STATISTICS SYLLABUS - PSY/POL/SOC 200 010
Fall 2023 (2238)

(on D2L the PSY, POL, and SOC sections are combined as PSY)

Lecture - M and W - 1:00 - 2:50 - OM 297
Labs - At ends of some lectures - OM 297

Professor: Dr. Robert S. Ryan

Office: 385 Old Main

Office hours: Tues. 12 - 1:30; Wed. 12 - 2; Thurs. 12 - 1:30. You are welcome to drop in at my office, 385 Old Main, any time to try to catch me. I can usually take a few minutes to help you unless I am tied up with something very important or time sensitive. It doesn't have to be during my office hours. You can drop in any time I'm not teaching, in a meeting, or busy with some other commitment (use the links to my teaching schedule to see when I'm teaching, and then email me with a time that looks like it will work for both of us. I'll check to make sure it doesn't conflict with any other time commitment and get back to you). However, if you are going out of your way to see me, whether during my office hours or not, then it is always best to call me at 484-646-4325 right before you want to come, just in case I am not available because of something unexpected. For example, I could be with another student who just stopped in. If you call or visit my office during a time you thought you could catch me and find that I am not there right at that moment or I don't answer the phone, don't assume I'm not available. First, knock on my door if it is closed. Also, I could have just stepped away from the office or my phone for a few minutes. So if you don't see me in my office, and I don't answer when you knock or answer the phone when you call, always wait at least a few minutes and try again.


KU Office Phone: 484-646-4325 (It's better to use E-mail)
Home Phone: Email me first, and we'll set up a call to my home phone if necessary

E-mail:
rryan@kutztown.edu

Website:
http://faculty.kutztown.edu/rryan



Required: Mind Tap with e-book Text

MindTap is a required component of this class. Mind Tap is the online platform of Cengage, the publisher of the textbook. It provides access to the text as an e-book, as well as providing other very useful learning activities.


Instructions for registering for the course on MindTap

Course: Statistics for the Social and Behavioral Sciences section 010 FA 23

Instructor: Robert Ryan

This course requires an online learning platform called MindTap. Follow the instructions below to get started.

Register for your MindTap Course
1. Use the course registration link https://student.cengage.com/course-link/MTPQR6CZDX2M
2. Follow the instructions on screen to create your Cengage account and register for this MindTap course.
3. Begin your temporary access* period.

Need help? Visit the Cengage Start Strong Website (https://startstrong.cengage.com) for step-by-step instructions.

*Temporary Access: You can access your MindTap course until 4:00 AM (UTC) on 9/4/2023 for free. At the end of the temporary access period, you will be prompted to purchase access. Your work will be saved and will be available to you again once you’ve completed your purchase.

NOTE: The cost of your course materials is included in your tuition, you will not need to make a separate purchase to access (unless you opted out of inclusive access).

MindTap Tips & Training Tools

Learn more about navigating your MindTap course: (https://help.cengage.com/mindtap/mt-student/introduction.html)

Technical Support & Troubleshooting

Our US-based support team delivers answers and advice via 24/7 online chat, Twitter, live phone support (1-800-354-9706) and through support.cengage.com, which includes helpful articles, and tutorials.

If you are having trouble loading MindTap, run the MindTap browser check (https://ng.cengage.com/static/browsercheck/index.html) to make sure your browser is compatible or refer to the MindTap System Requirements (https://help.cengage.com/mindtap/MindTap-System-Requirements.pdf). If MindTap isn’t loading, be sure to visit Techcheck (https://techcheck.cengage.com) to see if there is an outage.


Survival tips for the course: I want every student to succeed in this course! Students can do well by following the good advice below: 

Brush up on your algebra. Self-paced materials are on D2L in Content/Important information/Algebra brush up materials/self_pretest_review_materials_posttest.
There is also a Basic Mathematics Review on MindTap. It is in the first module "Course Support."

Do all the basics. Attend all classes Set aside time to read the text and do the MindTap assignments. Ask questions in class as soon as you don't understand anything, or email me your questions.

Don't fall behind. Assess your understanding early and get help immediately if you are having trouble.

