### Two-Sample Test of Proportions#### OverviewThis Stata output represents a two-sample test of proportions. The test compares two groups (x and y) to determine if there is a significant difference between their proportions.#### Missing Values Needed- **A:** Standard Error for x- **B:** Confidence Interval for x- **C:** Mean for y- **D:** z-value- **E:** Pr(Z < z) for Ha: diff < 0- **F:** Pr(|Z| < |z|) for Ha: diff != 0- **G:** Pr(Z > z) for Ha: diff > 0#### Input Values- **x:** - Number of observations = 132 - Mean = 0.45 - Std. Err. = A - 90% Conf. Interval = B - **y:** - Number of observations = 125 - Mean = C - Std. Err. = 0.0444972- **diff** (Difference in proportions x - y): - Mean = -0.1 - Std. Err. = 0.0620886 - z = D - 90% Conf. Interval from -0.2021267 to 0.0021267#### Hypothesis Tests- **Null Hypothesis (Ho):** diff = 0- **Alternative Hypotheses (Ha):** - diff < 0: Pr(Z < z) = E - diff != 0: Pr(|Z| < |z|) = F - diff > 0: Pr(Z > z) = G#### InterpretationThe data requires the calculation of missing values A-G to complete the analysis. With these values, you can determine the statistical significance and interpret the results of the test to understand if the two sample proportions are significantly different.

Given information: Variable Mean Std. Errr. z P > |z| 90% Conf. Interval x 0.45 A B y…

Answered: Calculate the Missing values in the…

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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In 1908, William Gosset published the article "The probable Error of a Mean" under the pseudonym of "Student". He included the data listed below for two different types of corn seed that were used on ad jacent plots of land. The listed values are the yields of head corn in pounds per acre. Use a 0.10 significance level to test the claim that the mean difference in yield between the two types of seed is 0. Regular 1903 1935 1910 2496 2108 1980 2060 1444 1612 1316 1511 Kiln dried 2009 1915 2011 2463 2180 1925 2122 1482 1542 1443 1535 a. Define the parameter A. mu Subscript d Baseline equals Mean of (Regular yield - Kiln dried yield) B. mu Subscript d Baseline equals Mean of the Regular yield C. mu Subscript d Baseline equals Mean of the Kiln dried yield D. mu equals Mean yield b. State the null and alternative hypotheses…
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5.
Use the output below to determine if there is a significant difference in the hour spent emailing between the two group if T0 =0.290
What percentage of scores should fall within ±1 SD for TADHD? Choices: 1. A higher percentage of scores than fell within ±1 SD for ADHD 2. A lower percentage of scores than fell within ±1 SD for ADHD 3. The same percentage of scores that fell within ±1 SD for ADHD What is true of a score of 65.55 for TADHD? Choices: 1. It falls within –1.5 SD of the mean and is thus unlikely to be due to chance 2. It falls within 1.5 SD of the mean and is thus unlikely to be due to chance 3. It falls outside –1.5 SD of the mean but is likely to be due to chance 4. It falls outside 1.5 SD of the mean but is likely to be due to chance

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