Basic Quantitative Methods in the Social Sciences (AKA Intro Stats)

1. Basic Quantitative Methods in the Social Sciences(AKA Intro Stats) 02-250-01 Lecture 1

2. Course Outline Highlights!

3. Course Outline Highlights! Course Description: Introduction to measurement of variables, organization and description of numerical data, testing hypotheses, inference, and interpretation of findings in the Social Sciences. Topics include: Descriptive statistics, normal distribution, probability, sampling, hypothesis testing, t-tests, correlation, and chi-square tests. Objectives: By the end of the course, students should have a basic understanding of how to interpret numerical data using direct calculation.

4. Anti-Requisites • Students cannot receive credit for more than one introductory statistics course. • The anti-requisites for this course are 65-205 (formerly called 65-253), 65-250, 65-251, 73-105, 73-205, and 85-222. If you have received credit for any of these courses, you are not eligible to receive credit for 02-250. If you are unsure, contact the Registrars office to clarify.

5. Required Textbook • Howell, D. C. (1999). Fundamental Statistics for the  Behavioral Sciences. 4th Ed. Pacific Grove, CA: Duxbury Press. Recommended Textbook • Kranzler, J. H. (2003). Statistics for the terrified. 3rd Ed. Upper Saddle River, NJ: Pearson Education Inc.

6. Course Webpage • This course has a comprehensive webpage. You MUST visit this page frequently (at least once a week), as it is updated regularly with important information. • The web page is where you will download lecture slides, read announcements, the course outline, evaluation details, and see your grades. • The website address is: http://www.uwindsor.ca/stats250

7. Lecture Notes • Approximately one week before each lecture, Powerpoint slides will be available on the web. You should download these slides, and print them out to bring to each class. If you do not have them, you will NOT have time to copy the slides during the lecture. You should also bring your lecture slides from the preceding class to each class.

8. Course Outline Highlights! Important Dates: • May 12                    First class - 4:00 PM sharp! • May 12 – May 19         Participant pool signup! • May 16                  Last day to register • May 19 Victoria Day, No Class • June 4                   Midterm Examination            • June 6                    Last day to voluntarily drop • June 16                 Assignment due in class at 4:00 PM Sharp! • June 18                     Last class • June 25                     Final Examination - 7 - 10pm

9. Course Outline Highlights! Written Assignment: • There will be ONE written assignment worth 25% (due AT THE BEGINNING OF CLASS on June 16) consisting of problems that will resemble problems on the midterm and final exams. Assignments received after 4:00 PM on the due date will NOT BE ACCEPTED. You must show all relevant calculations to receive full marks on these assignments. • If you cannot attend class on June 16, hand the assignment in to J. Frank’s mailbox in the Psychology Department. Please remember to have your assignment dated and time stamped (i.e., by 4:00 pm on June 16) and signed by one of the departmental secretaries.

10. Course Outline Highlights • All tests are open-book format (i.e., you may bring your textbook, with any written notes in the book, but no other outside material, e.g., photocopied sheets of paper) • You should also bring pens, pencils, and a calculator to the Mid-term and Final exams

11. Course Outline Highlights • Calculators capable of storing information entered by the user are not allowed and sharing of calculators or other materials (i.e., textbook) is not permitted under any circumstances • so don’t forget your textbook for the exams! • You must bring your U of W student ID Card to the exams

12. Course Outline Highlights! Grading Scheme: • One written assignment = 25% • 1 Mid-term test = 30% of final grade • Final Examination = 45% of final grade • TOTAL: 100%

13. Course Outline Highlights! • You may earn up to two bonus points in this class • You can earn these in two ways: • Participation in research • Completion of a bonus assignment (described in the course outline)

14. Sign Up for Participant Pool!! • see Psychology research first hand! • earn up to 2 bonus points • HOW???? • sign up on the web (takes less than 5 minutes): • www.uwindsor.ca/psychology/signup • or access through psych homepage • You MUST sign up by 9:00 am May 19 to be included

