Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Spring 2018 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays & Fridays. Welcome http://www.youtube.com/watch?v=oSQJP40PcGI

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

In nearly every class we will use clickers to answer questions in class and participate in interactive class demonstrations Remember bring your writing assignment forms notebook and clickers to each lecture

Schedule of readings Before next exam (February 9) Please read chapters 1 - 5 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

Homework Assignment 3 due Monday, January 22 Go to D2L - Click on “Content” Click on “Interactive Online Homework Assignments” Complete the next two modules: HW3-Part1-Sampling Techniques HW3-Part2-Integrating Methodologies

By the end of lecture today 1/19/18 Use this as your study guide By the end of lecture today 1/19/18 Levels of Measurement Nominal, Ordinal, Interval and Ratio Categorical vs Numeric Project 1

Categorical versus Numerical data Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count

Handedness - right handed or left handed Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count Handedness - right handed or left handed Family size Hair color Ethnic group GPA Age (Time since birth) Temperature (Kelvin) Yearly salary Breed of dog Gender - male or female Temperature (Fahrenheit) Please note this is a binary variable

On a the top half of a writing assignment form Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count On a the top half of a writing assignment form please generate two examples of categorical data and two examples of numerical data Please note we’ll use the bottom half for something else

What are the four “levels of measurement”? Ratio Absolute zero Most numeric Categories Intrinsic ordering Equal sized intervals Units meaningful Interval Names Categories Intrinsic ordering Ordinal Approaching Numeric Categories Least numeric Names Nominal Weakest

What are the four “levels of measurement”? Categorical data Nominal data - classification, differences in kind, names of categories Ordinal data - order, rankings, differences in degree Numerical data Interval data - measurable differences in amount, equal intervals Ratio data - measurable differences in amount with a “true zero” Gender - male or female Family size Jersey number Place in a foot race (1st, 2nd, 3rd, etc) Handedness - right handed or left handed

What are the four “levels of measurement”? Categorical data Nominal data - classification, differences in kind, names of categories Ordinal data - order, rankings, differences in degree Numerical data Interval data - measurable differences in amount, equal intervals Ratio data - measurable differences in amount with a “true zero” Age Hair color Telephone number Ethnic group Breed of dog Temperature Yearly salary

Please note : page 29 in text

What are the four “levels of measurement”? Categorical data Nominal data - classification, differences in kind, names of categories Ordinal data - order, rankings, differences in degree Numerical data Interval data - measurable differences in amount, equal intervals Ratio data - measurable differences in amount with a “true zero” Look at your examples of qualitative and quantitative data. Which levels of measurement are they?

Project 1 Likert Scale (summated scale) Correlation (scatterplots) Comparing two means (bar graph)

Likert Scale is always a “summated scale” with multiple items. All items are measuring the same construct. The score reflects the sum of responses on a series of items. - Likert Scale (miniquiz like Cosmo example in lecture - ask several questions then sum responses) - For example, several questions on political views (coded so that larger numbers mean “more liberal”) 1. Lower taxes and a smaller government will improve the standard of living for all. agree 1 --- 2 --- 3 --- 4 --- 5 disagree 2. Marriage should be between one man and one woman agree 1 --- 2 --- 3 --- 4 --- 5 disagree 3. Evolution of species has no place in public education agree 1 --- 2 --- 3 --- 4 --- 5 disagree

I prefer rap music to classical music Likert Scale is always a “summated scale” with multiple items. All items are measuring the same construct. The score reflects the sum of responses on a series of items. Anchored rating scales: a written description somewhere on the scale I prefer rap music to classical music Agree 1---2---3---4---5 Disagree Fully anchored rating scales: a written description for each point on the scale I prefer rap music to classical music 1- - - - - - - - - 2- - - - - - - - - 3- - - - - - - - - 4- - - - - - - - - 5 Strongly Agree Agree Neutral Strongly Disagree Disagree

Likert Scale is always a “summated scale” with multiple items. All items are measuring the same construct. The score reflects the sum of responses on a series of items.

Project 1 Likert Scale (summated scale) Correlation (scatterplots) Comparing two means (bar graph)

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 The closer to zero the weaker the relationship and the worse the prediction Positive or negative

Positive correlation: as values on one variable go up, so do values Positive correlation: as values on one variable go up, so do values for the other variable Negative correlation: as values on one variable go up, the values for the other variable go down Height of Mothers by Height of Daughters Height of Mothers Positive Correlation Height of Daughters

Positive correlation: as values on one variable go up, so do values Positive correlation: as values on one variable go up, so do values for the other variable Negative correlation: as values on one variable go up, the values for the other variable go down Brushing teeth by number cavities Brushing Teeth Negative Correlation Number Cavities

Thank you! See you next time!!