Syllabus Stat 202 Spring 2020

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Basic Statistics (Stat 202) Spring 2020 (Sections 028 and 035)

(For course materials, click here).

Instructor: Sean Carver, Ph.D., Professorial Lecturer, American University.


  • office location: Don Myers Technology and Innovation Building (DMTI, East Campus), Room 208F
  • email:
  • office phone: 202-885-6629
  • office hours, spring semester, 2020: Tuesday, Wednesday, and Friday 4:00 PM to 5:20 PM. likely to be adjusted as needed throughout semester (see below).

Course Description: Stat 202 is an introduction to statistics that emphasizes working with data and statistical ideas. Topics covered include: classification of data, averages, variability, probability, frequency distributions, confidence intervals, tests of significance, least squares regression, and correlation. A computer package is used to demonstrate statistical techniques. A major focus for this course is the ideas behind, and the methods for, drawing conclusions about a population from a sample.

A Word of Warning: The Math/Stat Department at AU teaches STAT 202 to prepare students to use statistics in advanced courses required for many majors. Thus the STAT 202 instructor does not always have the luxury of setting the most comfortable and easy pace through the course material. The pace will be determined by what we need to cover for your future classes. There is a lot of material in the curriculum, so be prepared to work hard and spend a lot of time studying outside of class.

Another Word of Warning: The material gets progressively harder throughout the semester, and later topics build on earlier ones. Learn the foundations well, and don't fall behind, because it is hard to catch up.

To reiterate: Studying, and in-class, Expectations:

  • Please note that this course is a 4-Credit Core Course and is part of the University’s Foundation Courses in Quantitative Literacy. We cover a large amount of material in this course (see the weekly schedule provided below). To do well in this course you will need to devote a minimum of 4 to 6 hours per week to studying the material over and above the time spent in-class. The study of Statistics is cumulative in nature – that is every single class builds on, and presumes, your mastering of statistical concepts & techniques covered in the previous class/es. In order to keep up with the class you will need to study & practice the weekly materials and maintain regular attendance throughout the semester.

Prerequisite: MATH-15x or higher, or permission of department. No prior knowledge of statistics is assumed.

Text for Class: STATS: data & models, Fifth Edition by De Veaux, Velleman, and Bock. Note the title of the text: there are two Statistics texts available with the same three authors, however the correct e-book comes free of charge with MyStatLab registration and registration for the course. A loose-leaf printed copy can be optionally purchased via MyStatLab for additional money. A bound copy can be optionally purchased separately, but this is expensive. Bound rental copies are available on-line for a very reasonable price.

Learning Management Software: MyStatLab from Pearson. Can be purchased from the bookstore and available as a free two week trial. Access instructions will be handed out on the first day of class. You must register for the section you belong to (035 or 031). You will need to upgrade your free access to full semester access. MyStatLab comes bundled with a subscription to the e-Textbook we will use for the course. You will need this bundle to complete and turn in the required homework.

Instructions for logging into MyStatLab for the first time:

Statistical Software: StatCrunch. StatCrunch is very easy to learn, and is a great pedagogical tool. StatCrunch (web-based software comes free with MyStatLab and is accessed through MyStatLab. Another way to access StatCrunch is with your AU creditials (regardless of what classes you are enrolled in) following the link: You can also access StatCrunch from StatCrunch.Com but you may need to pay for access through this site (you will need to pay for access after you leave AU).

Please Bring A Laptops To Class! I will be demonstrating software in class with the idea that you follow along with your own computer. Additionally, I will be giving problems to solve in class that require a computer. You may borrow a computer from the library if yours is temporarily unavailable.

Learning Outcomes: Learning objectives: At the end of this course you will be expected to

  1. understand the major concepts related to statistical reasoning and to statistical inferences for drawing such conclusions
  2. understand how these concepts are used in experiments and observational studies across many disciplines, and
  3. implement the methods yourself in statistical analyses.

Work will be a balance between understanding the concepts underlying a method, implementation of the method, and interpretation of the results.

This course is divided into four related areas of study:

  1. Data collection – the theory and practice of study design.
  2. Data summary and exploration – which illustrates to us how the data actually behave.
  3. Probability and sampling theory – from which we determine how we expect the data to behave.
  4. Data analysis – which allows us to reconcile our expectations with the actual data behavior so that we can make statistical inferences and draw conclusions.

Office Hours: Students are strongly encouraged to come to office hours if they need or want help. My office hours are tentatively scheduled, as follows (days and times may be adjusted throughout the semester, please come talk to me if you want to come but can't make those times):

  • Tuesday, Wednesday, and Friday 4:00 PM to 5:20 PM. likely to be adjusted as needed throughout semester.
  • Please wait a few minutes, in case I have momentarily stepped out. Also please knock if the door is closed.
  • There may be times during the semester when I miss office hours for some reason. I will usually hold make up office hours, possibly on Monday, and I will convey the change in plans to the class ahead of time.\
  • No office hours during or Spring Break or other days the university is closed or no classes.
  • My office is DMTI 208F.

