2810-650
Psychology 2810-650
Statistics for Psychology
If there is a discrepancy between the outline posted below and the outline posted on the OWL course website, the latter shall prevail.
1.0 CALENDAR DESCRIPTION
Introduction to data analysis with particular reference to statistical procedures commonly used in psychological research.
Antirequisites: Biology 2244A/B, Economics 2122A/B, 2222A/B, Geography 2210A/B, Health Sciences 3801A/B, MOS 2242A/B, Psychology 2820E, 2830A/B, 2850A/B, 2851A/B, the former 2885, Social Work 2207A/B, the former 2205, Sociology 2205A/B, Statistical Sciences 2035, 2141A/B, 2143A/B, 2244A/B, 2858A/B and the former 2122A/B (and Statistical Sciences 2037A/B if taken before Fall 2010)
Antirequisites are courses that overlap sufficiently in content that only one can be taken for credit. So if you take a course that is an antirequisite to a course previously taken, you will lose credit for the earlier course, regardless of the grade achieved in the most recent course.
Prerequisites: One full course in mathematics plus at least 60% in a 1000-level Psychology course. To fulfill the mathematics requirement you must complete a full course equivalent by taking 1.0 course from among the following courses: Applied Mathematics 1201A/B or the former Calculus 1201A/B, Mathematics 0110A/B, 1120A/B, 1225A/B, 1228A/B, 1229A/B, 1600A/B, Calculus 1000A/B, 1100A/B, 1301A/B, 1500A/B, 1501A/B, the former Linear Algebra 1600A/B, Statistical Sciences 1024A/B, the former Mathematics 030 and 031.
If Mathematics 0110A/B is selected, then either Statistical Sciences 1024A/B or Mathematics 1228A/B must be taken. The combination of Mathematics 1228A/B and Statistical Sciences 1024A/B is strongly recommended.
1.0 course
Unless you have either the prerequisites for this course or written special permission from your Dean to enroll in it, you may be removed from this course and it will be deleted from your record. This decision may not be appealed. You will receive no adjustment to your fees in the event that you are dropped from a course for failing to have the necessary prerequisites.
2.0 COURSE INFORMATION
Co-Instructor: Dr. Tony Vernon
Office and Phone Number: 6302 SSC 519-661-3681
Office Hours: by appointment
Email: vernon@uwo.ca
Co-Instructor: Livia Veselka
Office: SSC 7440
Office Hours: by appointment
Email: lveselka@uwo.ca
Course Coordinator: Dr. Tony Vernon
Teaching Assistant: Breanna Atkinson
Office: 6301 SSC
Office Hours: by appointment
Email: batkin3@uwo.ca
Teaching Assistant: Kristi Chin
Office: 9334 SSC
Office Hours: by appointment
Email: kchin25@uwo.ca
Teaching Assistant: Tram Nguyen
Office: 7245 SSC
Office Hours: by appointment
Email: tnguye95@uwo.ca
If you or someone you know is experiencing distress, there are several resources here at Western to assist you. Please visit: http://www.uwo.ca/uwocom/mentalhealth/ for more information on these resources and on mental health.
Please contact the course instructor if you require material in an alternate format or if you require any other arrangements to make this course more accessible to you. You may also wish to contact Services for Students with Disabilities (SSD) at 519-661-2111 ext 82147 for any specific question regarding an accommodation.
3.0 TEXTBOOK
McClave & Sincich, Statistics (13th edition). N.B. The text is optional for this section of the course
4.0 COURSE OBJECTIVES
At the completion of this course you will have been exposed to a wide variety of statistical methods for analyzing data obtained from different types of experiments. This should enhance your ability to critically read and evaluate research reports and to conduct your own research.
4.1 STUDENT LEARNING OUTCOMES
The goal of this course is to enable students to demonstrate:
- that they know how to use a number of mathematical and statistical formulas to compute different statistics and related values
- that they know how to perform a variety of statistical and data analytic procedures "by hand" (not on a computer)
- that they can correctly calculate probabilities, evaluate probability distributions and carry out hypothesis testing/estimation procedures
- that they are able to recognize when it is appropriate to perform and then to successfully perform a number of statistical analyses including Z-tests, t-tests, F-tests (all varieties), chi-square tests, and regression/correlation analyses
- that they know how to analyze data and draw correct interpretations from the analyses in a variety of experimental and non-experimental contexts
The ways in which students will be assessed in order to evaluate the extent to which they have achieved these goals will include assignments, quizzes, and exams, and these will need to be completed within the times specified.
