What if a significance level of 0.01 was used instead? Would your decision and conclusion change? State the decision and conclusion based on this new significance level in two complete sentences. **One Sample Proportion Hypothesis Test:****Outcomes in: Black Friday Shopping**- **Successes**: 357- **p**: Proportion of successes- **H₀**: p = 0.69- **Hₐ**: p ≠ 0.69**Hypothesis Test Results:**| Variable | Count | Total | Sample Prop. | Std. Err. | Z-Stat | P-value ||-----------------------|-------|-------|--------------|-------------|-----------|----------|| Black Friday Shopping | 0 | 550 | 0 | 0.019720778 | -34.988477| <0.0001 |**Explanation:**This table demonstrates the results of a one-sample proportion hypothesis test. The hypothesis test is designed to assess whether the proportion of successes in Black Friday shopping is significantly different from 0.69.**Details:**1. **Count**: Number of observed successes (here shown as 0, which appears to be an error given the context earlier stated as 357).2. **Total**: Total number of observations (550).3. **Sample Prop.**: Sample proportion, calculated as the ratio of successes to total observations (currently shown as 0).4. **Std. Err. (Standard Error)**: The standard deviation of the sampling distribution, which quantifies the uncertainty in the sample proportion (0.019720778 here).5. **Z-Stat (Z-Statistic)**: A statistical measure that describes the position of the sample proportion relative to the hypothesized population proportion, standardizing by expected variability (-34.988477).6. **P-value**: Indicates the probability of obtaining a test statistic as extreme or more extreme than the observed one, assuming the null hypothesis is true (less than 0.0001 indicates strong evidence against the null hypothesis). The result suggests the sample proportion is significantly different from the hypothesized proportion of 0.69.

ne sample proportion hypothesis test: atcomes in: Black Friday Shopping ccess : 357 Proportion of successes · :p= 0.69 :p#0.69 vpothesis test results: Variable Count Total Sample Prop. Std. Err. Z-Stat P-value Black Friday Shopping 550 0.019720778| -34.988477| <0.0001

ne sample proportion hypothesis test: atcomes in: Black Friday Shopping ccess : 357 Proportion of successes · :p= 0.69 :p#0.69 vpothesis test results: Variable Count Total Sample Prop. Std. Err. Z-Stat P-value Black Friday Shopping 550 0.019720778| -34.988477| <0.0001

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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Question

What if a significance level of 0.01 was used instead? Would your decision and conclusion change? State the decision and conclusion based on this new significance level in two complete sentences.

**One Sample Proportion Hypothesis Test:**

**Outcomes in: Black Friday Shopping**

- **Successes**: 357
- **p**: Proportion of successes
- **H₀**: p = 0.69
- **Hₐ**: p ≠ 0.69

**Hypothesis Test Results:**

| Variable | Count | Total | Sample Prop. | Std. Err. | Z-Stat | P-value |
|-----------------------|-------|-------|--------------|-------------|-----------|----------|
| Black Friday Shopping | 0 | 550 | 0 | 0.019720778 | -34.988477| <0.0001 |

**Explanation:**

This table demonstrates the results of a one-sample proportion hypothesis test. The hypothesis test is designed to assess whether the proportion of successes in Black Friday shopping is significantly different from 0.69.

**Details:**

1. **Count**: Number of observed successes (here shown as 0, which appears to be an error given the context earlier stated as 357).
2. **Total**: Total number of observations (550).
3. **Sample Prop.**: Sample proportion, calculated as the ratio of successes to total observations (currently shown as 0).
4. **Std. Err. (Standard Error)**: The standard deviation of the sampling distribution, which quantifies the uncertainty in the sample proportion (0.019720778 here).
5. **Z-Stat (Z-Statistic)**: A statistical measure that describes the position of the sample proportion relative to the hypothesized population proportion, standardizing by expected variability (-34.988477).
6. **P-value**: Indicates the probability of obtaining a test statistic as extreme or more extreme than the observed one, assuming the null hypothesis is true (less than 0.0001 indicates strong evidence against the null hypothesis).

The result suggests the sample proportion is significantly different from the hypothesized proportion of 0.69.

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