|Crump, Matthew||Lecture||29989||PSYC.||3400||MEAL||M,W||Whitehead 222||11:00AM - 12:15PMfirstname.lastname@example.org|
|Crump, Matthew||Lecture||29991||PSYC.||3400||MEBL||M,W||Whitehead 222||11:00AM - 12:15PMemail@example.com|
|Crump, Matthew||Lecture||29993||PSYC.||3400||MECL||M,W||Whitehead 222||11:00AM - 12:15PMfirstname.lastname@example.org|
|Crump, Matthew||Lecture||29995||PSYC.||3400||MEDL||M,W||Whitehead 222||11:00AM - 12:15PMemail@example.com|
|Crump, Matthew||Lecture||29997||PSYC.||3400||MEEL||M,W||Whitehead 222||11:00AM - 12:15PMfirstname.lastname@example.org|
|Crump, Matthew||Lecture||30004||PSYC.||3400||MEFL||M,W||Whitehead 222||11:00AM - 12:15PMemail@example.com|
|Stone, Shira||Lab||29990||PSYC.||3400||MEAB||M||James 4607||12:20PM - 2:10PM||Shira623@gmail.com|
|Alhazmi, Fahd||Lab||29992||PSYC.||3400||MEBB||M||James 5201||12:20PM - 2:10PMfirstname.lastname@example.org|
|Alhazmi, Fahd||Lab||29994||PSYC.||3400||MECB||W||James 4607||12:20PM - 2:10PMemail@example.com|
|Anderson, Kyle||Lab||29996||PSYC.||3400||MEDB||W||James 5201||12:20PM - 2:10PMfirstname.lastname@example.org|
|Stone, Shira||Lab||29998||PSYC.||3400||MEEB||F||James 4607||09:00AM - 10:50AM||Shira623@gmail.com|
|Stone, Shira||Lab||30005||PSYC.||3400||MEFB||F||James 4607||11:00AM - 12:50AM||Shira623@gmail.com|
|Week||Date||Reading||Lecture Slides||Monday Lab||Wednesday Lab||Friday Lab|
|F Jan 25||1: R Basics|
|1||M Jan 28||Chpt 1||Intro/Science||1: R Basics|
|W Jan 30||Chpt 1||DataVis||1: R Basics|
|F Feb 1||2: Intro/Graphing|
|2||M Feb 4||Chpt 2||Central Tendency||2: Intro/Graphing|
|W Feb 6||Chpt 2||Variance||2: Intro/Graphing|
|F Feb 8||3: Descriptives|
|M Feb 11||Chpt 3||Correlation||3: Descriptives|
|3||W Feb 13||Chpt 3||Regression||3: Descriptives|
|F Feb 15||Flex|
|M Feb 18||No Class|
|W Feb 20||Chpt 4||Distributions||4: Correlation|
|F Feb 22||4: Correlation|
|4||M Feb 25||Chpt 4||Sampling||4: Correlation|
|W Feb 27||Chpt 5||Foundations for inference||5: Central Limit Theorem|
|F Mar 1||5: Central Limit Theorem|
|5||M Mar 4||Chpt 5||Missed Class due to snow||5: Central Limit Theorem|
|W Mar 6||Chpt 5||Randomization test||6. Hypothesis Testing|
|F Mar 8||6. Hypothesis Testing|
|6||M Mar 11||Chpt 6||one-sample t tests||6. Hypothesis Testing|
|W Mar 13||Chpt 6||paired sample t-tests||7. T-tests 1|
|F Mar 15||7. T-tests 1|
|7||M Mar 18||Chpt 6||Independent t-tests||7. T-tests 1|
|W Mar 20||Chpt 12||Power and Effect-size||Midterm Study|
|F Mar 22||Midterm study|
|8||M Mar 25||Midterm Review||Midterm Study|
|W Mar 27||Midterm||8. T-tests 2|
|F Mar 29||8. T-tests 2|
|9||M Apr 1||Chpt 7||One-factor ANOVA I||8. T-tests 2|
|W Apr 3||Chpt 7||One-factor ANOVA II||9. One-way ANOVA|
|F Apr 5||9. One-way ANOVA|
|10||M Apr 8||Chpt 8||Repeated measures ANOVA I||9. One-way ANOVA|
|W Apr 10||Chpt 8||Repeated measures ANOVA II||10. RM ANOVA|
|F Apr 12||10. RM ANOVA|
|11||M Apr 15||Chpt 9||Factorial ANOVA I||10. RM ANOVA|
|W Apr 17||Chpt 9||Factorial ANOVA II||Flex|
|F Apr 19||Spring Recess|
|M Apr 22||Spring Recess|
|W Apr 24||Spring Recess|
|F Apr 26||Spring Recess|
|M Apr 29||Chpt 10||Factorial ANOVA III||11. Factorial ANOVA|
|13||W May 1||Chpt 10||Mixed Design ANOVAs||11. Factorial ANOVA|
|F May 3||11. Factorial ANOVA|
|M May 6||Chpt 10||Chpt 10||12. Mixed ANOVA|
|14||W May 8||R Markdown||12. Mixed ANOVA|
|F May 10||12. Mixed ANOVA|
|M May 13||Reproducible Science||5: Central Limit Theorem|
|W May 15||Final Review||flex|
|M May 20||M May 20 10:30AM - 12:30 PM||Final Exam|
2 hours lecture, 4 hours laboratory, 4 credits
Basic descriptive and inferential statistics including the elements of experimental designs in psychological research. STEM variant course - Satisfies Pathways Required Core Math and Quantitative Reasoning requirement.
