Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Spring 2017 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays.

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Introduction to Statistics
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Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Spring 2017 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays & Fridays. Welcome http://www.youtube.com/watch?v=oSQJP40PcGI

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 ..

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

Schedule of readings Before next exam (February 10) 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

Start by reading Online supplemental reading 1 (Appendix D) Please read Chapters 1 & 2

Homework Assignment 3 Go to D2L - Click on “Content” Click on “Interactive Online Homework Assignments” Complete Assignment 3: HW3-Part1-Sampling Techniques HW3-Part2-Integrating Methodologies Due: Monday, January 23th

By the end of lecture today 1/20/17 Use this as your study guide By the end of lecture today 1/20/17 Population (census) versus sample Descriptive or inferential Parameter versus statistic Random sampling vs Random assignment Random versus non-random sampling techniques Simple random sampling Systematic random sampling Stratified sampling Cluster sampling Convenience sampling Snowball sampling Judgment sampling

So far, Measurement: observable actions Theoretical constructs: concepts (like “humor” or “satisfaction”) Operational definitions Validity and reliability Independent and dependent variable Random assignment and Random sampling Within-participant and between-participant design Single blind (placebo) and double blind procedures

So far, Continuous vs Discrete variables Quantitative vs qualitative variables Levels of measurement: Nominal, Ordinal, Interval and Ratio

Sample versus population (census) How is a census different from a sample? Census measures each person in the specific population Sample measures a subset of the population and infers about the population – representative sample is good What’s better? Use of existing survey data U.S. Census Family size, fertility, occupation The General Social Survey Surveys sample of US citizens over 1,000 items Same questions asked each year

Population (census) versus sample Parameter versus statistic Parameter – Measurement or characteristic of the population Usually unknown (only estimated) Usually represented by Greek letters (µ) pronounced “mew” pronounced “mu” Statistic – Numerical value calculated from a sample Usually represented by Roman letters (x) pronounced “x bar”

Descriptive or inferential? To determine this we have to consider the methodologies used in collecting the data Descriptive or inferential? Descriptive statistics - organizing and summarizing data Inferential statistics - generalizing beyond actual observations making “inferences” based on data collected What is the average height of the basketball team? Measured all of the players and reported the average height Measured only a sample of the players and reported the average height for team In this class, percentage of students who support the death penalty? Measured all of the students in class and reported percentage who said “yes” Measured only a sample of the students in class and reported percentage who said “yes” Based on the data collected from the students in this class we can conclude that 60% of the students at this university support the death penalty Measured all of the students in class and reported percentage who said “yes”

Descriptive or inferential? Descriptive statistics - organizing and summarizing data Inferential statistics - generalizing beyond actual observations making “inferences” based on data collected Men are in general taller than women Measured all of the citizens of Arizona and reported heights Shoe size is not a good predictor of intelligence Measured all of the shoe sizes and IQ of students of 20 universities Blondes have more fun Asked 500 actresses to complete a happiness survey The average age of students at the U of A is 21 Asked all students in the fraternities and sororities their age

What is the independent variable? Amount of sleep Does amount of sleep (4 vs 8 hours) affect class attendance? Selected 350 students from 38,000 undergraduates at U of Washington and randomly assigned students into two groups. What is the independent variable? Amount of sleep How many levels are there of the IV? 2 levels (4 hours vs 8 hours) What is the dependent variable? Group 1 gets 4 hours sleep Class attendance What is population and sample? Population: whole school Sample: group of 350 students Note: Parameter would be what we are guessing for the whole school based on these 350 students What is statistic ? Group 2 gets 8 hours sleep Average class attendance for 350 students Quasi versus true experiment (random assignment)? True Random sample? Doesn’t say in the problem, so we have to assume “no”

What is the independent variable? Gender of teacher Does gender of the teacher affect test scores for the students in California? Selected 150 students from Santa Monica and created two groups. What is the independent variable? Gender of teacher How many levels are there of the IV? 2 levels (male vs female teacher) What is the dependent variable? Group 1 gets a female teacher Test Scores What is population and sample? Population: California Sample: group of 150 students from Santa Monica What is statistic ? Group 2 gets a male teacher Average test score for 150 students Quasi versus true experiment (random assignment)? Doesn’t say in the problem, so we have to assume “no” Random sample? No – Random sample would require that everyone in California be equally likely to be chosen.