Use all the resources you can. The Psychology department has Graduate Assistants that tutor Statistics students. There is information about them on D2L, and their email is psychga@kutztown.edu. You may also be able to ask the tutoring center for a tutor. Try going to https://www.kutztown.edu/about-ku/administrative-offices/student-success-center/tutoring-services.html

Study with other students so you can quiz each other.

Practice, Practice, Practice. Statistics becomes clearer the more you do it. Do practice problems from the text, make up your own little practice problems. Work in groups and give each other practice problems. Practice, Practice, Practice.

More importantly, in addition to practicing procedures, make sure you understand the concepts underlying how the procedures work. The reason for practicing the procedures is not just to learn how to do them. Only a few questions on tests will require you to do the procedures. The reason for practicing the procedures is mostly to help you understand the concepts behind them. Most of the test questions will be about the concepts behind the procedures.

You can email me (rryan@kutztown.edu) to set up a one on one meeting with me for extra help.

CASA is here to help! The Center for Academic Success & Achievement (CASA) provides students with individualized success plans, study skills support, and connections to campus resources.  The CASA website, https://www.kutztown.edu/about-ku/administrative-offices/student-success-center.html, has valuable links and resources.

Course description: The purpose of this course is to introduce the student to the concepts of descriptive and inferential statistics.  The results of any research should be summarized by appropriate descriptive statistics such as central tendency, variability, and the shape of the distribution.  Relationships will be studied using correlation, regression, and chi-square.  Research which involves sampling will be analyzed by appropriate inferential statistics such as t-tests and ANOVA.  Sampling error, hypothesis testing, interval estimation, measures of effect size, significance levels, Type I Error, Type II Error, and power will be discussed.  In addition, the student will be introduced to SPSS for Windows, Microsoft Excel, and/or other appropriate software for performing descriptive and inferential statistical procedures presented throughout the course. PREREQUISITES:  PSY 011 (Psych majors need a C or better).



Course objectives:

Students will:

1.   State the correct type of representation for different types of data
2.   Explain the importance of the scale on the X and Y axes of a graph
3.   Construct a frequency distribution table or graph and use it to critically examine central tendency, variability, and shape
4.   Produce graphs with a statistical program
5.   Given a description of a research situation, select the appropriate measures (of central tendency and variability) and select the appropriate inferential test (from among the one sample z test, one sample t test, two independent samples t test, paried t test, one way ANOVA, correlation, and chi square test of independence)
6.   Compute the correct statistical measure or test by hand and with a statistical program
7.   State the correct evaluation of descriptive measures and inferential tests
8.  Write up the results of descriptive measures and inferential tests in APA format
9.  Explain that a p value is the probability that the data that actually was obtained occurred only by chance, that is, how likely is it that the data would have been obtained if the null hypothesis were true.
10. Articulate the distinction between statistical significance and practical importance
11. Describe how sample size, the difference between means, and the variability within groups influence statistical significance
12. Determine whether a result is statistically significant or not by examining the output of a statistical program



Summary of class policies.
(For complete class policies, see http://faculty.kutztown.edu/rryan/policies.htm)

Academic Honesty: It is my intention to uphold the academic honesty policy of Kutztown University and all other student conduct standards as described in the online student handbook, "The Key". "Academic dishonesty involves any attempt to obtain academic credit or influence the grading process by means unauthorized by the course instructor". It is the responsibility of students to be aware of this policy and abide by it at all times.

Use of AI, such as ChatGPT:

If you wish to risk using Generative AI in your writing, you should be aware that you will be held personally responsible for the clarity and rationality of the writing. Consider the following example:

An author named Norman Solomon recently published a book entitled "War Made Invisible: How America Hides the Human Toll of Its Military Machine." It is about how the media report on war so as to make the general public accept it.

Generative AI was used to produce a summary of the book. The first sentence of the AI generated summary was, "The U.S. media coverage that makes it easier to sell wars to the public, as well as the often-hidden cost of civilian casualties from errant U.S. attacks, are all harshly criticized by journalist Solomon." Not bad. But the second sentence was, "He guarantees that when Russia designated Ukrainian communities during the new attack, the U.S. media was everyone available and jumping into action with compassionate, piercing revealing."

Your real capability, however imperfect you might think it is, might be preferable to so-called artificial intelligence.


