Summarize these data with a variety of descriptive statistics that you are learning in your course. In particular, make sure to compute the mean, the variance, and the standard deviation of these scores.<\/p>\n
If you would like some help with computing descriptive statistics by hand, click here<\/a>.<\/p>\n Enter these data into the first column of Stats Homework’s<\/i> data manager and give this variable a descriptive name. Your screen should look like this:<\/p>\n Always double-check<\/u> and save<\/u> your data. To conduct your analysis, pull down the Analyze<\/b> menu and choose Explore Data<\/b>. Here is the user dialog for this procedure:<\/p>\n <\/p>\n Move your variable to the window on the right, select all the optional output, select at least one graph, and click “Compute.”<\/p>\n Trimmed Means<\/strong>.\u00a0 Here we have the means of your sample after trimming the most extreme values from the two tails of your sample.\u00a0 You will see the trimming goals — 10% and 20% — and the actual percentage trimmed from each tail of your sample — 7% and 20%.\u00a0 Finally, you will see the number of scores that were retained to compute the trimmed means.<\/p>\n Supplemental Statistics.<\/strong> These are statistics that can be helpful if you want to double-check your hand-written computations.<\/p>\n The Box Plot<\/strong><\/p>\n Make sure to explore the options for this plot.\u00a0 You can change the plot to a graphical confidence interval, and you can change a variety of features like the scale of the axis, and the title and labels.<\/p>\n Stats Homework<\/i> also includes a procedure for computing just the basic descriptive statistics. This procedure is especially helpful when you need the basic descriptive statistics on a number of variables. Pull down the Analyze<\/b> menu and choose Descriptive Statistics<\/b>. Here is the output screen that is produced:<\/p>\n <\/p>\n <\/p>\n
\n![\"explore6\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2016\/06\/explore6.png\")
<\/a><\/p>\n![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore7.png\")
<\/a><\/p>\nBasic Output<\/h4>\n
![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore9.png\")
<\/a><\/p>\nDescriptive Statistics.<\/strong><\/h4>\n
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Optional Outputs<\/h4>\n
![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore10.png\")
<\/a>\u00a0Confidence Intervals. <\/strong>Each confidence interval uses your sample to make a statement about what the mean of the population of all test scores might be. The first one tells you that with 95% certainty we know that the population mean of all test scores is between 67.28 and 79.38. The second group of confidence intervals include the median.\u00a0 Thus, with 98.7% confidence, we know that the population median is between 68 and 80.<\/p>\n![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore11.png\")
<\/a>Distributional Statistics<\/strong>. \u00a0Shapiro & Wilks’ test for normality: this test compares the shape of your sample distribution to that of the normal distribution. If the p<\/i> value for this test is less than .05, this would suggest that your data are significantly non-normal. Many test statistics assume that your data are normally distributed. So, this test is a way to empirically check the assumption of normality in your data.<\/p>\n![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore12.png\")
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![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore8.png\")
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\nIf You Need Fewer Statistics<\/h3>\n
![\"\"](\"https:\/\/sites.berry.edu\/vbissonnette\/wp-content\/uploads\/sites\/21\/2021\/01\/explore14.png\")
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