My goal is for you to learn:
How to answer research questions in Psychology with data
The basics of research designs in psychology, and how they relate to data-analysis strategies
an intuitive, practical, and conceptual understanding of strategies for asking and answering questions with data
How to use R, a free and open-source statistics software program.
NOTE: The schedule and procedures described in this syllabus are subject to change in the event of extenuating circumstances. You will always be notified of changes both in class AND by posts to the class website. Your enrollment in the course represents your acknowledgment and acceptance of the non-negotiable policies described in the syllabus.
The textbook for this course is “Answering questions with Data”, it is FREE and available online as a web-book.
The lab manual for this course is also free, and is available online as a web-book.
Supplementary material will be posted on the course website. For example, check out the resources page on this website.
There will be two, 1 hour 15 minute, lectures each week. The lecture covers material that is available in the text book. The course schedule outlines chapters that should be read prior to each lecture. It is very important to read the textbook before you come to lecture. I’ve said it twice, now again. Read the assigned parts of the textbook before each lecture. Read it at home, read it on the bus, read it in a tree, read it at the library. Just read it.
You will be tested on material from the lectures and textbook in two exams: a midterm, and a cumulative final exam.
There will be one two hour lab each week (1 hour 50 minutes). Every week you will be completing a structured set of activities that we have planned for you in the lab manual. This is where you will spend time learning how to use computer software, in particular R, and R-studio, to do statistics on real data.
Your final grade combines your performance in the lab and lecture portions of the course. The percentage grade is determined from the following components.
Percentage grades are converted to letter grades according to the following rubric.
The course allows for some flexibility in determining your final grade. If you perform better on the final exam than on the midterm, you may replace the midterm grade with your higher final grade (the reverse does not apply).
The instructor reserves the right to determine whether the final grade depends more heavily on a scale or a curve.
As you can see, your lab work takes up 40% of your entire grade. Compared to everything else, this is the single biggest part of your entire grade. There are 11 graded labs.
The lab work for each week is split up into three parts. Your grade for each lab will be broken down as follows (4 total points for each lab).
The whole point of the labs is to train you how to do things. You will notice that half of the lab is pass/fail, you just have to show up and follow along, and hand in your work to get half of the grade. The third part is graded, but you will see why in a moment, we’re giving you practice for the kinds of the questions you will see on the midterm and final.
Part 1. Learn 1 point
Part 1 grading is pass/fail:
Part 1 activities: You will follow the step-by-step instructions in the lab manual to complete data analysis tasks using R. Don’t worry this is actually pretty easy, we are mainly asking you to copy/paste things and press enter.
Part 2. Generalize 1 point
Part 2 grading is pass/fail:
Part 2 activities: After you see how we did something in Part 1, you try to do something very similar in part 2. You will show your work in a file that we give you. You may or may not be able to successfully complete the generalization assignment. That is OK. You will pa
Part 3. Think and write 2 points
The third part of each lab will have some questions that require written answers. Your answers to these questions will be graded by your TA, who will give you feedback on your answers.
Each question will come with a clear rubric about how the question will be graded.
Each week you will be given an online quiz on Blackboard. It will typically be around 10 questions about the material for that week. Here are some things you should know about the quizzes:
You will have the entire week to complete the quiz, and you will be able to take the quiz over and over as many times as you want.
Your grade on the quiz will always be taken from the last attempt.
Many of the quiz questions, or very similar ones, will be on the midterm and the final. The purpose of the quizzes is to give you practice with the kinds of questions that will be on the midterm and final. If you are wondering what kinds of questions are going to be on the midterm and final, you will find out by taking the quizzes.
Everyone has questions about the midterm and final. Here are the answers to all of your questions. You already know the midterm is worth 20% of your final grade, and your final exam is worth 25% of the final grade.
Q. What’s on the exams? A: the midterm and final have the same structure. Half of each exam is multiple choice questions, the other half is long-answer questions
Q. What kind of multiple choice questions, I need examples… A: All of the MC questions on the midterm and final will be like the ones in your weekly quizzes, which you can do over and over again. Yes, some of the midterm and final questions will be very similar (or even identical except for slightly different values) to the ones from the quizzes
Q. What kind of long-answer questions, I need examples and feedback: The long-answer questions will be very similar, and sometimes the same as the long-answers you write for Part 3 of each lab. You will get feedback from the lab instructor each week about your answers to those questions. In general you will have about 6-7 weeks of feedback on your answers before you take the exams.
