{"id":111,"date":"2024-08-21T12:03:58","date_gmt":"2024-08-21T12:03:58","guid":{"rendered":"http:\/\/localhost\/researchmethods\/?post_type=content&p=111"},"modified":"2024-09-12T14:46:38","modified_gmt":"2024-09-12T14:46:38","slug":"chapter-19-correlation","status":"publish","type":"content","link":"https:\/\/staging.routledgelearning.com\/researchmethods\/student-resources\/chapter-19-correlation\/","title":{"rendered":"Chapter 19 – Correlation"},"content":{"rendered":"\n
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\n\tHome<\/a>\n<\/span>\u203a<\/span>\n\tStudent Resources<\/a>\n<\/span>\u203a<\/span>\n\tChapter 19 \u2013 Correlation\n<\/span><\/div>\n\n

Chapter 19 – Correlation<\/h1>\n\n\n

This chapter explores positive and negative correlations.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Exercises<\/h2>\n\n\n\n

Exercise 19.1<\/h3>\n\n\n\n

Scatter plots<\/strong><\/p>\n\n\n\n

Have a look at the scatter plots below and select a description in terms of strength (weak, moderate, strong) and direction (positive, negative or curvilinear).<\/p>\n\n\n\n

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Figure 18.1.1<\/strong><\/figcaption><\/figure>\n\n\n\n
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Figure 18.1.2<\/strong><\/figcaption><\/figure>\n\n\n\n
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Figure 18.1.3<\/strong><\/figcaption><\/figure>\n\n\n\n
Show answer<\/summary>\n

Figure 1: strong, positive<\/strong><\/strong><\/p>\n\n\n\n

Figure 2: moderate, negative<\/strong><\/strong><\/p>\n\n\n\n

Figure 3: strong, curvilinear<\/strong><\/strong><\/p>\n<\/details>\n\n\n\n

Exercise 19.2<\/h3>\n\n\n\n

Calculating Pearson\u2019s and Spearman\u2019s correlations<\/strong><\/p>\n\n\n\n

You\u2019ll need one of these data sets for this exercise<\/p>\n\n\n\n

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Download – Correlation data sets<\/strong><\/a><\/div>\n<\/div>\n\n\n\n

The data set in the file correlation.sav (SPSS) or correlation.xls (Excel) is for you to use to calculate Pearson\u2019s r<\/em> and Spearman\u2019s r<\/em>  (two-tailed) either by hand or using SPSS or a spreadsheet programme. Copy the table below and enter, using either p<\/em> = or p<\/em> \u2264. Don\u2019t worry if your answer is out by a small amount as this might be due to rounding errors.<\/p>\n\n\n\n

Pearson\u2019s r<\/em>  = <\/td> <\/td>p<\/em> =<\/td>p <\/em>\u2264<\/td><\/tr>
Spearman\u2019s r =<\/em><\/td> <\/td>p<\/em> =<\/td>p <\/em>\u2264<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Show answer<\/summary>\n
Pearson\u2019s r<\/em>  = <\/td> -.48<\/td>p<\/em> = 0.005<\/td>p <\/em>\u22640.01<\/td><\/tr>
Spearman\u2019s r<\/em> =<\/td> -.492<\/td>p<\/em> = 0.004<\/td>p <\/em>\u22640.01<\/td><\/tr><\/tbody><\/table><\/figure>\n<\/details>\n\n\n\n

Exercise 19.3<\/h3>\n\n\n\n

A few questions on correlation<\/strong><\/p>\n\n\n\n

1. Jarrod wants to correlate scores on a general health questionnaire with the subject that students have chosen for their first degree. Why can\u2019t he?<\/p>\n\n\n\n

Show answer<\/summary>\n

First degree choice is a categorical variable.<\/p>\n<\/details>\n\n\n\n

2. Amy wants to correlate people\u2019s scores on an anxiety questionnaire with their status \u2013 married or not married. Can she?<\/p>\n\n\n\n

Show answer<\/summary>\n

Yes, she can use the point biserial correlation coefficient (though better to conduct a difference test e.g., unrelated t<\/em>).<\/p>\n<\/details>\n\n\n\n

3. As the number in a sample increases the critical value required for a significant correlation with p<\/em> \u2264 .05 increases or decreases?<\/p>\n\n\n\n

Show answer<\/summary>\n

Decreases.<\/p>\n<\/details>\n\n\n\n

In the first set of exercises for this chapter, question 2 asks you to draw the scatterplot for the maths and music data in Table 19.5. Here is a possible answer:<\/p>\n\n\n\n

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Figure 19.3.1<\/strong><\/figcaption><\/figure>\n\n\n\n

The maths and music score scatterplot \u2013 answer to exercise in Chapter 19.<\/p>\n\n\n\n

Exercise 19.4<\/h3>\n\n\n\n

Have a go at this short quiz to test your understanding of correlation and identify any gaps in your knowledge.<\/p>\n\n\n\n

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