Students with Disabilities: The Office of Human Diversity, located in 220 Stratton Administration Center, provides many services for students with disabilities. If you have a documented disability please speak with me privately to let me know as soon as possible so that I may provide whatever accommodation you require. If you have an injury sustained during military service including PTSD or TBI, you are also eligible for accommodations under the ADA and should contact the Disability Services Office.

Title IX Reporting Responsibilities: Educators must report incidents of gender-­based crimes, including sexual assault, sexual harassment, stalking, dating violence, and domestic violence. If a student discloses such incidents to me during class or in a course assignment, I am not required to report the disclosure, unless the student was a minor at the time the incident occurred. Regardless of the student’s age, if the incident is disclosed to me outside the classroom setting or a course assignment, I am required by law to report the disclosure, including relevant details, such as the names of those involved in the incident, to Public Safety and Police Services and to Mr. Jesus Pena, Title IX Coordinator.  Information about Title IX can be found at the website for the Office of Social Equity.

Attendance: You will earn 4 points towards your grade by attending each class. Classes will include some lecture material that will overlap with the text, and some that will be additional material. Some classes will have hands-on activities (e.g., constructing a distribution of means) and examples to illustrate the material from the text, as well as the additional material. Also, some classes will include lab work and some will include practice quizzes. Therefore, poor attendance will not only cost you points, but it will also surely hurt your ability to do well in the course.

If you miss a test: If you miss a test, contact me to let me know why you missed it. It is important to make it up immediately.

Excusable absences: "Excusing" you only means excusing you from missing a test and/or attendance points. It does not mean excusing you from understanding the material on which you will be graded. It is always your responsibility to make sure you understand the material. Any time you miss a test you are given a grade of zero. To replace the zero with a grade, first, you should make up the test immediately (the next day if possible). Secondly, however, in order to be allowed to have your grade count, you may be required to provide written documentation that your absence was necessary.

Communication: Kutztown email is now the standard means of communication between faculty and students. If I need to contact the whole class (especially important in the winter) I will send an email to the class list. The class list contains the Kutztown email address of everyone registered for the course. You should check your email regularly.

Using your One Drive account or a flash drive to access your files.

You can save your files to your One Drive account and access them from anywhere you can get on the internet. Or, if you save them to a flash drive, you just need to keep the flash drive with you, but you don't need the internet.

MindTap: On the MindTap website there will be the following items for points towards your grades. Mastery Training (30 pts. each). The Mastery Training presents information and gives you repeated practice answering questions about it. It tailors the questions to your performance on previous questions. It is designed to capitalize on the benefits of space practice. It will tell you when you need to take a break. It will not let you continue to completion without breaks. In order to earn all the points you must take breaks and complete the entire activity in multiple, spaced sessions. For most chapters there are End of Chapter Problems. The number of points vary, and the later chapters have more points than the earlier ones. Their number of points is in a parenthesis right after the chapter number in the Schedule of Topics below (for example "Chapter 1 (22):"). There are four Tests, each covering the chapters since the previous test (22, 27, 27, and 30 pts., respectively.) There is a Final Exam (non-cumulative) on chapters 14 and 13 (14pts.) All the MindTap activities except the Tests are open the whole semester. The Tests are only open the day of the test, from 7am to 11:59pm.


Grading: Your grade for the course comes from the activities and tests on Mind Tap and for attending classes.  There are 14 Mastery Trainings, one for each chapter. That's a total of 420 points for the Mastery Trainings. There are a total of 334 points for End of Chapter Problems. The tests and Final Exam have a total of 120 points. There are 23 face to face classes. You will earn 4 points for each one you attend for a total of 92 points for attendance. The total number of points for the course is 966. Your grade will be the total points you earn divided by 966 (then multiplied by 100 to convert it to a percentage.) Grades are not curved. You will be able to see your grades for the MindTap activities and tests on Mind Tap. The attendance points are about 9.5% of the total points available. Each letter grade is 10% more than the letter below it. Therefore, attendance has the potential to vary your letter grade by as much as a full letter.

