PSY 520 - 3-1 Short Paper One - Statistical Significance

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Nov 24, 2024

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1 3-1 Short Paper One: Statistical Significance Tyeshia Gantt Southern New Hampshire University

2 Description of Statistical Significance A hypothetical research article that compared memory test performance between two groups of participants: participants who consumed caffeine before the test and participants who didn’t consume caffeine showed results that proved a significant difference between the two groups. The results showed that the participants who consumed caffeine performed worse than the participants who didn’t consume caffeine.  Caffeinated Group : (M = 7.64, SD = 2.41)  Non-Caffeinated Group : (M = 9.81, SD = 3.16), t(97) = 2.14, p < .05 “Statistical significance helps quantify whether a result is likely due to chance or to some factor of interest” (Gallo, 2016). The individual conducting the test collected enough data to determine the relationship, reject the null hypothesis, and accept the alternative hypothesis to confidently state the results were statistically significant. “If the absolute value of your correlation coefficient is above .381, you reject your null hypothesis (there is no relationship) and accept the alternative hypothesis: There is a statistically significant relationship. If the absolute value of your correlation coefficient were less than .381, you would fail to reject your null hypotheses: There is not a statistically significant relationship” (Siegle, 2015). Explanation of P Value A p-value or probability value is a number that describes the likelihood of data occurring by random chance. A lower p-value suggests that the data is inconsistent with the null hypothesis and favors the alternative hypothesis. “A p-value less than or equal to a predetermined significance level (often 0.05 or 0.01) indicates a statistically significant result, meaning the observed data provide strong evidence against the null hypothesis. This suggests the effect under

3 study likely represents a real relationship rather than just random chance” (Mcleod, 2023). A p- value doesn't necessarily tell if a null hypothesis is true or false, however, it does let you know how likely you would see the collected data if the null hypothesis were true.

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4 References Gallo, A. (2016). A Refresher on Statistical Significance. Harvard Business Review. Retrieved from https://hbr.org/2016/02/a-refresher-on-statistical-significance Mcleod, S. (2023). P-values and statistical significance. Simply Psychology. Retrieved from https://www.simplypsychology.org/p-value.html Siegle, D. (2015). Statistical Significance | Educational Research Basics by Del Siegle. Retrieved from https://researchbasics.education.uconn.edu/statistical_significance/#

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