Coyne and Messina: significance versus practical value

The paper has two halves that require different skills and are worth different things. The first is mechanical: fill in the assessment table by matching each statistic the authors used against the chart, checking data type, sample size and the kind of research question the statistic can answer. The second is the argument the assignment is really about, which is whether a statistically significant finding is a useful one. Most submissions do the table competently and then treat the significance discussion as a closing paragraph, which inverts the weight. Complete the table first because it is quick, then spend the majority of your words on the second half, using the table as your evidence. The table tells you what the authors could conclude; the discussion says whether anyone should act on it, and that is the harder and better-marked question. Allocate the word count deliberately before you draft, because 1,250 words is not much for both halves.

Matching statistics to the chart is more than a lookup and rewards attention to the constraints. The chart pairs each statistic with a data type, a sample size condition and a research question. A correlation coefficient requires interval or ratio data and answers what the relationship is between two variables; it does not establish direction or cause, which is the misreading most likely to appear in a study relating satisfaction to admissions. Regression answers how much of the change in an outcome is predicted by one or more predictors, and needs a larger sample. A t-test compares two groups, an analysis of variance compares more. When you assess appropriateness, check three things for each: whether the data type matches, whether the sample supports it, and whether the question the authors asked is the question that statistic answers. The third is where genuinely inappropriate choices show up.

The assignment says plainly that there were three errors in Table 4 on page 185 and asks whether you found them, which is an invitation to read the table rather than the abstract. Approach it systematically instead of hunting. Check whether reported significance markers match the stated p values, whether the numbers in a row are internally consistent, whether totals sum correctly, whether degrees of freedom fit the stated sample, and whether a coefficient's sign matches the direction described in the text. Report what you find and how you found it, and if you locate only two, say so honestly and say what you checked; a paper that documents its method and finds two is worth more than one that vaguely claims all three. Refer to the discussion on pages 189 to 190 as the prompt directs, since that commentary is part of what you are assessing.

The significance against usefulness discussion has a real structure and should not become a list of caveats. Statistical significance is a statement about the probability of the observed data under a null hypothesis, and it depends heavily on sample size: with a large enough sample, trivially small differences become significant. Effect size is what tells you how large the difference is, and confidence intervals tell you how precisely it has been estimated. Pragmatic usefulness adds a further question the statistics cannot answer at all, which is whether the size of the effect justifies the cost of acting on it. A significant association between satisfaction scores and admissions may be too small to change any management decision, and a non-significant finding in an underpowered study is not evidence of no effect. Say which of these applies here. Say which of the statistics in the table would survive that scrutiny and which would not.

On execution, keep the paper anchored in this study rather than drifting into a general essay about p values, because the prompt names the article, the page range and the module chart. Use the chart as your stated criterion so the assessment is checkable, and quote figures from the study accurately with page references. No abstract is required. The assignment uses a rubric and goes to LopesWrite, so paraphrase properly and keep direct quotation minimal, particularly from the results section where it is tempting. Follow APA style as the Style Guide directs. Close by saying what you would want to know before acting on the study's findings, which is the practical form of the pragmatic usefulness question and a stronger ending than a summary. Keep the direct quotation to figures and short phrases, since the results section is where similarity scores climb fastest. Say plainly what would have to be true for a manager to act on this study.