Q. Is the final cumulative? A: Yes, but it contains more things from the second half of the semester, roughly 75% second half things, and 25% first half things.
Q. Is there some deal about the final and midterm, is this true? A: Yes, if you perform better on the final exam than on the midterm, I will automatically replace your midterm grade with your higher final grade. Let’s say you got 75% on the midterm and 85% on the final. I will then automatically give you 85% on both the midterm and final. However, the reverse does not apply. If you got 85% on the midterm, and 75% on the final, you will receive those grades with no changes.
Lecture and Lab attendance is taken every lecture and lab.
You will LOSE points on your quizzes and lab assignments for NOT ATTENDING LECTURE AND LAB.
If a student is late or misses more than 3 classes, then each additional late/missed class will result in subtracting 1% from the 25% for the Weekly quizzes. We know that life happens and sometimes you can’t make it to class. We are giving you you three classes where you can miss (because of things happening in your life that we don’t need to know about) without having any impact on your grade (all lecture notes are online for missed classes, talk to a friend, read the textbook, etc.)
Lecture attendance is taken every lecture at the very beginning of class. Latecomers who miss attendance will not be allowed to record their attendance, and will be recorded as absent.
Late Labs: Unless you have contacted your lab instructor regarding serious extenuating circumstances, there will be a penalty of .25 per day up to a total of 2 points for late labs. This means that it is in your best interests to complete the lab, even late, as you can still receive up to 2 points (50% of the grade). However, no lab reports will be accepted after three weeks beyond the due date. Labs not submitted by three weeks past the due date will receive a zero.
The faculty and administration of Brooklyn College support an environment free from cheating and plagiarism. As a student, you are personally responsible for being aware of what constitutes cheating, and plagiarism; and, for avoiding both. You can view the complete text of the CUNY Academic Integrity Policy here: http://www.brooklyn.cuny.edu/bc/policies If a faculty member suspects a violation of academic integrity, and upon investigation, confirms that violation, or if the student admits the violation, the faculty member MUST report the violation.
Make-up exams will be given only when there is a “good” reason for having missed an exam. For example, if a sudden illness causes you to miss an exam, then you should be prepared to provide me with a brief note signed by your physician. Contact me before an exam in the event that you anticipate missing one. In the event of an emergency, contact me as soon as possible. If you are missing a class for religious reasons refer to the state law regarding non-attendance because of religious beliefs (p. 64 in the Undergraduate Bulletin or p. 40 of the Graduate Bulletin).
WARNING: This is not the kind of course for which you do not need to come to class, and read the textbook at the last minute and expect to do well on tests and papers. The material in this course builds in complexity across classes, and doing well in this course will require a constant moderate level of effort. If you join the course later or are unsure about anything please ask.
It is important to me that the course be accessible to all students. In order to receive disability-related academic accommodations students must first be registered with the Center for Student Disability Services. Students who have a documented disability or suspect they may have a disability are invited to set up an appointment with the Director of the Center for Student Disability Services, Ms. Valerie Stewart-Lovell at 718-951-5538. If you have already registered with the Center for Student Disability Services please provide me with the course accommodation form so we may discuss your specific accommodation. A guide and more information can be found here http://catsweb.cuny.edu
Your cell phone, PDA or other device must be turned off during class. If you are a habitual offender in this respect (i.e. it happens more than twice during the semester), you will be asked to leave the classroom. If you absolutely need to have your phone on during class—talk to me at the beginning of the semester.
Please pick up after yourself. Absolutely no food is allowed in the lecture and lab rooms.
I will regularly use e-mail to send out announcements, changes in the syllabus, reminders about tests or due dates etc. It is your responsibility to check e-mail regularly to keep up-to-date with these announcements. I will use the e-mail address you have listed with the College. Therefore, please make sure that this is indeed the correct address.
The Library maintains a collection of links to sites that can assist you with proper citation format and paraphrasing and quoting other authors at Research & Writing Help. The Learning Center has writing tutors available to help you with your writing http://lc.brooklyn.cuny.edu/.
The best learning is done in conversation with others, whether they are people—classmates, teachers, friends—or texts—books, articles, essays, poems, films etc. It should not be a solitary process. However, the assignments that you hand in for this course must be done on your own, should represent your own thinking, and should be original work that you have done for this particular course. A good way to balance these two seemingly contradictory approaches (collaborative learning and original individually-produced work) without knowingly—or, even unwittingly—resorting to plagiarism or other forms of academic misconduct is to learn and meticulously observe the rules for citing the work of others (this could be the great point your roommate made that you used in your paper, it could be a well-turned phrase from an academic essay, or it could be anything in between). It is your responsibility to learn what constitutes plagiarism and the correct rules for citing sources—read the information on the following website carefully: http://www.brooklyn.cuny.edu/bc/policies/. The bottom line is: passing off anyone’s words or ideas as your own for any reason whatsoever is plagiarism.