15. Course Outline Highlights • Attendance: Regular attendance is strongly advised • Stated differently, this is NOT a course where you will be able to keep up just by reading the book and doing the exercises • It is your responsibility to obtain notes for any missed lectures from a classmate

16. Course Outline Highlights • Missed Tests: Students MUST take the midterm and final exams during the scheduled times • If a scheduled test is missed, the student will receive a grade of zero for that test except in cases of medical/family emergency or extreme circumstances (these do not include travel, special occasions, or job-related scheduling conflicts), in which case supporting documents (e.g., physician’s note) must be submitted to one of the instructors within one week following the missed test

17. Course Outline Highlights • Note: The final exam cannot be re-written at another time • If it is missed for a valid reason, the student must apply for aegrotat standing through the Registrar’s Office

18. Course Outline Highlights • The University Calendar explains the regulations regarding plagiarism and other academic dishonesty • It is your responsibility to familiarize yourself with these regulations

19. Hints for Stats • Dates for topics covered are approximate (see the Course Outline) • Keep up with the work – this is a subject which builds upon itself – don’t get left behind

20. More Hints for Stats • Attend class! It is very easy to be left behind if you miss classes • You are responsible for all class material covered and assigned readings. • If you have to miss class, you are responsible for getting the notes from another student

21. HELP CLINIC • Tammy Whitlock, a senior graduate student will be available on a drop-by first-come-first-serve basis for extra help in the Statistics Help Clinic. The clinic is located in Chrysler Hall North, room G134. You can call the help clinic at 253-3000 ext. 2393 as well during the help clinic hours. The Help Clinic hours are TBA, and will be posted here as soon as I know them. Tammy is available for the following: • working on extra practice problems • getting help with what you don't understand • reviewing your assignment and exams • clarification of grades

22. IMPORTANT NOTE • I am available during my office hours (as noted above) on a first-come-first-serve basis. Due to the high enrollment in the class, any questions or issues about course content or exams should be directed to the Help Clinic, and not to myself. • For instance, if you want help understanding t-tests or if you wish to review your mid-term exams, you should go to the Help Clinic. If you miss an exam or if you have a problem that cannot be dealt with at the Help Clinic, you should come to my office hours.

23. More Hints for Stats • Work in groups on practice problems • IMPORTANT NOTE: This class is both theoretical and applied – know how to calculate formulae and why (i.e., test selection – we’ll explain this in the coming weeks…)

24. Final Hint • For many students, you have put this class off for as long as possible • Try not to get stressed out! This class is as easy or hard as you make it! • If you put the time in, you will be fine 

25. Finally, Some Math Review (see Appendix A) Unless otherwise indicated, the order of mathematical operations is: • Work within parentheses first • Square or find the square root • Multiply or divide • Add or subtract

26. Order of Operations Summary • PEMDAS – Please Excuse My Delayed Assignment Sir • Parentheses • Exponents • Multiply and Divide • Add and Subtract

27. More Math Review • Perform mathematical operations: • Contained within a set of parentheses () first, to find the quantity (2+4)2 = (6)2 = 36 • Also perform operations within the square root sign first, then take the square root of the quantity • Perform operations above or below the dividing line of a fraction prior to dividing

28. More Math Review • In rounding off decimals, if the first digit is equal to or greater than 5 (e.g., .7), round up • In rounding off decimals, if the first digit is less than 5 (e.g., .3), round down • RULE: While working on a problem, round your calculations to 4 decimal places. When reporting your final answer, round your calculation to 2 decimal places (unless otherwise directed).

