Original Claim: Fewer than 90% of adults have a cell phone. This is a claim about a population proportion so a normal distribution is assumed. The claim undergoes a hypothesis test using a significance level of α = 0.05. The P-value based on sample data is calculated to be 0.0003.State the null hypothesis (H0).State the alternative hypothesis (H1).What kind of test would this be, a two-tailed, a left-tailed, or a right-tailed?Sketch a normal distribution curve and highlight the region of significance (also called critical region or rejection region).On your graph, next highlight the P-value. (The P-value means that there is a 0.03% chance that your results could be random or happen by chance).State a conclusion about the null hypothesis. (Reject H0 or fail to reject H0.)Without using technical terms or symbols, state a final conclusion that addresses the original claim, i.e., fewer than 90% of adults have a cell phone.Now we will test this hypothesis using the critical value method. The z statistic is most relevant to this test. Using the z-score tables at the back of the textbook, find the z-score for a significance level of α = 0.05. This is the critical value. What is it?Sketch a normal distribution curve, plot the critical value, and highlight the critical or rejection region. (It will look similar to your curve in 2d above).The z test statistic based on sample data is -3.4. Find -3.4 on the z-score table. What is the cumulative area from the LEFT?On your graph, plot the z test statistic.State a conclusion about the null hypothesis. (Reject H0 or fail to reject H0.)

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Description: Original Claim: Fewer than 90% of adults have a cell phone. This is a claim about a population proportion so a normal distribution is assumed. The claim undergoes a hypothesis test using a significance level of α = 0.05. The P-value based on sample d

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Original Claim: Fewer than 90% of adults have a cell phone. This is a claim about a population proportion so a normal distribution is assumed. The claim undergoes a hypothesis test using a significance level of α = 0.05. The P-value based on sample data is calculated to be 0.0003.
1. State the null hypothesis (H0).
2. State the alternative hypothesis (H1).
3. What kind of test would this be, a two-tailed, a left-tailed, or a right-tailed?
4. Sketch a normal distribution curve and highlight the region of significance (also called critical region or rejection region).
5. On your graph, next highlight the P-value. (The P-value means that there is a 0.03% chance that your results could be random or happen by chance).
6. State a conclusion about the null hypothesis. (Reject H0 or fail to reject H0.)
7. Without using technical terms or symbols, state a final conclusion that addresses the original claim, i.e., fewer than 90% of adults have a cell phone.
  
  Now we will test this hypothesis using the critical value method. The z statistic is most relevant to this test.
8. Using the z-score tables at the back of the textbook, find the z-score for a significance level of α = 0.05. This is the critical value. What is it?
9. Sketch a normal distribution curve, plot the critical value, and highlight the critical or rejection region. (It will look similar to your curve in 2d above).
10. The z test statistic based on sample data is -3.4. Find -3.4 on the z-score table. What is the cumulative area from the LEFT?
11. On your graph, plot the z test statistic.
12. State a conclusion about the null hypothesis. (Reject H0 or fail to reject H0.)

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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