Psychology 9A/Sociology 109
Introduction to Elementary Statistical Methods for the Study of Behavior
Spring 2016
Kevin Dooley, Ph.D.
Locations: Lecture SOCS 203 Tues 6:30-9:40 PM; Lab MBA 106 Thurs 6:30-9:40 PM
Office Hrs: SOCS 203, Tues before class (by appointment)
Email:
http://dooleykevin.com/psyc9a.html
Course Information (ECC Catalogue):
4 units; 3 hours lecture, 3 hours lab
Prerequisite: Psychology 5 or Sociology 101 and Mathematics 80 with a minimum grade of C in prerequisite
Credit, degree applicable Transfer CSU, UC*
This is a course in statistical methods and research design for the behavioral sciences. The course focuses on descriptive and inferential statistical techniques for summarizing research data and for making conclusions about the populations they represent. Students are introduced to the basic challenges and skills involved in successful undergraduate and graduate training in the behavioral sciences, including both reviewing and writing scientific research reports.
Note: Psychology 9A is the same course as Sociology 109. * Note: The maximum UC credit allowed for students completing Psychology 9A and Sociology 109 or Psychology 9A and Mathematics 150 is one course.
Course Objectives:
1. Define and differentiate the following basic concepts in research: population, parameter, sample, statistic, predictor variable, response variable (dependent), predictor (independent) variable, extraneous variable, natural (organismic or subject) variable, and operational definition, inductive reasoning, and deductive reasoning.
2. Detail the goals of statistical data analysis by explaining how models explain and predict ("account for") data and how regularities uncovered by models can lead to the discovery of underlying mechanisms of behavioral phenomena.
3. Apply American Psychological Association (APA) format by writing reports suitable in format for submission to an APA-refereed journal, including review of scientific literature, abstract, method, results, and discussion.
4. Construct and/or interpret the following numerical descriptions of data: grouped and ungrouped frequency distributions, stem plots, boxplots, bar graphs, histograms, and polygons.
5. Define, calculate, and interpret different measures of central tendency (mean, median, and mode) for different data sets, including arrays, ungrouped frequency distributions, and grouped frequency distributions.
6. Assess the mathematical characteristics of the mean in order to explain why it is the preferred measure of central tendency in many statistical applications.
7. Define, calculate, and interpret measures of variation: (range, interquartile range, sum of squares, variance, and standard deviation) for different data sets, including arrays, ungrouped frequency distributions, and grouped frequency distributions.
8. Categorize distributions in terms of skew and outliers by applying measures of central tendency and variation to calculate statistics.
9. Calculate z-scores and use them to make probability statements about ranges of scores in a normal distribution.
10. Assess error and precision by calculating and interpreting residuals, sum of squares of residuals, and mean squares of residuals.
11. Apply probability theory by (a) defining and differentiating relevant concepts such as sample space, event, outcome, mutual exclusiveness, independence, and exhaustiveness; (b) using the Addition and Multiplication Rules to calculate probabilities; and (c) calculating joint and conditional probabilities from frequency tables and explain how they can be used to infer relations between variables.
12. Apply the Central Limit Theorem to determine various aspects of a sampling distribution of a statistic, including shape, mean, variance, and standard error.
13. Define and differentiate one- and two-tailed probabilities and explain how they are related to directional and nondirectional hypotheses.
14. Identify Null and Alternative Hypotheses for various research questions and express them mathematically in the form of linear models.
15. Determine statistical significance by defining and differentiating alpha levels, p values, Type I and Type II errors and applying these concepts to decisions regarding statistical hypotheses.
16. Calculate and interpret the following: (a) single sample cases when population parameters are known (z-tests) and unknown (t-tests); (b) two-sample cases when the samples are independent and dependent (independent and correlated t-tests); (c) multi-sample (3 or more) independent cases with a single predictor variable (one-way ANOVA) and 2+ predictor variables (two-way ANOVA).
17. Conduct statistical tests by calculating and interpreting estimates of effect size, statistical power, degree of association, homogeneity of variance, and (for ANOVA) a posteriori comparisons (e.g., Tukey's HSD, Fischer's LSD).
18. Analyze and explain the advantages of multigroup and factorial research designs in comparison to single factor two-group designs.
19. Measure and apply correlation and regression by (a) defining and differentiating these two concepts; (b) explaining their application in prediction and estimation; (c) differentiating between correlation and causation; (d) calculating either a Pearson Product Moment Correlation Coefficient or a Spearman r, (depending on the level of measurement of the bivariate data); and (e) calculating a regression line and its associated statistics (i.e., residual variance, standard error of the estimate, proportion of explained and unexplained variation, coefficient of determination).
Student Learning Outcomes:
Logic of the Scientific Method. Students who finish this course with a grade of A, B, or C will be able to
identify and differentiate research methodology versus statistics/data analysis. Students will be assessed by
multiple choice exams, essay exams, oral presentations, or research-based papers.
Fundamental Principles. Students who finish this course with a grade of A, B, or C will be able to
calculate and interpret basic statistics, both descriptive (e.g., mean, Sum of Squares, variance, standard
deviation) and inferential (e.g., coefficient of determination, Cohen’s d, t-test, ANOVA, Pearson r).
Students will be assessed by multiple choice exams, essay exams, oral presentations, or research-based
papers.
