1 / 36

Reasoning in Psychology Using Statistics

Reasoning in Psychology Using Statistics. Psychology 138 2018. Exam 2 in lecture and lab on Wednesday Be prepared to do calculations (including square roots) on calculator. Announcements. We ’ d like to say: X causes Y To be able to do this: The causal variable must come first

Download Presentation

Reasoning in Psychology Using Statistics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Reasoning in PsychologyUsing Statistics Psychology 138 2018

  2. Exam 2 in lecture and lab on Wednesday • Be prepared to do calculations (including square roots) on calculator Announcements

  3. We’d like to say: • X causes Y • To be able to do this: • The causal variable must come first • There must be co-variation between the two variables • Need to eliminate plausible alternative explanations Causal claims

  4. - Or sleeping well makes you happy? • We’d like to say: • X causes Y • To be able to do this: • The causal variable must come first • There must be co-variation between the two variables • Need to eliminate plausible alternative explanations • Directionality Problem (temporal precedence): • Happy people sleep well Causal claims

  5. We’d like to say: • X causes Y • To be able to do this: • The causal variable must come first • There must be co-variation between the two variables • Need to eliminate plausible alternative explanations • Third Variable Problem: • - Happy people sleep well • - Or does sleeping well make you happy? • OR something elsemakes people happy and sleep well! • Regular exercise • Minimal use of drugs & alcohol • Being a conscientious person • Being a good relationship Other Variable Causal claims

  6. Coincidence (random co-occurence) • r=0.52 correlation between the number of republicans in US senate and number of sunspots • From Fun with correlations • See also Spurious correlations • We’d like to say: • X causes Y • To be able to do this: • The causal variable must come first • There must be co-variation between the two variables • Need to eliminate plausible alternative explanations Causal claims Correlation is not causation blog posts: Internet’s favorite phrase Why we keep saying it

  7. Descriptive Statistics - Statistical procedures to help organize, summarize & simplify large sets of data • One variable (frequency distribution) • Display results in a frequency distribution table & histogram (or bar chart if categorical variable). • Make a deviations table to get measures of central tendency (mode, median, mean) & variability (range, standard deviation, variance). • Two variables (bivariate distribution) • Display results: Make a scatterplot. • Make a bivariate deviations or z-table table to get Pearson’s r. • Z-scores & normal distribution Review for Exam 2: Descriptive statistics

  8. Are hours sleeping related to GPA? • You conduct a survey. • Your sample of 10 gives these results for average hours per night sleeping: 7, 6, 7, 8, 8, 7, 9, 5, 9, 6 • You also have respondents give their overall GPA: 2.4, 3.9, 3.5, 2.8, 3.0, 2.1, 3.9, 2.9, 3.6, 2.7 • We will focus on sleep results first and then both variables together. • What kind of scales are they? • To find standard deviation, will we use formula for population or sample? Example

  9. Hrs. sleep n=10 7,6,7,8,8 7,9,5,9,6 ∑ 10 1.0 100 Step 1: Frequency distribution & histogram

  10. Hrs. sleep n=10 7,6,7,8,8 7,9,5,9,6 ∑ 10 1.0 100 Will enter first two columns as X and Y axes for frequency distribution Step 1: Frequency distribution & histogram

  11. Hrs. sleep n=10 p = f/n ∑ 10 1.0 100 Step 1: Frequency distribution & histogram

  12. 10 1.0 100 Step 1: Frequency distribution & histogram

  13. 10 1.0 100 Step 1: Frequency distribution & histogram

  14. 10 1.0 100 Step 1: Frequency distribution & histogram

  15. 10 1.0 100 Step 1: Frequency distribution & histogram

  16. 10 1.0 100 Step 1: Frequency distribution & histogram

  17. Hrs. sleep F R E Q U E N C Y SCORE Step 1: Frequency distribution & histogram

  18. Suppose that you combine two groups together. • How do you compute the new group mean? Group 1 Group 2 New Group 140 110 110 110 140 110 110 140 110 110 A weighted mean

  19. Suppose that you combine two groups together. • How do you compute the new group mean? Be careful computing the mean of this distribution, remember there are groups here Group 1 Group 2 New Group 9 9 8 8 7 7 7 6 6 5 140 110 110 110 140 110 110 140 110 110 A weighted mean

  20. Hrs. sleep n = 10 X Create table, sorted in descending order Step 2: Deviations table

  21. Hrs. sleep n = 10 X Mode = 7 (filled in) Median = 7 (arrow) Mean = (∑X)/n = 72/10 = 7.2 Range = 5 to 9 ∑ 72 Step 2: Deviations table

  22. Hrs. sleep n = 10 X = 9-7.2 Mode = 7 Median = 7 Mean = (∑X)/n = 72/10 = 7.2 Range = 5 to 9 ∑ 72 7.2 0 Step 2: Deviations table

