I am unable to obtain the same final answer and wonder if I am calculating a portion incorrectly.  Can someone help me break down the continued equation?

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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I am unable to obtain the same final answer and wonder if I am calculating a portion incorrectly.  Can someone help me break down the continued equation?

The given image depicts a mathematical equation, specifically a statistical formula used in hypothesis testing. Here is the transcription:

\[
\frac{(149.28 - 212.163) - (0)}{\sqrt{\frac{185.894^2}{853} + \frac{190.58^2}{821}}} = -6.831
\]

Explanation:

This might be an example of computing a test statistic for a hypothesis test, such as a t-test in statistics. Let's break down the components:

1. Numerator: \((149.28 - 212.163) - (0)\)
   - This represents the difference between two sample means (149.28 and 212.163), adjusted by the hypothesized difference (0 in this case).

2. Denominator: \(\sqrt{\frac{185.894^2}{853} + \frac{190.58^2}{821}}\)
   - This represents the standard error of the difference between the two means. 
   
   - \(185.894\) and \(190.58\) are standard deviations of the two samples.
   
   - \(853\) and \(821\) are the sample sizes.

3. The result of the equation is \(-6.831\), which is the value of the test statistic.

This test statistic can then be compared against a critical value from a t-distribution to determine whether to reject the null hypothesis. In this case, the test statistic is \(-6.831\), which would correspond to a very low p-value, indicating strong evidence against the null hypothesis if the p-value falls below a chosen significance level (e.g., 0.05).
Transcribed Image Text:The given image depicts a mathematical equation, specifically a statistical formula used in hypothesis testing. Here is the transcription: \[ \frac{(149.28 - 212.163) - (0)}{\sqrt{\frac{185.894^2}{853} + \frac{190.58^2}{821}}} = -6.831 \] Explanation: This might be an example of computing a test statistic for a hypothesis test, such as a t-test in statistics. Let's break down the components: 1. Numerator: \((149.28 - 212.163) - (0)\) - This represents the difference between two sample means (149.28 and 212.163), adjusted by the hypothesized difference (0 in this case). 2. Denominator: \(\sqrt{\frac{185.894^2}{853} + \frac{190.58^2}{821}}\) - This represents the standard error of the difference between the two means. - \(185.894\) and \(190.58\) are standard deviations of the two samples. - \(853\) and \(821\) are the sample sizes. 3. The result of the equation is \(-6.831\), which is the value of the test statistic. This test statistic can then be compared against a critical value from a t-distribution to determine whether to reject the null hypothesis. In this case, the test statistic is \(-6.831\), which would correspond to a very low p-value, indicating strong evidence against the null hypothesis if the p-value falls below a chosen significance level (e.g., 0.05).
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