How would you interpret the results of the ANOVA?

Post a total of 3 substantive separate responses This includes your initial post and 2 replies to other students.

Respond to the following in a minimum of 175 words:

· How would you interpret the results of the ANOVA?

· What does the p value tell you?

· The results mention df. What does that term represent? How is it calculated? Write a plainly stated sentence that explains what these results tell you about the groups.

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Respond to the following in a minimum of 125 words:

Ana Hall

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ANOVA which also stands for the analysis of variances which is a statistical method that is used to test differences between one or two means. “ There are four main assumptions of ANOVA which are the expected values of the errors are zero, the variances of all the errors are, equal to each other, the errors are independent, and they are normally distributed” (Mila, 2018). To interpret the results of ANOVA there are certain steps that you should follow which is to determine if the difference in the means are correct, examine the group means and compare them and also to make sure the model fits the analysis of the data. The p value is used in hypothesis testing to support the null hypothesis and used as evidence as well which means the smaller the p value the greater the evidence for the hypothesis. The DF in statistics means the degree of freedom which means the measure of the number of independent pieces of information. “Degrees of freedom becomes a little more complicated in ANOVA tests. Instead of a simple parameter (like finding a mean), ANOVA tests involve comparing known means in sets of data” (Mila, 2018).

Mila, L. 2018 How to Interpret Results Using ANOVA Test Retrieved by: https://www.educba.com/interpreting-results-using-anova/

Respond to the following in a minimum of 125 words:

RESPOND TO THE CLASSMATE BELOW

Matin Campbell

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To interpret the results of an ANOVA you have to distinguish the difference amonst the group mean, then you would examine, and compare the group, and how it will work into your data. Determine if the model fits the assumption of the analysis. ANOVA test general differences instead of specific differences among the mean (Walker, H. M. (April 1940). It compares the response variable mean at different level factors. The four main assumption are expected values of the error are zero, the variance of those errors are = to each other, they are independent, and distributed normally. The P-value helps to distinguish the significance of the result. It is a number from 0 to 1. A small p-value_< 0.05 that gives strong evidence against the null hypothesis, so it can be rejected. Df stands for the degree of freedom, the number of independent value that can vary in an analysis without breaking constraints. Results using these statistics lets you how many components need to be known before the vector is fully determined.

 Walker, H. M. (April 1940). “Degrees of Freedom” (PDF). Journal of Educational Psychology31 (4): 253–269.

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