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Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Fall, 2014 Room 120 Integrated Learning Center (ILC) 10:00 - 10:50 Mondays, Wednesdays & Fridays. http://www.youtube.com/watch?v=oSQJP40PcGI

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Remember: Bring electronic copy of your data (flash drive or email it to yourself) Your data should have correct formatting See Lab Materials link on class website to double- check formatting of excel is exactly consistent Labs

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Schedule of readings Before next exam (September 26 th ) Please read chapters 1 - 4 in Ha & Ha textbook Please read Appendix D, E & F online On syllabus this is referred to as online readings 1, 2 & 3 Please read Chapters 1, 5, 6 and 13 in Plous Chapter 1: Selective Perception Chapter 5: Plasticity Chapter 6: Effects of Question Wording and Framing Chapter 13: Anchoring and Adjustment

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Reminder A note on doodling

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By the end of lecture today 9/15/14 Use this as your study guide Correlational methodology Positive, Negative and Zero correlation Characteristics of a distribution Central Tendency Dispersion Shape

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Homework due – Wednesday (September 17 th ) No new homework – refine correlations worksheet

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Review of Homework Worksheet.10.08 22 35 25 8 100,000 10.22.35.25 80,000 250,000 350,000 220,000 Notice Gillian asked 1300 people 130+104+325+455+286=1300 130/1300 =.10.10x100=10.10 x 1,000,000 = 100,000

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Review of Homework Worksheet.10.08 22 35 25 8 100,000 10.22.35.25 80,000 250,000 350,000 220,000

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Review of Homework Worksheet

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10 2030 40 50 Age 1 2 3 4 5 6 7 8 9 Dollars Spent Strong Negative Down -.9

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Review of Homework Worksheet =correl(A2:A11,B2:B11) =-0.9226648007 Strong Negative Down -0.9227

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Review of Homework Worksheet =correl(A2:A11,B2:B11) =-0.9226648007 Strong Negative Down -0.9227 This shows a strong negative relationship (r = - 0.92) between the amount spent on snacks and the age of the moviegoer Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Correlation r (actual number)

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Scatterplot displays relationships between two continuous variables Correlation: Measure of how two variables co-occur and also can be used for prediction Range between -1 and +1 Range between -1 and +1 The closer to zero the weaker the relationship The closer to zero the weaker the relationship and the worse the prediction Positive or negative Positive or negative

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Correlation

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Correlation - How do numerical values change? Let’s estimate the correlation coefficient for each of the following r = +1.0r = -1.0 r = +.80 r = -.50r = 0.0 http://neyman.stat.uiuc.edu/~stat100/cuwu/Games.html http://argyll.epsb.ca/jreed/math9/strand4/scatterPlot.htm

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Number of bathrooms in a city and number of crimes committed Positive correlation Positive correlation: as values on one variable go up, so do values for other variable Negative correlation: as values on one variable go up, Negative correlation: as values on one variable go up, the values for other variable go down

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Is it possible that they are causally related? Correlation does not imply causation Yes, but the correlational analysis does not answer that question What if it’s a perfect correlation – isn’t that causal? No, it feels more compelling, but is neutral about causality Number of Birthday Cakes Number of Birthdays

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Linear vs curvilinear relationship Linear relationship is a relationship that can be described best with a straight line Curvilinear relationship is a relationship that can be described best with a curved line

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r = +0.97 This shows a strong positive relationship (r = 0.97) between the appraised price of the house and its eventual sales price Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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r = +0.97r = -0.48 This shows a moderate negative relationship (r = -0.48) between the amount of pectin in orange juice and its sweetness Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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r = -0.91 This shows a strong negative relationship (r = -0.91) between the distance that a golf ball is hit and the accuracy of the drive Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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r = -0.91 r = 0.61 This shows a moderate positive relationship (r = 0.61) between the length of stay in a hospital and the number of services provided Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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r = +0.97r = -0.48 r = -0.91 r = 0.61

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Height of Daughters (inches) Height of Mothers (in) 48 52 56 60 64 68 72 76 48 52 5660 64 68 72 This shows the strong positive (r = +0.8) relationship between the heights of daughters (in inches) with heights of their mothers (in inches). Both axes and values are labeled Both axes have real numbers listed Variable name is listed clearly Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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Height of Daughters (inches) Height of Mothers (in) 48 52 56 60 64 68 72 76 48 52 5660 64 68 72 This shows the strong positive (r = +0.8) relationship between the heights of daughters (in inches) with heights of their mothers (in inches). Both axes and values are labeled Both axes have real numbers listed Variable name is listed clearly Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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Height of Daughters (inches) Height of Mothers (in) 48 52 56 60 64 68 72 76 48 52 5660 64 68 72 This shows the strong positive (r = +0.8) relationship between the heights of daughters (in inches) with heights of their mothers (in inches). Both axes and values are labeled Both axes have real numbers listed Variable name is listed clearly Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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Height of Daughters (inches) Height of Mothers (in) 48 52 56 60 64 68 72 76 48 52 5660 64 68 72 This shows the strong positive (r = +0.8) relationship between the heights of daughters (in inches) with heights of their mothers (in inches). Both axes and values are labeled Both axes have real numbers listed Variable name is listed clearly Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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Height of Daughters (inches) Height of Mothers (in) 48 52 56 60 64 68 72 76 48 52 5660 64 68 72 This shows the strong positive (r = +0.8) relationship between the heights of daughters (in inches) with heights of their mothers (in inches). Both axes and values are labeled Both axes have real numbers listed Variable name is listed clearly Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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1. Describe one positive correlation Draw a scatterplot (label axes) 2. Describe one negative correlation Draw a scatterplot (label axes) 3. Describe one zero correlation Draw a scatterplot (label axes) Break into groups of 2 or 3 Each person hand in own worksheet. Be sure to list your name and names of all others in your group Use examples that are different from those is lecture 4. Describe one perfect correlation (positive or negative) Draw a scatterplot (label axes) 5. Describe curvilinear relationship Draw a scatterplot (label axes)

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Height of Daughters (inches) Height of Mothers (in) 48 52 56 60 64 68 72 76 48 52 5660 64 68 72 This shows the strong positive (r = +0.8) relationship between the heights of daughters (in inches) with heights of their mothers (in inches). Both axes and values are labeled Both axes have real numbers listed 1. Describe one positive correlation Draw a scatterplot (label axes) 2. Describe one negative correlation Draw a scatterplot (label axes) 3. Describe one zero correlation Draw a scatterplot (label axes) 4. Describe one perfect correlation (positive or negative) Draw a scatterplot (label axes) 5. Describe curvilinear relationship Draw a scatterplot (label axes) Variable name is listed clearly Description includes: Both variables Strength (weak,moderate,strong) Direction (positive, negative) Estimated value (actual number)

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