PSY260_Project_Two

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Psychology

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Dec 6, 2023

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1 Project Two Eivor Raven-Eye Southern New Hampshire University PSY 260: Statistical Applications for the Behavioral and Social Sciences Nathaniel Thomas October 14, 2023

2 Project Two Analysis Report Summary: If someone wanted to discover the average level of agreement among LGBTQIA+ individuals on the right of marriage equality across a large and diverse geographical area in the USA, an inferential test would need to be conducted. A ANOVA test would be used to find this average level of agreement. By using this test, we can compare each geographic location’s meaning to one another. The data collected from the interviews was retrieved using a Likert scale. Those who support or agree with gay marriage scored closer to five on the Likert scale, whereas those who oppose it scored closer to one on the Likert scale. The a (alpha) level of significance equals .05. The four geographical regions of the United States, incorporated into this test, is the West, Midwest, Northeast and the South. The independent variable would be the geographic region, while the dependent variable is the average agreement level to gay marriage. The data concluded that F(9,28fi) = 1.36, P= .225, n2=.02, which measures the effect size used for the analysis of this variance. When the U.S means, for all geographical locations, is combined, the overall mean equals 1.91. By separating these means, the West's mean score is 1.8fi, the Midwest mean score is 1.93, the Northwest mean score equaling 2.16, and the South mean score concluded to be 1.79, meaning the Northwest scored highest, in regard to the mean scores. The p value, along with the alpha value (.225 > .05) shows no statistical significance in the four geographical locations and the varied conclusions about the average agreement of gay marriage. Since the p-value's size is used to reject or fail to reject the null hypothesis, it is concluded that there is not enough evidence (as seen in.225 > .05) to reject the null hypothesis (HO). According to Grimm when conducting an ANOVA it is assumed that the samples represent the general populous of that area. An actionable item for future research would be to sample larger regional populations and to ensure diversity of ages, ethnicities and sub-regional locations in order to provide for greater representation of the populations in each region and increase the significance level of those findings. It could also be beneficial to incorporate religious groups as a subcategory since there is a religious component to positive and negative views on the topic. Output From Data Analysis:

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