Introduction to Statistics



Introduction to Statistics (Psych 274)

Brian Baucom, Ph.D.

Fall, 2008

Lectures: SGM 601, Monday and Wednesday 2:00-3:20

Labs: SGM 631, Tuesday 8:00-9:50, Wednesday 12:00-1:50, or Thursday 2:00-3:50

Instructor: Brian Baucom, Ph.D.

Office: SGM 922

Office hours: Monday and Wednesday, 3:30-4:30

Phone: 310-625-9267

Email: baucom@usc.edu

TA’s: Jongsoo Baek & Chris Courtney

Office hours: by appointment

Email: jongsoob@usc.edu & ccourtne@usc.edu

Course overview:

This course covers the basic elements of statistics commonly used in the social sciences. We will cover material and do exercises that will help you to develop a conceptual understanding of how statistics work as well as to acquire the skills and knowledge to carry out and interpret a number of statistical tests both by hand and using statistical software (SPSS).

Course materials:

There is only one required textbook for this course:

Kiess, H. O. (2002) Statistical Concepts for the Behavioral Sciences (3rd edition), Allyn and Bacon: Boston. (A study guide is available, but not required.)

The book is available through the bookstore. There may also be used copies available at on-line booksellers like .

You are also required to have a hand calculator that has a memory and takes square roots in order to do homework problems and to take exams. You will find it convenient to have a calculator that performs at least the simple statistical functions such as finding a mean and a standard deviation; these cost $10-15. Though some PDA's and other small electronic devices (e.g., iPods, cell phones, etc.) have calculators built in, you are not allowed to use these devices during exams so please make sure to purchase a calculator or to borrow one from a friend for exams.

Course policies:

Blackboard – I will use Blackboard to post slides, assignments, announcements, and exam grades as promptly as possible. Your TA will post your lab assignments and grades on Blackboard as well. Your TA will also distribute copies of your lab assignments in lab sessions so there is no need to print out a copy for yourself. Please monitor your scores often and keep all returned, graded assignments until final grades have been determined. You will need to bring a graded assignment in as proof if it was incorrectly entered into Blackboard. All score corrections must be requested prior to the scheduled final exam period. No changes will be made after that date and time.

Attendance – Attendance in lab is required in order to get credit for any activity conducted that day date. You are required to attend the lab section for which you are registered. All lab assignments are due at the end of your scheduled lab session. If you must miss a lab due to a pre-scheduled event, you must arrange in advance of the lab period to complete the work either in another of my lab sections or on your own time. It is due at the end of the lab attended or at the end of your scheduled lab if you are completing it on your own time. Only one such arrangement will be made per student per semester, and requires advanced notification of all TA’s involved plus written evidence that you cannot attend your lab. If you miss lab without such arrangements, make-ups will only be allowed if you can document a lab-day justifiable absence (defined below); otherwise you will not receive any credit for the lab task completed on the day you missed.

Please be aware that you are responsible for all information presented during lecture and lab sessions. This information will usually be significantly more extensive than the lecture and lab notes that are available on Blackboard. I strongly encourage you to come to all lecture and lab sessions, and to get notes from a classmate or two if you are unable to attend. If you have a justifiable absence, you may come to office hours to see if additional information was given in lecture.

Office hours – Office hours are a chance for you to get additional help in either understanding the concepts we’ve been covering or in the how to of conducting the statistical analyses from class and lab. I encourage you all to come to office hours as often as would be helpful and useful. If you cannot come to my office hours, please contact me by email to see about scheduling an alternative time to meet. Given the number of students in the course, all office hours visits will be limited to approximately 15 minutes per student per week whether you come during scheduled times or during an alternative time. If you need additional assistance, you could consider arranging for a private tutor. I can assist you in finding a good, knowledgeable tutor if you would like.

Deadlines – All deadlines are firm; being absent the day an assignment is due, given, or amended does not grant you an extension. Written work must be printed (not emailed), unless told otherwise, and turned in either to your TA within 10 minutes of the start of a lab session if it is due at the start of lab or to your TA’s mailbox by 4:30pm on the due date. Please do not timestamp your work with the administrators in the Psychology office. Extensions will not be granted without a justifiable absence (defined below).

Justifiable absences – Only the following qualify as justifiable absences: 1) serious illness, 2) personal/family emergency, 3) school-related activity, and 4) scheduled graduate school or job interview with proof from the school or company. I must have in writing from a doctor or an appropriate staff person a statement that you could not possibly attend class on the specific dates that includes the lab/due date. Your extension is one lecture/lab session for every session you were excused. One day is assumed unless your note states otherwise. Show me your excuse the first class day after it expires and I will notify your TA that you are to make up any missed lab(s).

