Differences In ANOVA

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Introduction
The ANOVA and the t-test are both similar in that they can tell the difference between groups, however, the major difference is that the ANOVA independent variable can have any number of groups (Sukal, 2013). The question of interest for this mini-research proposal using the one-way ANOVA, is the following: Does the frequency in days of the week make a difference in having an ideal body weight? The one-way ANOVA is the most appropriate statistical test as the question identifies an independent variable that can have up to a maximum of 7 groups, to represent the days of the week. The statistical notation is the following:
F =
MSbet
MSwith (Sukal, 2013, Formula 6.4) The null hypothesis would be the following: The frequency in the days of the week does not make a difference in ideal body weight. The alternative hypothesis would be, that indeed, the frequency in days of the week does make a difference in ideal body weight. The types of errors that can occur
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When an F is large that it indicates that the difference between at least two of the groups in the analysis is not random and that there is a significant difference (Sukal, 2013). On the other hand, if an F is small then it indicates that the independent variable did not have enough of an impact (Sukal, 2013). Therefore, by using the before mentioned statistical test, to determine the F ratio, this writer would be able to tell whether if there is a variance that can be explained by the independent variable on the dependent variable (Sukal, 2013). The interesting thing about the one-way ANOVA is that the formula for the sum of squares can indicate the difference between the groups, within the groups, and the difference between the individual scores and the mean (Sukal, 2013). The statistical test mentioned is appropriate as it would be able to indicate a discrepancy or difference amongst the

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