# Week-5-DQ-1-Response-to-classmate-Catherine-Sidoti

In an analysis of personality traits and the positive/negative meaning of life in adults a one way ANOVA was calculated in order to examine whether the sub-dimensions of meaning in life differed among age groups, this was conducted in more than 2 age groups (Isik & Ãœzbe 2015). In Maryâ€™s experiment, if there are greater than 2 independent variables, an ANOVA would be utilized, for example there could be one variable with noise, no noise and another factor with ambient music as a 3rd. In Maryâ€™s experiment, this is when an ANOVA should be utilized; the dependent variable is how much time it takes for the 6th graders score on a math lesson in each of the conditions. Each subject could have a score at the end that would function as a continuous variable if the variable was scaled in increments of time or such as the amount of time required for each participant to answer the math questions.

The one way ANOVA must have the following data requirements, continuous DVs, IV is categorical such as greater than 2 groups, cases that have values on both the DV and the IV, independent samples/groups such as independent of observation such as there is no relationship between the subjects in each sample which means that the subjects in the first group canâ€™t be in the second group and that they cannot influence subjects in the other group. The sample must be random, the distribution must be normal; homogeneity of variance must exist. When this assumption is violated and sample sizes differ among groups, the p value for the overall F test is cannot be trusted and there should not be any outliers. If the normality and homogeneity of variance assumptions for the one way ANOVA are not met, a nonparametric test can be run such as the Kruskal-Wallis. The following heuristic can be utilized each group should have at least 6 participants; an unbalanced design increases the possibility of violating assumptions which threatens ANOVA F test validity (Kent State University, 2017).

The one-way ANOVA compares the means between the groups being examined by further investigating whether the means are statistically significant from each other. Testing for the null hypothesis applies the following formula: where Âµ = group mean and k = number of groups. If the one-way ANOVA concludes a statistically significant result, the alternative hypothesis (HA) is accepted, which is that there are at least two group means that are statistically significantly different from each other (Lund & Lund, 2013).

Response to the above question using 150-250 words and please use at least 1 reference. Please ensure there is also a reference page at the end and that the reference page is formatted in APA 6th edition format. Please also ensure that reference is listed in response properly.