Activities, Assignments, and Grading:

Exams – There will be three, non-cumulative exams given during lecture sessions (two during the regular semester and the final exam during the exam period). Each exam will assess your understanding of the concepts discussed in the lecture and lab sessions as well as in your reading assignments. Questions will be based primarily on material covered during lecture and lab. Each student is required to bring a lead pencil and a Scantron form to each exam. I will provide you with a formula sheet for each exam that contains the necessary formulas for conducting all analyses on the exams. Unexcused missed exams will receive a score of 0. Make up exams will be given with written documentation

Homework – Homework is assigned in a manner to help you learn the concepts and procedures that we discuss in lecture and that you read about outside of class. Full credit will be given for homework if a genuine effort was made to do the problems, whether correct or incorrect. The answers to most computational questions are in the Appendix of your book and your TA will hand out the correct answers to conceptual questions in lab.

Lab assignments – Your TA will provide you with a handout containing detailed instructions for each lab assignment. It is highly recommended that you keep these handouts over the course of the semester to use as study guides for your exams. Though we will not use SPSS on any of the exams, the labs will frequently walk you through the steps of how to conduct analyses and interpret the results. This information will be valuable to you when you are reviewing for exams.

Grading -

You final grade in the course will be based on a weighted average of attendance, homework, and exams using the scales below:

Weights for exams and assignments:

Exams (200 points each X 3): 600

Lecture attendance: 120

Homework Problems: 100

Lab Attendance: 80

Lab Assignments: 100

Total possible points: 1000

Grading scale (grades are rounded to the nearest percent):

A (93%+) A- (92-90%) B+ (89-88%) B (87-83%) B- (82-80%) C+(79-78%)

C (77-73%) C- (72-70%) D (69-60%) F (59% or lower)

Academic integrity:

Cheating during an exam will result in a score of 0 on that exam. A score of zero will be assigned if a student has displayed a test for others to see, looked at another student’s exam, or attempted to communicate in any manner with another student during the exam. You are not allowed to leave the testing room and return once the exam has been distributed. No cell phone, pda’s, computers, or other electronic devices may be out or on during an exam.

Gross dishonesty on any graded portion of the course, including exams and lab assignments, will result in a grade of F for the entire course. Gross dishonesty includes behaviors such as, but not limited to, using tests, notes, or answer sheets during an exam, having someone else take an exam for you, or submitting written assignments which are not solely your own work.

Disability services and programs statement:

Any student requesting academic accommodations based on a disability is required to register with Disability Services and Programs (DSP) each semester. A letter of verification for approved accommodations can be obtained from DSP. Please be sure the letter is delivered to me (or to your TA) as early in the semester as possible. DSP is located in STU 301 and is open 8:30 a.m. to 5:00 p.m., Monday through Friday. DSP’s phone is (213) 740-0776.

Lecture Schedule

A tentative schedule of dates, topics and readings are shown below. Some topics might be covered faster or slower than shown in this schedule, depending on the students' understanding of the material. Homework problems (which are due in lab), along with assignment dates and due dates are listed on the last page. Homework assignments may be modified, and announced in lecture, as the Semester proceeds.

