of \( z = -2.13 \) is obtained when testing the claim that \( p < 0.15 \).

a. Using a significance level of \( \alpha = 0.01 \), find the critical value(s).

b. Should we reject \( H_0 \) or should we fail to reject \( H_0 \)?

[Click here to view page 1 of the standard normal distribution table.](#)  
[Click here to view page 2 of the standard normal distribution table.](#)

a. The critical value(s) is/are \( z = \) [_______]  
(Round to two decimal places as needed. Use a comma to separate answers as needed.)

---

**Graph/Diagram Explanation:**

*Standard Normal Distribution Table (Page 1)*

- Title: **NEGATIVE z Scores**
- There is a small graph illustrating a standard normal distribution curve with negative z-scores highlighted on the left side.
- The table displays cumulative areas (probabilities) from the left for various negative z-scores.
- Each row represents a different z-score, starting from -2.7 and decreasing.
- The columns represent the second decimal point of the z-score from .00 to .09.

For example, the cell corresponding to \( z = -2.1 \) and .03 gives the cumulative probability for \( z = -2.13 \).
Transcribed Image Text:**Text from Educational Website** The test statistic of \( z = -2.13 \) is obtained when testing the claim that \( p < 0.15 \). a. Using a significance level of \( \alpha = 0.01 \), find the critical value(s). b. Should we reject \( H_0 \) or should we fail to reject \( H_0 \)? [Click here to view page 1 of the standard normal distribution table.](#) [Click here to view page 2 of the standard normal distribution table.](#) a. The critical value(s) is/are \( z = \) [_______] (Round to two decimal places as needed. Use a comma to separate answers as needed.) --- **Graph/Diagram Explanation:** *Standard Normal Distribution Table (Page 1)* - Title: **NEGATIVE z Scores** - There is a small graph illustrating a standard normal distribution curve with negative z-scores highlighted on the left side. - The table displays cumulative areas (probabilities) from the left for various negative z-scores. - Each row represents a different z-score, starting from -2.7 and decreasing. - The columns represent the second decimal point of the z-score from .00 to .09. For example, the cell corresponding to \( z = -2.1 \) and .03 gives the cumulative probability for \( z = -2.13 \).
# Standard Normal Distribution Table (Page 2)

This page provides a standard normal distribution table specifically for positive z-scores. The table shows the cumulative area from the left under the standard normal curve for various z-scores, which helps in finding probabilities in statistics.

## Diagram

At the top of the page, there's a diagram of a standard normal distribution curve. This symmetrical bell-shaped curve is centered at 0, with labels indicating the z-score position to the right of zero. This signifies the distribution of data under the standard normal curve.

## Table Explanation

The table is titled "Standard Normal (z) Distribution: Cumulative Area from the LEFT." It lists z-scores in increments of 0.01, ranging from 0.0 to 0.08 across the columns.

Each row corresponds to a specific z-score value, ranging from 0.0 to 0.8, increasing by increments of 0.1.

### Cumulative Areas:

- **z = 0.0** to **z = 0.09**:
  - The table columns from ".00" to ".09" show the cumulative probabilities for z-scores starting from 0.000 to 0.099.
  
For example, a z-score of 0.05 has a cumulative area of 0.5199, indicating that approximately 51.99% of the data falls to the left of this score.

### Examples:

- **z = 0.1**:
  - .00 | 0.5398
  - .01 | 0.5438
  - .02 | 0.5478
  - ... 
  - .09 | 0.5753

- **z = 0.3**:
  - .00 | 0.6179
  - .01 | 0.6217
  - .02 | 0.6255
  - ...
  - .09 | 0.6517

This table is a crucial tool in statistics for finding probabilities and is commonly used in hypothesis testing and confidence interval estimation.
Transcribed Image Text:# Standard Normal Distribution Table (Page 2) This page provides a standard normal distribution table specifically for positive z-scores. The table shows the cumulative area from the left under the standard normal curve for various z-scores, which helps in finding probabilities in statistics. ## Diagram At the top of the page, there's a diagram of a standard normal distribution curve. This symmetrical bell-shaped curve is centered at 0, with labels indicating the z-score position to the right of zero. This signifies the distribution of data under the standard normal curve. ## Table Explanation The table is titled "Standard Normal (z) Distribution: Cumulative Area from the LEFT." It lists z-scores in increments of 0.01, ranging from 0.0 to 0.08 across the columns. Each row corresponds to a specific z-score value, ranging from 0.0 to 0.8, increasing by increments of 0.1. ### Cumulative Areas: - **z = 0.0** to **z = 0.09**: - The table columns from ".00" to ".09" show the cumulative probabilities for z-scores starting from 0.000 to 0.099. For example, a z-score of 0.05 has a cumulative area of 0.5199, indicating that approximately 51.99% of the data falls to the left of this score. ### Examples: - **z = 0.1**: - .00 | 0.5398 - .01 | 0.5438 - .02 | 0.5478 - ... - .09 | 0.5753 - **z = 0.3**: - .00 | 0.6179 - .01 | 0.6217 - .02 | 0.6255 - ... - .09 | 0.6517 This table is a crucial tool in statistics for finding probabilities and is commonly used in hypothesis testing and confidence interval estimation.
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