Let’s try one A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. The independent variable in this study was a. the performance of the subjects on the vision exam b. the subjects who ate the carrots c. whether or not the subjects ate the carrots d. whether or not the subjects had their vision tested

Let’s try one A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. The dependent variable in this study was a. the performance of the subjects on the vision exam b. the subjects who ate the carrots c. whether or not the subjects ate the carrots d. whether or not the subjects had their vision tested

Let’s try one A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. This experiment was a a. within participant experiment b. between participant experiment c. mixed participant experiment d. non-participant experiment

Let’s try one When Martiza was preparing her experiment, she knew it was important that the participants not know which condition they were in, to avoid bias from the subjects. This is called a _____ study. She also was careful that the experimenters who were interacting with the participants did not know which condition those participants were in. This is called a ____ study. a. between participant; within participant b. within participant; between participant c. double blind design; single blind d. single blind; double blind design

Let’s try one A measurement that has high validity is one that a. measures what it intends to measure b. will give you similar results with each replication c. will compare the performance of the same subjects in each experimental condition d. will compare the performance of different subjects

Writing Assignment – Pop Quiz Ari conducted a watermelon seed spitting experiment. She wanted to know if people can spit farther if they get a running start. She tested 100 people. She randomly assigned them into one of two groups. One group stood still on the starting line and spit their watermelon seeds as far as they could. The second group was allowed to run up to the starting line before they spit their watermelon seeds. She measured how far each person spit their watermelon seeds. Please answer the following questions 1. What is the independent variable? 2. The independent variable: Is it continuous or discrete? 3. The independent variable: Is it nominal, ordinal, interval or ratio? 4. What is the dependent variable? 5. The dependent variable: Is it continuous or discrete? 6. The dependent variable: Is it nominal, ordinal, interval or ratio? 7. Is this a quasi or true experiment? 8. Is this a within or between participant design 9. Is this a single blind, double blind or not at all blind experiment? 10. Be sure to put your name and CID on this page

Writing Assignment – Pop Quiz Ari conducted a watermelon seed spitting experiment. She wanted to know if people can spit farther if they get a running start. She tested 100 people. She randomly assigned them into one of two groups. One group stood still on the starting line and spit their watermelon seeds as far as they could. The second group was allowed to run up to the starting line before they spit their watermelon seeds. She measured how far each person spit their watermelon seeds. Running versus standing still Please answer the following questions 1. What is the independent variable? 2. The independent variable: Is it continuous or discrete? 3. The independent variable: Is it nominal, ordinal, interval or ratio? 4. What is the dependent variable? 5. The dependent variable: Is it continuous or discrete? 6. The dependent variable: Is it nominal, ordinal, interval or ratio? 7. Is this a quasi or true experiment? 8. Is this a within or between participant design 9. Is this a single blind, double blind or not at all blind experiment? 10. Be sure to put your name and CID on this page Discrete Distance that the seed was spit Nominal Continuous True Experiment Ratio Between Not at all

Simple random sampling: each person from the population has an equal probability of being included Sample frame = how you define population Let’s take a sample …a random sample Question: Average weight of U of A football player Sample frame population of the U of A football team Random number table – List of random numbers Pick 24th name on the list Or, you can use excel to provide number for random sample =RANDBETWEEN(1,115) 2016 Pick 64th name on the list (64 is just an example here) 64

Systematic random sampling: A probability sampling technique that involves selecting every kth person from a sampling frame You pick the number Other examples of systematic random sampling 1) check every 2000th light bulb 2) survey every 10th voter

Stratified sampling: sampling technique that involves dividing a sample into subgroups (or strata) and then selecting samples from each of these groups - sampling technique can maintain ratios for the different groups Average number of speeding tickets 12% of sample is from California 7% of sample is from Texas 6% of sample is from Florida 6% from New York 4% from Illinois 4% from Ohio 4% from Pennsylvania 3% from Michigan etc Average cost for text books for a semester 17.7% of sample are Pre-business majors 4.6% of sample are Psychology majors 2.8% of sample are Biology majors 2.4% of sample are Architecture majors etc

Cluster sampling: sampling technique divides a population sample into subgroups (or clusters) by region or physical space. Can either measure everyone or select samples for each cluster Textbook prices Southwest schools Midwest schools Northwest schools etc Average student income, survey by Old main area Near McClelland Around Main Gate etc Patient satisfaction for hospital 7th floor (near maternity ward) 5th floor (near physical rehab) 2nd floor (near trauma center) etc

Non-random sampling is vulnerable to bias Convenience sampling: sampling technique that involves sampling people nearby. A non-random sample and vulnerable to bias Snowball sampling: a non-random technique in which one or more members of a population are located and used to lead the researcher to other members of the population Used when we don’t have any other way of finding them - also vulnerable to biases Judgment sampling: sampling technique that involves sampling people who an expert says would be useful. A non-random sample and vulnerable to bias

Thank you! See you next time!!