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Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10:00 - 10:50 Mondays, Wednesdays.

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Presentation on theme: "Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10:00 - 10:50 Mondays, Wednesdays."— Presentation transcript:

1 Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10: :50 Mondays, Wednesdays & Fridays. Welcome

2 Labs continue next week
Lab sessions Everyone will want to be enrolled in one of the lab sessions Labs continue next week

3 Project 1 - Likert Scale - Correlations - Comparing two means (bar graph)
PowerPoint

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11 Schedule of readings Before next exam (September 23rd)
Please read chapters in OpenStax 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

12 Homework Assignment 5 Frequency Tables and Graphing with Excel
Please print out and complete this homework worksheet And hand it in during class on Monday Due: Monday, September 12th This worksheet can be found on our regular class website and printed out to be completed (not on D2L)

13 By the end of lecture today 9/9/16
Use this as your study guide By the end of lecture today 9/9/16 Characteristics of a distribution Central Tendency Dispersion

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15 You are looking to see if “class standing” affects
Homework review You are looking to see if “class standing” affects the “level of sales”. Class standing Independent variable (IV):______________ Number of levels of IV: ________________ (how many means?) Quasi or True experiment:______________ Dependent variable: __________________ Between or within participant design: ______________ In this study, what is the operational definition of “class standing”? In this study, what is the operational definition of “level of sales”? 4 Quasi Level of sales Between Classification based on units earned Number of bags of peanuts sold

16 You are looking to see whether “type of program”
Homework review You are looking to see whether “type of program” has an effect on “body transformation”. Please identify the following variables: Independent variable (IV):______________ Number of levels of IV: _______________ (how many means?) Quasi or True experiment:______________ Dependent variable: __________________ Between or within participant design: ______________ What is the operational definition of “type of program”? What is the operational definition of “body transformation”?   Type of program 2 True Body transformation Between Type of program = type of diet (regular versus programmatic diet) Body transformation = number of pounds lost

17 You are looking to see which driving choice is most
Homework review You are looking to see which driving choice is most efficient. So you ask each driver to drive each of the three routes and time themselves on how long it takes. Please identify the following variables: Independent variable (IV):______________ (how many means) Number of levels of IV: ________________ Dependent variable: __________________ Between or within participant design: ______________ What is the operational definition of “driving efficiency”? What is the operational definition of “driving choice”? Type of route 3 driving efficiency Within Driving efficiency = travel time (measured in minutes) Driving choice = route taken

18 Homework review

19 Notice that the operational definition of each construct matters
Homework review Notice that the operational definition of each construct matters

20 Homework review gender 2 quasi salary between nominal ratio

21 Name of City 3 Quasi- experiment Temperature Between Nominal Interval

22 Must be complete and must be stapled
Homework review city 3 quasi temperature between nominal interval Must be complete and must be stapled Hand in your homework

23 Step 2: List scores in order Step 3: Decide grouped
53 58 60 61 64 69 70 72 73 75 76 78 80 82 84 87 88 89 91 93 94 95 99 Scores on an exam Remember Dot Plots Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 5: Generate frequency histogram Score on exam 6 5 4 3 2 1 Scores on an exam Score Frequency 80 – 84 5

24 Step 2: List scores in order Step 3: Decide grouped
53 58 60 61 64 69 70 72 73 75 76 78 80 82 84 87 88 89 91 93 94 95 99 Scores on an exam Remember Dot Plots Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 5: Generate frequency histogram Score on exam 6 5 4 3 2 1 Scores on an exam Score Frequency 80 – 84 5

25 Step 2: List scores in order Step 3: Decide grouped
53 58 60 61 64 69 70 72 73 75 76 78 80 82 84 87 88 89 91 93 94 95 99 Scores on an exam Remember Dot Plots Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 5: Generate frequency histogram Score on exam 6 5 4 3 2 1 Scores on an exam Score Frequency 80 – 84 5

26 Step 2: List scores in order Step 3: Decide grouped
53 58 60 61 64 69 70 72 73 75 76 78 80 82 84 87 88 89 91 93 94 95 99 Scores on an exam Remember Dot Plots Step 1: List scores Step 2: List scores in order Step 3: Decide grouped Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 5: Generate frequency histogram Score on exam 6 5 4 3 2 1 Scores on an exam Score Frequency 80 – 84 5

27 Step 2: List scores in order Step 3: Decide grouped
Scores on an exam Step 2: List scores in order Step 3: Decide grouped Step 4: Decide 10 for # bins (classes) 5 for bin width (interval size) Step 5: Generate frequency histogram Scores on an exam Score Frequency 80 – 84 5 Score on exam 6 5 4 3 2 1

28 Generate frequency polygon
Scores on an exam Generate frequency polygon Plot midpoint of histogram intervals Connect the midpoints Scores on an exam Score Frequency 80 – 84 5 Score on exam 6 5 4 3 2 1

29 Generate frequency ogive (“oh-jive”)
Scores on an exam Generate frequency ogive (“oh-jive”) Frequency ogive is used for cumulative data Plot midpoint of histogram intervals Connect the midpoints Scores on an exam Score 95 – 99 80 – 84 Score on exam 30 25 20 15 10 5 Cumulative Frequency 28 26 23 18 13 9 6 5 2 1

30 Pareto Chart: Categories are displayed in descending order of frequency

31 Stacked Bar Chart: Bar Height is the sum of several subtotals

32 Simple Line Charts: Often used for time series data (continuous data)
Simple Line Charts: Often used for time series data (continuous data) (the space between data points implies a continuous flow) Note: For multiple variables lines can be better than bar graph Note: Fewer grid lines can be more effective Note: Can use a two-scale chart with caution

33 Pie Charts: General idea of data that must sum to a total (these are problematic and overly used – use with much caution) Exploded 3-D pie charts look cool but a simple 2-D chart may be more clear Exploded 3-D pie charts look cool but a simple 2-D chart may be more clear Bar Charts can often be more effective

34 Overview Frequency distributions
The normal curve Challenge yourself as we work through characteristics of distributions to try to categorize each concept as a measure of 1) central tendency 2) dispersion or 3) shape Mean, Median, Mode, Trimmed Mean Standard deviation, Variance, Range Mean Absolute Deviation Skewed right, skewed left unimodal, bimodal, symmetric

35 Thank you! See you next time!!

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