5.0 EVALUATION
This course consists of 12 units presented in 19 lectures, which are described below. Each lecture is designed to be completed in one week. At the end of each lecture you will be given a number of assignment questions, which you need to complete on a pass/fail basis before you begin the next lecture. There will also be six quizzes – each based on approximately one or two units – and these need to be completed and submitted and they will be graded and count towards your course mark. Finally, there will be three exams, all three of which will be written on campus or at an approved exam centre. The first exam will be on Saturday November 19 2016, the second will be on Saturday February 4 2017, and the third will be during the final exam period (April 9-30, 2017).
Final scores and grades will be assigned as follows:
Quizzes 10%
Exam 1 25%
Exam 2 30%
Exam 3 35%
100%
N.B. Make-up quizzes and exams will not be scheduled except for documented medical or compassionate reasons
None of the assignments, quizzes, or exams is multiple-choice. Instead, you will be given word problems and you will need to perform numerical computations and to write out detailed answers. The format of the quizzes and the exams will be exactly the same as the assignments, so once you have done one or two assignments, you will be familiar with the format.
VERY IMPORTANT: At the end of the course, in order to get credit for your quiz and exam marks you MUST have completed and passed ALL of the assignments. Each week you need to submit your assignment on-line before the deadline (11:55pm on the Friday of each week) and you need to have attempted to answer every question on the assignment or your assignment will be considered to have been submitted late. Late assignments will be accepted HOWEVER EACH LATE ASSIGNMENT WILL COST YOU A 3% DEDUCTION FROM YOUR OVERALL COURSE GRADE. If any assignments have not been passed by Friday April 7, 2017 you will not receive credit for your quiz or exam marks and you will therefore fail the course.
Although the Psychology Department does not require instructors to adjust their course grades to conform to specific targets, the expectation is that course marks will be distributed around the following averages:
70% 1000-level and 2000-level courses
72% 2190-2990 level courses
75% 3000-level courses
80% 4000-level courses
The Psychology Department follows the University of Western Ontario grading guidelines, which are as follows (see http://www.uwo.ca/univsec/pdf/academic_policies/general/grades_undergrad.pdf ):
A+ 90-100 One could scarcely expect better from a student at this level
A 80-89 Superior work that is clearly above average
B 70-79 Good work, meeting all requirements, and eminently satisfactory
C 60-69 Competent work, meeting requirements
D 50-59 Fair work, minimally acceptable
F below 50 Fail
6.0 TEST AND EXAMINATION SCHEDULE
Quiz 1: Friday September 30, 2016: available on-line from 12 noon until 9pm.
Quiz 2: Friday October 21, 2016: available on-line from 12 noon until 9pm.
Exam 1: Saturday November 19, 2016 at 2pm on UWO campus (Elborn College room 2168A&B) or at an approved exam centre
Quiz 3: Friday December 2, 2016: available on-line from 12 noon until 9pm.
Quiz 4: Friday January 13, 2017: available on-line from 12 noon until 9pm.
Exam 2: Saturday February 4, 2017 at 2pm on UWO campus (Elborn College room 2168A&B) or at an approved exam centre
Quiz 5: Friday March 10, 2017: available on-line from 12 noon until 9pm.
Quiz 6: Friday March 31, 2017: available on-line from 12 noon until 9pm.
Exam 3: Will be scheduled by the registrar during the final exam period (April 9-30, 2017): on UWO campus or at an approved exam centre
7.0 CLASS SCHEDULE
Unit 1: Introduction and descriptive statistics I:
Lectures 1 and 2 (weeks of September 12 and 19)
In this unit you will meet the instructors – Dr. Tony Vernon and Livia Veselka - and they will describe the nature of the course and go through the course outline with you. You will then be introduced to some statistical terminology, and, in lecture 2 you will be given an introductory lecture on descriptive statistics. This will include learning how to compute measures of central tendency (the mean, the median, the mode, and the grand mean); measures of variability (the range, the standard deviation, and the variance); and two ways to manipulate data (the scale and the translation theorems) and the effects that these have on the mean and the standard deviation. Note: the first assignment will be given out the week of September 19; there is no assignment during the week of September 12.