|Day |Date |Topic |Readings |

|Mon |8/25 |Introduction and course overview. | |

|Wed |8/27 |Basic concepts of statistics. |Chp. 1 & 2 |

| | |Scientific Research: Scales of measurement, discrete | |

| | |& continuous variables. | |

|Mon |9/1 |Labor Day: no class | |

|Wed |9/3 |Describing data: Frequency distributions and graphs |Chp. 3 |

|Mon |9/8 |Describing data: Measures of central tendency. |Chp. 4 |

|Wed |9/10 |Describing data: Measures of variability. |Chp. 5 |

|Mon |9/15 |The normal distribution and probability. |Chp. 6 |

|Wed |9/17 |The normal distribution and probability. |Chp. 6 |

| | |(continued) | |

|Mon |9/22 |Using Statistics for Inference and Estimation. |Chp. 7 |

|Wed |9/24 |Using Statistics for Inference and Estimation. |Chp. 7 |

| | |(continued) | |

|Mon |9/29 |First Midterm Exam | |

|Wed |10/1 |Statistical hypothesis testing with z-tests. |Chp. 8 |

|Mon |10/6 |Statistical hypothesis testing with the one-sample t test. |Chp. 8 |

|Wed |10/8 |Elementary Research Methods. |Chp. 9 |

| | |. | |

|Mon |10/13 |Statistical hypothesis testing with the two-sample t test |Chp. 9 |

| | |for independent and dependent groups. | |

|Wed |10/15 |One-factor between-subjects analysis of variance. |Chp. 10 |

|Mon |10/20 |One-factor between-subjects analysis of variance. |Chp. 10 |

| | |(continued) | |

|Wed |10/22 |Multiple comparison procedures for the one-factor |Chp. 10 |

| | |between-subjects analysis of variance. | |

|Mon |10/27 |Second Midterm Exam | |

|Wed |10/29 |Two-factor between-subjects analysis of variance. |Chp. 11 |

|Mon |11/3 |Two-factor between-subjects analysis of variance. |Chp. 11 |

| | |(continued) | |

|Wed |11/5 |Two-factor between-subjects analysis of variance. |Chp. 11 |

| | |(continued) | |

|Mon |11/10 |Analysis of frequency data with the chi square test. |Chp. 15 |

| | | |(pp. 448-462) |

|Wed |11/12 |Analysis of frequency data with the chi square test. |Chp. 15 |

| | | |(pp. 448-462) |

|Mon |11/17 |Correlation. |Chp. 13 |

|Wed |11/19 |Correlation. |Chp. 13 |

|Mon |11/24 |Correlation. |Chp. 13 |

|Wed |11/26 |Regression. |Chp.14 |

|Mon |12/1 |Regression. |Chp.14 |

|Wed |12/3 |Regression. |Chp.14 |

| | |Final Exam: TBA | |

Homework Assignments

|Date | | |Due on |

|Assigned |Chapter |Assigned Problems |Lab Dates |

|8/27 |Ch. 1 & 2 |p. 7—1, 2; p. 9—1, 2; p. 10—1, 2; p. 12—3, 4, 6 |9/2 to |

| | |p. 17—1, 2; p. 19—1, 2, 3, 4, 5; p. 23—1, 2, 3; |9/4 |

| | |p. 26—1, 2, 3, 4; p. 29—9, 10, 12, 13, 14 | |

|9/1 |Ch. 3 |p. 35—1, 2; p.46—1, 3, 6, 7 a & b; p.54—1, 2, 3; p. 59—5; p. 60-61—6 a, b, c, d; 7|9/9 to |

| | |a, b. |9/11 |

|9/8 |Ch. 4 |p. 66—1, 2, 3, 4, 7; p. 70—1, 2; p. 74—1, 2, 3; p.75— 3, 4; p. 76.—5. |9/16 to |

| | | |9/18 |

|9/10 |Ch. 5 |p. 80—1, 2, 3; p.89— 1, 2a, c, d; p. 92—1; p. 94—3, 4. |9/16 to |

| | | |9/18 |

|9/15 |Ch. 6 |p. 100—1, 2, 4a,c,e,g,k,i; p.110—1, 2a,b,c, 3a,b; p. 119—1, 3, 4a,b,c, 5a,b; |9/23 to |

| | |p.122-125—4, 5, 6, 8, 11. |9/25 |

|9/22 |Ch. 7 |p. 130—1, 2; p. 139-140—1, 5, 6, 7a,b, 8; p. 143—1, 2a,b; p. 145-146—1, 2, 3, |9/30 to |

| | |8a,b,c. |10/2 |

|10/1 |Ch. 8 |p. 157—1, 2, 3, 5; p. 160—3, 5, 6; |10/7 to |

| | | |10/9 |

|10/6 |Ch. 8 |p. 170—1a,b, 2a,b, 3a,b, 4, 5, 6; p. 175—1, 2, 3, 4; |10/14 to |

| | |p. 177—1, 2, 3, 4, 5, 13 |10/16 |

|10/8 |Ch. 9 |p. 184—1, 2, 3, 4, 5; p. 190—1, 2, 3d.; p. 200—1, 3, 6, 9 (problem 1) |10/14 to |

| | | |10/16 |

|10/13 |Ch. 9 |p. 210—1, 2, 4a & d, 5, 6, 7 (Report 1); p. 215—1, 2; p. 220—5 |10/21 to |

| | | |10/23 |

|10/15 |Ch 10 |p. 237—1, 3, 5, 6, 7, 10, 13, 16, 19 |10/21 to |

| | | |10/23 |

|10/20 |Ch 10 |p. 246—1, 2, 3, 5, 13 (Exp 6-10), 14, 15; p. 267—1, |10/28 to |

| | |p. 269—4, 5, p. 270—10 |10/30 |

|10/29 |Ch 11 |p. 279—1, 2a,b,c,d,e; 3 (Table 1) |11/4 to |

| | |p. 288-290—1, 2, 3, 4, 6, 8, 12, 13, 14, 17 (Table 1) |11/6 |

|11/3 |Ch 11 |p. 295—1, 5, 9, 10 (Table 1); p. 307—1, 2(Table 1 & 4) |11/11 to |

| | |p. 321—3-3.1 & 3.2; p.320—4, 5 (Table 1), 6 |11/13 |

|11/10 |Ch 15 |p. 460-461—1, 2, 4, 7, 8c, 9 |11/18 to |

| | | |11/20 |

|11/17 |Ch 13 |p. 371-372—1, 3, 4; p. 384—1, 2, 3 |11/25 to |

| | | |11/27 |

|11/19 |Ch 13 |p. 390—1, 2, 4, 6; p.398—1, 2, 4, 6; 402—3 (use definitional formula); p. 406—9 |11/25 to |

| | | |11/27 |

|11/26 |Ch 14 |p. 414—1, 2, 4; p. 425—1, 3,; p. 433—1, 2, 3, 4, 6, 7; |12/2 to |

| | | |12/4 |

|12/1 |Ch 14 |p. 443—2; p. 444—2; p. 446—6 |12/9 in TA Mailbox |

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