University of California, Merced PSY 10: Analysis of Psychological Data Spring 2017 Class location: COB2 110 (Classroom and Office Building 2 Room 110) Class meeting time: Tuesday and Thursday 3:30 5:20pm Instructor Yang Liu Office: SSM 312B Email: yliu85@ucmerced.edu Course Website: https://catcourses.ucmerced.edu Office Hours: Friday 10am 12pm, or by appointment Teaching assistants Kathleen Coburn Office: SSM 303 Email: kcoburn@ucmerced.edu Office Hours: Tuesday 12 2pm Michelle Turitz Mitchell Office: SSM 303 Email: mturitz@ucmerced.edu Office Hours: Wednesday 11am 1pm Marcus Vadnais Office: SSM 313 Email: mvadnais@ucmerced.edu Office Hours: Monday 10am 12pm Discussion sessions CRN Course No. Meeting time Instructor 15342 PSY-010L-02 Friday, 9:30 10:20am Marcus 15343 PSY-010L-03 Monday, 9:00 9:50am Marcus 15345 PSY-010L-05 Monday, 1:00 1:50pm Michelle 15346 PSY-010L-06 Monday, 3:00 3:50pm Katie 15349 PSY-010L-08 Thursday, 6:30 7:20pm Michelle 15351 PSY-010L-10 Thursday, 8:30 9:20pm Katie 1
Course description This course provides a general and fundamental introduction to statistical methods for analyzing data in social and behavioral sciences. Scientists collect data to describe and interpret nature and human activities. To make sense of the data, statistical methods for extracting information and making inferences are needed. Statistics is seen in all aspects of everyday life, such as professional sports, insurance, financial markets, public policies, and medical procedures. Prerequisites C or higher grade in PSY 1 or COGS 1 C or higher grade in MATH 5 Required textbook Caldwell, S. (2012). Statistics unplugged (4th Edition). Cengage Learning. ISBN: 978-0840029430 Electronic version is available; however, you cannot access the tables in the appendices during quizzes Other required materials A standard calculator, which should be able to perform basic calculations as well as square roots and exponents. Note: If you fail to bring your calculator to class, you may not be able to finish quizzes or exams. Except for basic calculators, any electronic devices are prohibited during quizzes and exams One big red scantron (Student Enrollment Form) for the first quiz Skinny red scantrons (Test Form) for all other in-class quizzes, exams, and final; each student needs 12 skinny red scantrons for the course, so just buy them all at once Blank scratch paper can be brought to each quiz and exam. This course is relevant to the UC Merced Guiding Principles by teaching students Scientific literacy Given that the focus of this course is applied statistics, students will be taught various ways of presenting and analyzing statistical data. This knowledge will help them to gain an understanding of scientific and quantitative information. They will be taught how to interpret scientific information and effectively apply quantitative tools to a variety of applied contexts. Scientific literacy will be gained through inclass discussions, quizzes, homework assignment, interactive assignments in class, and exams Decision making Students will participate in in-class discussions and complete assignments related to decision-making in the context of statistical analysis. They will be taught to evaluate, 2
interpret, and use information effectively for critical analysis and problem-solving in the context of applied statistics Ethics and responsibility Ethics in statistics will be covered through lectures and assignments. Students will be taught about ethical ways of examining and reporting trends in data Course goals and outcomes Become well acquainted with various statistical tests and measures Understand and be able to communicate basic ideas in the discipline in a meaningful way by utilizing basic terms of the discipline Become familiar with basic areas of application of statistics in psychological sciences Develop a rudimentary understanding of the way statistics are used (and misused) in popular culture Understand the underlying concepts behind various statistical tests Understand the reasoning processes used by the psychologist to arrive at particular conclusions regarding human behavior Become a more independent thinker and learner How to succeed in this course? Read your textbook Come to every class on time Come to every discussion session on time Review the materials before you do homework Finish homework seriously Come to office hours if you have questions Structure of each lecture Homework assignments are due online; hard copies are not accepted Every lecture starts with a 10 15 minute review of the previous lecture The Pop-up quiz, if there is one, takes place sometime after the review but before the end of the class; the answer key is provided in class after collecting the answers There is a 5 10 minute break in the middle of the lecture Important announcements are made both in class and on CatCourses Make sure you can receive emails and announcements from CatCourses CatCourses: https://catcourses.ucmerced.edu Grading Final grade consists of three parts: (a) homework assignments, (b) quizzes, and (c) exams. The total points available are 500. Homework assignments (120 points; 24% of final grade) 3
Homework is meant to help you master the course materials and prepare for quizzes and exams (Note: If you want to do well in quizzes and exams, finish your homework carefully) There will be 6 homework assignments, published online approximately every other week; each assignment is worth 20 points In-class Quizzes (80 points; 16% of final grade) Quizzes are meant to ensure you read the textbook and finish homework on your own. Quiz questions are all from the textbook and homework, with minor variation Quizzes will take place on either Tuesday or Thursday, depending on the progress of the class. You will not be notified ahead of time about when the quiz will be given. There will be 10 in-class quizzes. Each quiz is worth 10 points Only the highest 8 quiz scores will be retained and count toward your final grade Make sure you bring the proper scantron to quizzes otherwise you will not be able to finish the quiz Students must work alone on quizzes (see section on Academic Integrity for consequences of violations) Exams (300 points; 60% of final grade) There will be 2 in-class mid-term exams and 1 final exam Each exam is worth 100 points Coverage of each exam is explained in the class schedule Students must work alone on exams (see section on Academic Integrity for consequences of violations) Extra credits Occasionally, extra credits will be given as rewards for attendance (in both lectures and discussion sessions) 5 points will be given to every student if the response rate of the course evaluation is over 80% Exam scores may be curved depending on the overall performance of the class Grading scale Letter grade Percentage Letter grade Percentage A 100 93% D+ 69.99 67% A 92.99 90% D 66.99 63% B+ 89.99 87% D 62.99 60% B 86.99 83% F <60% B 82.99 80% C+ 79.99 77% C 76.99 73% C 72.99 70% 4