Unit 2: Descriptive statistics II:
Lecture 3 (week of September 26)
This unit will continue looking at descriptive statistics and, in particular, will focus on different ways to interpret the standard deviation. Topics to be covered will include mound-shaped symmetrical distributions (MSSDs), percentiles, interpolation, Z scores, and asymmetrical distributions and Chebyshev’s theorem. A quiz covering Units 1 and 2 will follow.
Unit 3: Probability I:
Lecture 4 (week of October 3)
In this unit we will cover the basic formulas and procedures that allow us to estimate the probability of different types of events. We will start with some definitions of terms that you need to be familiar with: including random sampling, sampling with and without replacement, simple events, complementary events and a-priori probability. You will then learn several formulas that allow you to find the probability of simple events, compound events, conditional events, and independent and dependent events. You will also be shown how to use these formulas to create tree diagrams. The unit will conclude with a number of practice questions
Monday October 10 is Thanksgiving and there will be no lecture or assignment this week.
Unit 4: Probability II:
Lecture 5 (week of October 17)
In this unit you will learn a number of counting rules, which will assist you in computing the probability of different events. Specific topics will include permutations, partitions, combinations, and the hypergeometric formula. We will then work through a number of example questions and a quiz covering Units 3 and 4 will follow.
The week of October 24 includes the fall study break so there will be no lecture or assignment this week
Unit 5: Discrete random variables:
Lectures 6 and 7 (weeks of October 31 and November 7)
This unit will introduce discrete variables in lecture 6, and will show how to generate their probability distributions and compute their mean and standard deviation. In the second part of lecture 6, a special case of discrete variables – binomial variables – will be introduced. In lecture 7 this unit will conclude with an introduction to hypothesis testing, and the concepts of Type I and Type II errors will be illustrated in the context of binomial experiments.
The week of November 14 will be a review week during which students can prepare for the first exam. An on-line package of review questions will be available for students to work on but these do not need to be submitted for grading
The first exam will be at 2pm on Saturday November 19. This exam will cover all of the material presented in the first 5 Units. Reminder: this exam will be written on campus (Elborn College room 2168A&B) or at an exam centre.
Unit 6: Continuous random variables:
Lecture 8 (week of November 21)
In this Unit we will cover the counterpart to discrete variables, namely continuous variables. Topics will include the normal distribution and Z scores and the use of Z tables to find percentiles and p-values without having to use interpolation. This Unit will also cover the normal approximation to the binomial distribution.
Unit 7: Introduction to inferential statistics:
Lecture 9 (week of November 28)
A large part of the course will be devoted to inferential statistics and this unit will introduce students to this topic. We will illustrate how to create sampling distributions, and how to use these sampling distributions to form confidence intervals to estimate an unknown population mean from sample data. Following this lecture there will be a quiz covering Units 6 and 7.
Following Unit 7 classes end on December 7 so there will be no more lectures or assignments until January, 2017.
Unit 8: Hypothesis testing I:
Lecture 10 (week of January 9)
This unit will build upon the concepts covered in Unit 7 and will show students how to perform “real-life” hypothesis tests about a population mean. The methods covered in this unit will provide the foundations for the entire rest of the course so this is probably the single most important unit in the course. Specific procedures to be covered will be the large sample Z test about mu and Type I and Type II errors in the context of large-sample hypothesis tests. Because this Unit is so important it will be followed by a quiz devoted just to the material presented in it.
Unit 9: Hypothesis testing II:
Lectures 11 and 12 (weeks of January 16 and 23)
This unit will build on the topics covered in Unit 8 and will illustrate five new hypothesis testing procedures. In lecture 11 you will learn the small-sample t test about mu and the single-sample Z test about proportions. In lecture 12 you will learn the 2-sample Z test of the difference between two population means, the 2-sample t test of the difference between two population means, and the F test for the equality of 2 variances. At the end of this unit, students should be completely familiar with the stages involved in hypothesis testing.
The week of January 30 will be a review week during which students can prepare for the second exam. An on-line package of review questions will be available for students to work on but these do not need to be submitted for grading
The second exam will be at 2pm on Saturday February 4. This exam will cover all of the material presented in Units 6-9 inclusively. Reminder: this exam will be written on campus (Elborn College room 2168A&B) or at an exam centre.
Unit 10: Hypothesis testing III:
Lectures 13 (week of February 6)
In this Unit, three new hypothesis testing procedures will be covered: the Wilcoxon test of the difference between two population means, the matched pair/dependent samples t test, and the single-sample chi-square test of a variance.
