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INF397C Introduction to Research in Information Studies Spring, 2009 Day 13

INF397C Introduction to Research in Information Studies Spring, 2009 Day 13. Correlation. With correlation, we return to DESCRIPTIVE statistics. (This is counterintuitive. To me.) (Well, it’s BOTH descriptive and inferential.)

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INF397C Introduction to Research in Information Studies Spring, 2009 Day 13

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  1. INF397CIntroduction to Research in Information StudiesSpring, 2009Day 13

  2. Correlation • With correlation, we return to DESCRIPTIVE statistics. (This is counterintuitive. To me.) (Well, it’s BOTH descriptive and inferential.) • We are describing the strength and direction of the relationship between two variables. • And how much one variable predicts the other.

  3. Correlation • Formula – • Hinton, p. 259, or • S, Z, & Z, p. 393 • Two key points: • How much predictability does one variable provide, for another. • NOT causation.

  4. Correlation (cont’d.) • Go to the McGraw-Hill statistics primer http://highered.mcgraw-hill.com/sites/0072494468/student_view0/statistics_primer.html and click on “Correlational Statistics.” Read the three sub-sections. I will NOT ask you to calculate a correlation, but I want you to understand the concepts surrounding it.

  5. Chi-square • Hinton, p. 247

  6. Chi square test • Let’s work an example. • Just know that you use the chi square test when you have FREQUENCY data.

  7. Let’s talk about the final • Here’s what you’ve read: • Huff (How to lie with statistics) • Dethier (To know a fly) • Hinton: Ch. 1 – 15, 20 • S, Z, & Z: Ch. 1-8, 10-13 • Several other articles

  8. For the final, EMPHASIZE… • Descriptive stat • Measures of central tendency, dispersion • Z scores • Probability • Frequency distributions, tables, graphs • Correlation (interpret, not calculate) • Inferential stat • Hypothesis testing • Standard error of the mean • t test (calculate one, for one sample; interpret others) • Confidence intervals (interpret, not calculate) • Chi square (interpret, not calculate) • ANOVA – interpret summary table • Type I and II errors

  9. Emphasize . . . • Experimental design • IV, DV, controls, confounds, counterbalancing • Repeated measures, Independent groups • Sampling • Operational definitions • Individual differences variable • Ethics of human study • Possible sources of bias and error variance and how to minimize/eliminate • Qualitative methods • Per Rice Lively, Gracy • Survey generation (from SZZ, Ch. 5)

  10. De-emphasize • Complicated probability calculations • APA ethical standard (S,Z, & Z, Ch. 3) • Content analysis (SZZ, Ch. 6) • Calculating an ANOVA. • Nonequivalent control group design (SZZ, Ch. 11) (Indeed, de-emphasize all Ch. 11) • Hinton, Ch. 12

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