Your percentage grade will be the points you earn divided by the points available. It can be converted to a letter grade according to the following breakdown. I do not use plus/minus grading:

90% - 100% = A
80% - 89% = B
70% - 79% = C
60% - 69% = D
< 60 = F



Schedule of Topics 
(Subject to change if needed)

Week

Date

Topic

1

Mon. 8/28/23




Wed. 8/30/23

  Mon. - Introduction to the course. Syllabus.
Chapter 1 (22): Introduction to Statistics - Understanding research: Populations and parameters vs. Samples and statistics. Research questions. Stating them in terms of variables. Predictive relationships vs. causal relationships. Manipulating a variable. Types of data - quantitative vs categorical; scales of measurement

 Wed. - Chapter 2 (12): Frequency Distributions

2

 Mon. 9/04/23

 Wed. 9/06/23

 Mon. - LABOR DAY - NO CLASS

 Wed. - Chapter 3 (0): Central Tendency

3

 Mon. 9/11/23

 Wed. 9/13/23

 Mon. - Chapter 4 (30): Variability - Range, Interquartile Range, Begin Standard Deviation

 Wed. - Chapter 4: Variability - Finish Standard Deviation

4

 Mon. 9/18/23

 Wed. 9/20/23

Mon. - Review Chapters 1 through 4

Wed. - Test 1: Chapters 1 - 4 (on Mind Tap,Wed. 9/20/23, 7am to 11:59pm- covers regular class time - NO CLASS)

5

 Mon. 9/25/23

 Wed. 9/27/23

 Mon. - Chapter 5 (10): z Scores: Location of Scores and Standardized Distributions

 Wed. - Chapter 6 (23): Probability and the normal distribution - the unit normal table (z table) - the concept of a probability distribution

6

 Mon. 10/02/23

 Wed. 10/04/23

 Mon. - Chapter 7 (0): An important probability distribution: The Distribution of Sample Means and review for Test 2: Chapters 5 - 7 .

Wed. - Test 2: Chapters 5 - 7 (on Mind Tap - open during regular class time - NO CLASS)

7

 Mon. 10/09/23 - NO CLASS - FALL BREAK

Tues., 10/10/23 MONDAY'S CLASS

 Wed. 10/11/23

 Mon. - NO CLASS - FALL BREAK DAY

TUESDAY, 10/10/23 MONDAY'S CLASS - Chapter 8 (35): The Logic of Hypothesis Testing and the Single Sample Z Test - Power and Errors of Inference

 Wed. - Chapter 8 (35): The Logic of Hypothesis Testing and the Single Sample Z Test - Power and Errors of Inference

8

 Mon. 10/16/23

 Wed. 10/18/23

Mon. - Chapter 8: Calculating single sample z tests - Power and Errors of Inference

 Wed. - Chapter 9 (0): The Single Sample t test - Power and Errors of Inference

9

 Mon. 10/23/23

 Wed. 10/25/23

Mon. - Test 3: Chapters 8 & 9 (on Mind Tap - open during regular class time - NO CLASS)

Wed. - Chapter 10 (42): The Independent Measures t test - Effect size and Interval Estimation

10

 Mon. 10/30/23

 Wed.
11/01/23

Mon. - Calculating Cohen's d either from raw data by hand, or from the results of a t test in SPSS

 Wed. - Chapter 11 (42): The Repeated Measures t test (calculated like a one sample t test on difference scores) - Effect size and Interval Estimation

11

 Mon. 11/06/23

 Wed. 11/08/23

Mon. & Wed. - Chapter 12 (27): The Independent Measures ANOVA

12

 Mon. 11/13/23

 Wed. 11/15/23

Mon. - Test 4: Chapters 10 – 12 (on Mind Tap - open during regular class time - NO CLASS)

Wed. - Chapter 14  (54): Correlation
Friday 11/17/23 - Last day to withdraw with a "W"

13

 Mon. 11/20/23

 Wed. 11/22/23

 Mon. - Chapter 14: Linear Regression


 Wed. - THANKSGIVING

14

 Mon. 11/27/23

 Wed. 11/29/23

 Mon. - Chapter 14: Linear Regression



 Wed. - Chapter 13 (37): Two factor ANOVA

15

 Mon. 12/04/23

 Wed. 12/06/23

 Mon. & Wed. - Chapter 13: Two factor ANOVA




FINAL EXAM - Chapters 14, & 13 - On Mind Tap - Open Thurs. 12/07/23 at 7am, until 11:59pm, Fri.  12/15/23