Everyday Application. Students who finish this course with a grade of A, B, or C will be able to evaluate
the strengths and limitations research data in their efforts to understand everyday life experiences (e.g.,
deciding whether to decline a childhood vaccination or to modify lifestyle in view of risk factors).Students
will be assessed by multiple choice exams, essay exams, oral presentations, or research-based papers.
ADA Statement: El Camino College is committed to providing educational accommodations for students with disabilities upon the timely request by the student to the instructor. A student with a disability, who would like to request an academic accommodation, is responsible for identifying herself/himself to the instructor and to the Special Resource Center. To make arrangements for academic accommodations, contact the Special Resource Center.
Student Code of Conduct
http://www.elcamino.edu/administration/board/boarddocs/5500%20%20Academic%20Honesty.pdf
Student Rights and Grievances Procedure 5530
http://www.elcamino.edu/administration/board/policies.asp
Grade Basis
Overall grade: 75% Lecture, 25% Lab
Lecture Grade: 4 exams weighted equally. Students may construct & consult a single page of
handwritten notes (8 ½ by 11, both sides) during the 75-minute exam.
Lab Grade: 2 APA-formatted research papers (80%); various lab homework/assignments (20%)
Required Texts & Materials:
● Witte & Witte. (2015). Statistics (8th, 9th, or 10th ed.) Wiley
● American Psychological Association. Publication Manual of the APA. Sixth edition, 2nd printing (or later). Washington, D.C. (Note: Do not purchase error-filled 1st printing -- purchase 2nd printing or later)
● Calculator with basic functions and square root capability -- statistical functions not required
Week Starting / Lecture Topic / Readings1/19 / Introduction to Statistics, Graphs / Ch. 1 & 2
1/26 / Central Tendency & Variability / Ch. 3 & 4
2/2 / Normal Distributions & z scores / Ch. 5
2/9 / Review, Exam 1 (Ch. 1-5) / Ch. 6
2/16 / Correlation, Regression / Ch. 7
2/23 / Probability / Ch. 8
3/1 / Review, Exam 2 (Ch. 6-8) / Ch. 9
3/8 / Sampling Distribution, z-tests / Ch. 10, 11
3/15 / (Spring break, no class)
3/22 / Confidence intervals, 1-sample t-test / Ch. 12, 13
3/29 / Review, Exam 3 (Ch. 9-13)
4/5 / Independent & Dependent t-tests / Ch. 14, 15
4/12 / ANOVA / Ch. 16
4/19 / Chi-square / Ch. 19
4/26 / Review, Exam 4 (Ch. 14, 15, 16, 19)
5/3 / Review, Misc. Topics / Ch. 21
5/10 / Final Exam
Lab Papers Due Dates:
APA PAPER #1 Thursday, 3/24
APA PAPER #2 Thursday, 5/5
Course Policies:
● Student work (e.g., homework assignments, research papers) must be written for this current semester – anything already submitted for other courses (or past semesters of this course) is considered plagiarized and will receive 0 points. See your APA Publication Manual for ethical guidelines regarding other sources and resubmission of one’s own work.
● Exam dates are listed above--assume these dates are valid unless notified otherwise by the professor.
● Students are responsible for keeping abreast of course announcements, including any changes in exam schedule or material.
● Study guides are not provided in this class; instead, students are expected to attend lectures in an active, purposeful way – thorough, thoughtful note taking in class that will provide students with their own study guide.
● Course grades are determined solely by the requirements detailed in Grading Basis above. Extra credit may occasionally be offered on exams but is not invented at the end of the semester to make up for failing scores throughout the semester.
● Each student should bring both the text & the APA Publication Manual to all lecture & lab meetings.
ECC Policies:
● Students who enroll in class but do not attend the first scheduled class meeting may be dropped from the roster & their places given to waiting students who were unable to enroll at the time of registration. If illness or emergency prevents a student from attending the first class session, the student must contact the instructor. A student who registers for a class & never attends is still responsible for dropping the class. Failure to properly drop a class may result in a “W” & may subject the student for any & all fees associated with the class.
● Students will not be permitted to attend classes in which they are not enrolled. Exceptions may be allowed by the instructor for bonafide visitors. Students who attend a class without proper enrollment (the student did not properly register or add the class) by the published deadline will not be permitted to “late add” the class except for documented extenuating & mitigating circumstances.
● Students are expected to attend their classes regularly. Students who miss the first class meeting or who are not in regular attendance during the add period for the class may be dropped by the instructor. Students whose absences from a class exceed 10% of the scheduled class meeting time may be dropped by the instructor. However, students are responsible for dropping a class within the deadlines published in the class schedule. Students who stop attending but do not drop may still be retained on the course roster & receive a failing grade. Students may view their registration status on MyECC.
● If space is available, students who have completed registration may add a class by going to the first meeting of the class & securing permission of the instructor. It is the responsibility of the student to fulfill all requirements to add a course, & to add the course by the add deadline in accordance with college procedures. Adds will not be processed beyond the add deadline.
● Official withdrawal from class must be processed through the online system in the Admissions Office. Failure to complete this process may result in the assignment of a letter grade of A through F.
● It is the responsibility of the student to officially drop a class by the deadline date.
● January 29 is the last day to: 1) Add classes, 2) Drop for an Enrollment Fee Refund, & 3) Drop without Notation on Permanent Record. April 15 is the last day to drop with a “W”. Students should independently confirm these important dates themselves.