Unit 11: Hypothesis testing IV:
Lectures 14, 15, and 16 (weeks of February 13, 27, and March 6). Note that reading week is the week of February 20 so there is no lecture or assignment that week.
This Unit will cover the analysis of variance (ANOVA). Specific topics will include between-subjects ANOVA (lecture 14), post hoc and planned comparison procedures (lecture 15), and repeated-measures/within-subjects ANOVA (lecture 16). Following this there will be a quiz covering just the material in Unit 11.
Unit 12: Hypothesis testing V:
Lectures 17, 18, and 19 (weeks of March 13, 20, and 27)
In this final Unit we will be covering correlation and regression (lectures 17 and 18) and chi-square tests of proportions and contingency tables (lecture 19). Following this there will be a quiz covering the material in Unit 12.
Following Unit 12 students will take the third of 3 exams during the final exam period (April 9-30). This exam will cover all of the material presented in Units 9, 10, 11, and 12. Reminder: this exam will be written on campus or at an exam centre.
Format of the course:
The way we have designed this course is a bit different from most Distance Studies courses. We have made a video of each lecture so, on your computer, you can view the lectures as if you were in an actual classroom. In place of static PowerPoint slides, you will actually see the lecture notes on your computer screen in a similar manner as you would if they were being written on a blackboard. You can pause or rewind the lectures at any point if you wish to go over something a second time and you can refer to handouts, which, for example, contain example questions that are being discussed in the lectures.
Although all the notes are contained within each lecture and can be reviewed as often as you wish, we strongly recommend that you simulate the classroom experience by taking notes exactly as you would in a classroom setting. We do not require you to this but, in our experience, you will gain a much quicker and better mastery of the material if you take your own notes and this, in turn, will allow you to perform better on assignments, quizzes, and exams.
In addition to the lectures, we have set up an on-line discussion board, which you can access at any time. On this board, you can type in questions regarding any of the lecture material or to request assistance on any of the assignment questions. The instructors will monitor the discussion board and answer your questions on a daily basis. This board is interactive in that you will each be able to see other students’ questions (and our answers to these) and you can also post questions/answers to one another.
8.0 STATEMENT ON ACADEMIC OFFENCES
Students are responsible for understanding the nature and avoiding the occurrence of plagiarism and other scholastic offenses. Plagiarism and cheating are considered very serious offenses because they undermine the integrity of research and education. Actions constituting a scholastic offense are described at the following link: http://www.uwo.ca/univsec/pdf/academic_policies/appeals/scholastic_discipline_undergrad.pdf
As of Sept. 1, 2009, the Department of Psychology will take the following steps to detect scholastic offenses. All multiple-choice tests and exams will be checked for similarities in the pattern of responses using reliable software, and records will be made of student seating locations in all tests and exams. All written assignments will be submitted to TurnItIn, a service designed to detect and deter plagiarism by comparing written material to over 5 billion pages of content located on the Internet or in TurnItIn’s databases. All papers submitted for such checking will be included as source documents in the reference database for the purpose of detecting plagiarism of papers subsequently submitted to the system. Use of the service is subject to the licensing agreement, currently between Western and Turnitin.com http://www.turnitin.com
Possible penalties for a scholastic offense include failure of the assignment, failure of the course, suspension from the University, and expulsion from the University.
9.0 POLICY ON ACCOMMODATION FOR MEDICAL ILLNESS
Western’s policy on Accommodation for Medical Illness can be found at:
http://www.westerncalendar.uwo.ca/2016/pg117.html
Students must see the Academic Counsellor and submit all required documentation in order to be approved for certain accommodation:
http://counselling.ssc.uwo.ca/procedures/medical_accommodation.html
10.0 OTHER INFORMATION
Office of the Registrar web site: http://registrar.uwo.ca
Student Development Services web site: http://www.sdc.uwo.ca
Please see the Psychology Undergraduate web site for information on the following:
http://psychology.uwo.ca/undergraduate/student_responsibilities/index.html
- Policy on Cheating and Academic Misconduct
- Procedures for Appealing Academic Evaluations
- Policy on Attendance
- Policy Regarding Makeup Exams and Extensions of Deadlines
- Policy for Assignments
- Short Absences
- Extended Absences
- Documentation
- Academic Concerns
- 2016 Calendar References
No electronic devices, including cell phones, will be allowed during exams.