Academic policies Electronic Devices in Class Electronic devices (laptops, tablets, cell phones, etc.) are not allowed in class, unless the instructor otherwise permits Late homework No makeup homework will be assigned. Unless appropriate reasons are accepted by the instructor prior to the due date, no late homework will be accepted. Instructor s permission of late submission is only granted under extreme circumstances (e.g., illness with doctor s note) When grading a late homework, a penalty factor of 0.8 will be multiplied to your original score; for example, if you receive 18/20 as the original score, the score appeared on your grade sheet will be 18 0.8 = 14.4. Only late submissions with instructor s approval will be graded this way; otherwise, any past-due assignment will receive a grade of 0. Missed quizzes No make-up quizzes will be given, unless you have three or more excused absences approved by the instructor. The purpose of dropping the two lowest quiz scores is to allow for missing up to two quizzes. Therefore, illness (and other similar incidents) will not be an excuse to make up a quiz unless you have missed three or more (with all absences excused) When grading a make-up quiz, a penalty factor of 0.8 will be multiplied to your original score; for example, if you receive 8/10 as the original score, the score appeared on your grade sheet will be 8 0.8 = 6.4. Missed exams Make-up exams will be given to students who can demonstrate that they missed the exam due to the most extreme of circumstances. If you miss an exam, you must notify the instructor at least 3 days in advance and schedule a make-up exam. If you have any emergency on the exam day, you must notify the instructor as soon as possible. Appropriate documentation must be provided before you can take the make-up exam. The Undergraduate Advising Office of School of Social Sciences, Humanities, and Arts (SSHA Advising) has the final authority in determining whether the plea warrants a make-up exam. The instructor will defer to the decision of SSHA Advising. Grade of Incomplete A grade of I (i.e., incomplete) will be assigned only in extraordinary circumstances. A written request must be filed. SSHA Advising has the final authority in determining whether the plea for I is reasonable. The instructor will defer to the decision of SSHA Advising Disability Any student who feels he or she may need an accommodation based on the impact of a disability should contact me privately to discuss his or her specific needs. Also contact Disability Services at (209) 228-7884 as soon as possible to become registered 5
and thereby ensure that such accommodations are implemented in a timely fashion Academic integrity Academic dishonesty of any kind (cheating, plagiarism, record altering, etc.) will not be tolerated and will be reported to the university. Not being aware of the related university policies is not a legitimate defense of the misconduct. Depending on how serious the problem is, academic misconduct will result in an F in the assignment or an F in the entire course. Cheating includes any attempt to defraud, deceive, or mislead the instructor in arriving at an honest grade assessment. Plagiarism is a form of cheating that involves presenting, as one s own the ideas or work of another. All work that is directly copied from other sources (e.g., a book, the www) must be in quotation marks with full reference to the original source. Words that are paraphrased from the original into your own words does not have to be in quotation marks, but must include a reference to the original source. Students who are caught cheating on a quiz or exam will be immediately asked to leave the class. The cheating incident will be reported to the Undergraduate Dean of Students, and a zero will be given for the score of the quiz/exam. Note that this policy will be upheld equally for people trying to copy work and also for people trying to help others. Tentative schedule Note: This schedule is subject to change. Date Topic Coverage Assignments Week 1 1/17 T Welcome and why statistics? Ch1 HW1 assigned 1/19 R Basic concepts in statistics Ch1 Week 2 1/24 T Display and visualize data Ch1 1/26 R Central tendency Ch2 HW1 due Week 3 1/31 T Variability Ch2 HW2 assigned 2/2 R Shape of distributions Ch2 3 Week 4 2/7 T The normal curve Ch4 2/9 R The normal curve Ch4 HW2 due Week 5 2/14 T Review 2/16 R Midterm 1 Ch1 4 Week 6 2/21 T Sampling distribution and CLT Ch5 HW3 assigned 2/23 R Sampling distribution and CLT Ch5 Week 7 2/28 T Sampling distribution and CLT Ch5 3/2 R Confidence intervals Ch6 HW3 due 6
Week 8 3/7 T Confidence intervals Ch6 HW4 assigned 3/9 R Confidence intervals Ch6 Week 9 3/14 T Hypothesis testing, basics Ch7 3/16 R One-sample Z- and t-tests Ch7 HW4 due Week 10 3/21 T Spring break, no class 3/23 R Spring break, no class Week 11 3/28 T Review 3/30 R Midterm 2 Ch4 7 Week 12 4/4 T t-test for two samples Ch8 HW5 assigned 4/6 R t-test for two samples Ch8 Week 13 4/11 T Hypothesis testing, more concepts Ch9 4/13 R Analysis of variance Ch10 HW5 due Week 14 4/18 T Analysis of variance Ch10 HW6 assigned 4/20 R Analysis of variance Ch10 Week 15 4/25 T NCME/AERA conference, no class 4/27 R NCME/AERA conference, no class Week 16 5/2 T Correlation and regression Ch12 5/4 R Correlation and regression Ch12 HW6 due Final exam 5/8 M Final exam Ch8 10, 12 6:30 9:30pm, COB2 110 7