29. So Let’s Get Started! • Definitions • Statistics • Populations and Samples • Parameters and Statistics • Variables • Operational Definitions

30. Definitions • Statistics (as a discipline): The body of rules and procedures for describing and evaluating numerical information • A set of procedures or rules for • a) reducing large masses of data to manageable portions and • b) allowing us to draw conclusions from those data

31. More Statistics • The subject matter of Statistics is usually divided into 2 broad groups of techniques and procedures: • Descriptive Statistics • Inferential Statistics

32. Descriptive Statistics • Descriptive Statistics: The techniques for organizing, summarizing, representing and extracting information from numerical data • These are used to describe data, e.g.: • Average • Standard Deviation

33. Inferential Statistics • Inferential Statistics: The rules and procedures for inferring the characteristics of populations from sample data (inferring parameters from statistics – we’ll explain these later) • These are used to make inferences about a population, e.g., • t-test • Correlation

34. Definitions: Populations • Population: Any defined group of objects, organisms, or events that you’re interested in • A population must be defined in enough detail to determine whether to include a given individual or event • A population contains all members of the defined group

35. Example 1: Population of U of W Statistics Students • This population would be described as all students enrolled in 02-250 during the 2003 calendar year (so a student enrolled in 115 Introductory Psychology would not be part of this population)

36. Example 2: Population of Canadian Teenagers • This population would be described as all teenagers in Canada between the ages of 13 and 18 • Note: A population is the entire group you are interested in

37. More Definitions! • Sample: Any subset of the population, usually meant to represent the population • If the population was defined as all students enrolled in 02-250 during all three 2003 calendar year semesters (that is, Fall, Winter, Intersession 2003), then this class would be a sample of the population • Population = three 02-250 classes • Sample = this 02-250 class (a subset of the population)

38. Samples cont. • If a population was defined as all teenagers in Canada between the ages of 13 and 18 then the teenagers between 13 and 18 in Windsor would be a sample of this population • Population: All teens in Canada • Sample: All teens in Windsor (a subset of the population)

39. Relationship Between Population and Sample

40. Samples vs. Populations • While populations are usually large (in number of events or persons), sizeis not the defining characteristic of populations • If you are only interested in the events or organisms which have been directly observed (which you have data for), then those events (or organisms) are considered the population, regardless of size

41. Samples vs. Populations cont. • On the other hand, if you wish to generalize the findings from an observed group to events (or organisms) which have not been directly observed, then the actually observed events (or organisms) are a sample (of a population)

42. Samples vs. Populations cont. • E.g., You measure the height of 115 students who you randomly approach in the CAW Centre. If you wish to simply state the average height of these 115 people, then they are a population • If, however, you want to estimate the average height of all U of W students, then these 115 students are a sample of the population of all U of W students

43. Sample vs. Population: You Decide! • Researcher X wants to know how tall the average University hockey player is. She measures and records the heights of 30 University of Windsor hockey players. These 30 athletes are….? • Researcher Y wants to know the average income of Windsor Liberal party members. She obtains financial data from all Liberal party members in Windsor. These data are from a …..?

44. Populations vs Samples cont. • For us to draw accurate conclusions about a population, our sample must be representative. In a representative sample the characteristics of the sample accurately reflect the characteristics of the population

45. Populations vs Samples cont. • To obtain a representative sample, we select a random sample • A random sample allows for all possible scores in the population to have the same chances of being included

46. Random Sampling • In order to obtain a random sample, we must use a random samplingtechnique, where every data point has an equal chance of being selected e.g.: • Coin toss • Random numbers table

47. Definitions cont. • Parameter: A term which describes or summarizes a population • E.g., the average age (mean) of all students enrolled in 02-250 during the 2003 calendar year (the population) • A parameter does one thing: it describes a population

48. Definitions cont. • Statistic: A term which describes or summarizes a sample • E.g., the average age (mean) of students in this class (as a sample of the population of all students enrolled in 02-250 during the 2003 calendar year) • A statistic does two things: • 1) it describes a sample and • 2) it estimates a parameter

49. Statistics vs. Parameters • It is often impractical to directly observe and measure every person or event in a population, so we must estimate population characteristics (parameters) using data obtained from samples (statistics)

50. Statistics vs. Parameters cont. • Collecting the age of all students enrolled in 02-250 during the 2003 calendar year would be very time consuming, so we can take a sample of those students (this class), collect their age data, and calculate the average (mean) age • This average age would then be an estimate (statistic) of the average age of all students who have taken 02-250 in the 2003 calendar year.