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(b) P. – P; = sample statistic p. - Pr- = -0.4 is a possible sample statistic. Five possible p-values are given below. Select the most accurate p-value for the O p-value = 0.832 O p-value = 0.400 O p-value = 0.075 O p-value = 0.14 O p-value = 0.007 eTextbook and Media

(b) P. – P; = sample statistic p. - Pr- = -0.4 is a possible sample statistic. Five possible p-values are given below. Select the most accurate p-value for the O p-value = 0.832 O p-value = 0.400 O p-value = 0.075 O p-value = 0.14 O p-value = 0.007 eTextbook and Media

MATLAB: An Introduction with Applications
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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**Problem (b): Sample Statistic \( \hat{p}_c - \hat{p}_f \)** The expression \( \hat{p}_c - \hat{p}_f = -0.4 \) represents a possible sample statistic. Below, five possible p-values are presented. Your task is to select the most accurate p-value for this sample statistic. **Options:** - \( \text{p-value} = 0.832 \) - \( \text{p-value} = 0.400 \) *(Selected)* - \( \text{p-value} = 0.075 \) - \( \text{p-value} = 0.140 \) - \( \text{p-value} = 0.007 \) To better understand which p-value is most accurate, consider the context of hypothesis testing and the implications of the p-value in assessing the statistical significance of the observed sample statistic.
Transcribed Image Text:**Problem (b): Sample Statistic \( \hat{p}_c - \hat{p}_f \)** The expression \( \hat{p}_c - \hat{p}_f = -0.4 \) represents a possible sample statistic. Below, five possible p-values are presented. Your task is to select the most accurate p-value for this sample statistic. **Options:** - \( \text{p-value} = 0.832 \) - \( \text{p-value} = 0.400 \) *(Selected)* - \( \text{p-value} = 0.075 \) - \( \text{p-value} = 0.140 \) - \( \text{p-value} = 0.007 \) To better understand which p-value is most accurate, consider the context of hypothesis testing and the implications of the p-value in assessing the statistical significance of the observed sample statistic.
**Influencing Voters: Is There a Difference in Effectiveness between a Phone Call and a Flyer?** A study is conducted to investigate which method, a recorded phone call or a flyer, is more effective in persuading voters to vote for a particular candidate. Since in this case, the alternative hypothesis is not specified in a particular direction, the hypotheses are: \( H_0 : p_c = p_f \) vs \( H_a : p_c \neq p_f \). A randomization distribution for \(\hat{p}_c - \hat{p}_f\) using \(n = 1000\) for this test is shown below. **Graph Explanation:** The histogram presented is a graphical representation of the randomization distribution of the difference in proportions \(\hat{p}_c - \hat{p}_f\). The x-axis represents the "Difference" between the proportions, ranging from approximately -0.6 to 0.6. The y-axis represents the "Frequency" of each difference occurring in the randomization test. The histogram shows a symmetrical distribution centered around 0, indicating that there is no significant bias towards one method being more effective than the other under the null hypothesis. The height of each bar represents the frequency of each range of differences observed in 1000 samples.
Transcribed Image Text:**Influencing Voters: Is There a Difference in Effectiveness between a Phone Call and a Flyer?** A study is conducted to investigate which method, a recorded phone call or a flyer, is more effective in persuading voters to vote for a particular candidate. Since in this case, the alternative hypothesis is not specified in a particular direction, the hypotheses are: \( H_0 : p_c = p_f \) vs \( H_a : p_c \neq p_f \). A randomization distribution for \(\hat{p}_c - \hat{p}_f\) using \(n = 1000\) for this test is shown below. **Graph Explanation:** The histogram presented is a graphical representation of the randomization distribution of the difference in proportions \(\hat{p}_c - \hat{p}_f\). The x-axis represents the "Difference" between the proportions, ranging from approximately -0.6 to 0.6. The y-axis represents the "Frequency" of each difference occurring in the randomization test. The histogram shows a symmetrical distribution centered around 0, indicating that there is no significant bias towards one method being more effective than the other under the null hypothesis. The height of each bar represents the frequency of each range of differences observed in 1000 samples.
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