3p15_ assignment #2

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Feb 20, 2024

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1 CHYS 3P15 Quantitative Research Methods in Child and Youth Dr. Ann Farrell TA: Melissa Blackburn Cadance Humphrys 7133680 Assignment #2

2 Descriptive Statistics: From the data given, the mean or average answer for self-reported scales of likeableness was 4.81. The standard deviation was 1.91. This means that our data is grouped closely to the mean average. The median or middle value for the data received was 4.78. This means that 68% of the data of likeableness scale falls between 2.9 and 6.72. Z-Scores: I assessed the Z-scores for the self-reported scores of likeableness. I determined there were no outliers from the data. I had come to this conclusion because no scores were outside the +/- 3 range. This was done by sorting the Z-scores created from ascending to descending. The highest score was 2.51. The lowest score was -2.37. Normality Testing: I also assessed the normality of the data set looking at the histogram. The skewness value was -0.03. The kurtosis value was -0.18. This falls between the +/- 3 values, this means that this is a normal distribution. These values are in suggested range meaning our data meets the assumption of distribution. The Kolmogorov-Smirnov Test: The Kolmogorov-Smirnov Test of Normality was used in this sample. The null hypothesis being, there is no significant difference between the self-reported likeableness and a normal distribution. The alternative hypothesis being, there is a significant difference between the self-reported likeableness and a normal distribution. From the KS test, p was .200. This would

3 mean we reject the null, and hypothesize that there is a significant difference between the likeableness and a normal distribution. This is because p is greater than 0.05. Conclusion: To conclude, our data set has met the assumption of normality. This is supported because our z-scores were in between the +/- 3 range. Our skewness and kurtosis values were also in the +/- 3 range. As well as our sig value being greater than 0.05. The histogram is also a visual representation of a normal distribution.

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