  23. Hrs. sleep n = 10 X = 1.82 Mode = 7 Median = 7 Mean = ∑X/n = 72/10 = 7.2 Range = 5 to 9 SD for sample = √15.6/9 = √1.73 = 1.32 ∑ 72 7.2 0 15.6 = SS Step 2: Deviations table

  24. The mean • Change/add/delete a given score, then the mean will change. • Add/subtract a constant to each score, then the mean will change by adding(subtracting) that constant. • Multiply (or divide) each score by a constant, then the mean will change by being multiplied by that constant. • The standard deviation • Change/add/delete a given score, then the mean will change. • Add/subtract a constant to each score, then the standard deviation will NOT change. • Multiply (or divide) each score by a constant, then the standard deviation will change by being multiplied by that constant. Characteristics of a mean & standard deviation

  25. Person Hrs. GPA A 7 2.4 B 6 3.9 C 7 3.5 D 8 2.8 E 8 3.0 F 7 2.1 G 9 3.9 H 5 2.9 I 9 3.6 J 6 2.7 GPA Hours of sleep Step 3: Scatterplot

  26. Person Hrs. GPA A 7 2.4 B 6 3.9 C 7 3.5 D 8 2.8 E 8 3.0 F 7 2.1 G 9 3.9 H 5 2.9 I 9 3.6 J 6 2.7 GPA What does shape of envelope indicate about correlation? low positive correlation Hours of sleep Step 3: Scatterplot

  27. Person Hrs. GPA A 7 2.4 B 6 3.9 C 7 3.5 D 8 2.8 E 8 3.0 F 7 2.1 G 9 3.9 H 5 2.9 I 9 3.6 J 6 2.7 K 5 1.0 GPA What does shape of envelope indicate about correlation? moderate positive correlation Hours of sleep Step 3: Scatterplot, Effect of outlier

  28. Person Hrs. GPA A 7 2.4 B 6 3.9 C 7 3.5 D 8 2.8 E 8 3.0 F 7 2.1 G 9 3.9 H 5 2.9 I 9 3.6 J 6 2.7 K 9 1.0 GPA What does shape of envelope indicate about correlation? low negative correlation Hours of sleep Step 3: Scatterplot, Effect of outlier

  29. n=10 Note signs! Sum Mean +r or – r? Step 4: Bivariate Deviations Table

  30. Pearson’s r & summary statistics XY co-deviations ___2.24___ √ 15.6 * 3.47 = _2.24_ √54.132 = _2.24_ = .304 7.357 = X deviations, Y deviations

  31. μ • Based on normative data: Normal, μ = 50.0, σ = 10.0 SRA (Scientific Reasoning Assessment) (fictional) • Preparing for your analyses • Write down what you know • Make a sketch of the distribution (make a note: population or sample) • Determine the shape • What is best measure of center? • What is best measure of variability? • Mark the mean (center) and standard deviation on your sketch 40 60 An example

  32. 0.0668 m SRA (Scientific Reasoning Assessment) (fictional) • Based on normative data: Normal distr., μ = 50.0, σ = 10.0 • Question 1 • If George got a 35 on the SRA, what is his percentile rank? Unit Normal Table • Since a normal distribution, can use Unit Normal Table to infer percentile. 40 60 1.0 -1.0 That’s 6.68% at or below this score (definition of percentile) z-scores & Normal Distribution

  33. 0.1587 0.1587 m SRA (Scientific Reasoning Assessment) (fictional) • Based on normative data: Normal distr., μ = 50.0, σ = 10.0 • Question 2 Unit Normal Table • What proportion of people get between a 40 and 60 on the SRA? 40 40 60 60 1.0 -1.0 That’s about 32% outside these two scores • Since a normal distribution, can use Unit Normal Table to infer percentile. That leaves 68% between these two scores z-scores & Normal Distribution

  34. transformation SRA (Scientific Reasoning Assessment) (fictional) • Based on normative data: Normal distr., μ = 50.0, σ = 10.0 • Question 3a • Suppose that Chandra took a different reasoning assessment (the RSE: Based on normative data, Normal distr., μ= 100, σ = 15). She received a 130 on the RSE. Assuming that they are highly positively correlated, what is the equivalent score on the SRA? z-scores & Normal Distribution

  35. transformation SRA(Scientific Reasoning Assessment) (fictional) • Based on normative data: Normal distr., μ = 50.0, σ = 10.0 • Question 3a (for RSE) • Suppose that Chandra took a different reasoning assessment (the RSE: Based on normative data, Normal distr., μ= 100, σ = 15). She received a 130 on the RSE. Assuming that they are highly positively correlated, what is the equivalent score on the SRA? (for SRA) z-scores & Normal Distribution

  36. In lab: continue to review, including SPSS • Questions? Wrap up

More Related