SI Leader: Alexis De Silva. SI stands for Supplemental Instruction and is basically support for students (think group tutoring) by other more senior students. Alexis will introduce herself during the first week of class and explain how the SI program works.

Tutoring through MATH/STAT tutoring center: Don Myers Building, Room 103, walk-ins welcome. See below, and

Class times and locations:

  • Section 028: Tuesday, Wednesday*, Friday 9:45 AM - 11:00 AM; TF: DMTI 119; W: DMTI 217
  • Section 035: Tuesday, Wednesday*, Friday 12:55 PM - 2:10 PM; TWF: DMTI 121
  • *Wednesday classes dismiss 15 minutes earlier.

Emergency Preparedness: In the event of an emergency, students should refer to the AU Web site and the AU information line at (202) 885-1100 for general university-wide information. Information specific to this course during a prolonged closure of the university will be posted on Blackboard.

Responsibility: There is a lot of material on the schedule listed above, and ultimately you are responsible for learning all of it---by paying attention and asking questions during class, by reading the text, by doing the homework sets, etc.

Important Dates:

  • Tuesday, January 14: First day of class.
  • Wednesday, February 19: Midterm Exam 1.
  • Week of March 9: Spring Break. No class or office hours.
  • Friday, March 20: Last Day to Drop Class or Change Grade Option.
  • Wednesday, April 8: Midterm Exam 2.
  • Friday, April 24: Last Day of Class.
  • Friday, May 1: Final Exams (both sections' final begins at a different start time, see below for specifics).

Final Exams:

  • Please note that I will not be able to accommodate students who wish to switch their exam time with another slot that I am proctoring an exam. This restriction is due to the fact that the rooms in DMTI are filled to capacity by a full section of STAT 202, and adding another person to the room would make others uncomfortable, or there might not be a chair for someone.
  • Please note that inconvenience with travel plans is NOT a valid excuse for not taking the final as scheduled.
  • If you miss the final or any exam, you will need an excuse through the Dean of Students.
  • With an excused absence, the make up may not be until next semester (June or September) the meantime you will get an incomplete.
  • Section 028 (usually meets at 9:45 AM), your final exam: Tuesday May 1, 2019, 8:10 AM to 10:40 AM. Note that the start time for the final is different from the usual class start time.
  • Section 035 (usually meets at 12:55 PM), your final exam: Friday May 1, 2019, 11:20 AM to 1:50 PM. Note that the start time for the final is different from the usual class start time.

Grading scheme:

95%-100% A
90%-94.9999% A-
87%-89.9999% B+
83%-86.9999% B
80%-82.9999% B-
77%-79.9999% C+
68%-76.9999% C
65%-67.9999% C-
55%-64.9999% D
0%-54.9999% F

Grading rubric:

Labs 10%
Homework 15%
Quizzes 0%
Midterm Exam 1 25%
Midterm Exam 2 25%
Final Exam 25%

Homework and Exam Rules:

  • Calculators are allowed during homework and exams. Any simple calculator is absolutely sufficient.
  • Collaboration on a homework or lab is OK, even encouraged! Exams are to be done individually.

Cell Phones and Other Media:

  • Cell phones need to be silenced and put away during class. Personal use of electronic media during class time is highly distracting – it downgrades the quality of the classroom learning experience for everyone. Laptops (tablets, readers, etc.) should only be out during class time if they are being used for classroom activities. Please save texting, typing/sending emails, checking Facebook, etc. for outside of class time. If you need to attend to something urgently, it is OK to excuse yourself from the classroom.

Accommodations: Please let me know during the first week of classes if you have any special needs that require accommodations.

Incompletes: A grade of incomplete will only be given under extreme circumstances and will not be granted to any student who is failing.

Homework: Assigned, completed, and automatically graded through MyStatLab. MyStatLab has on-line help to assist with problems. An incorrect problem can be attempted again. Homework is due through MyStatLab at 11:59 PM on the day indicated on the tentative schedule below. Homework will be accepted late with a 10% penalty (90% credit) until 11:59 PM on the day of the final exam.

Quizzes: Periodically will be a quiz to test your knowledge of the material. These quizzes will not be for credit and will be self-graded. Bring a pen or pencil and something to write on.

Exams: You will use a lab computer if one is available. Otherwise, you will need your computer. You can borrow a computer from the library, if needed. You will have access to StatCrunch. You will not be able to do Google searches, access this website, or use your computer in any other way, unless cleared by instructor. Absences on exam days must be excused through the Dean of Students, who needs to send a letter to me indicating that they excuse your absence. If excused through the Dean of Students, you do not need to disclose the reason to me.

Labs: Periodically, I will assign labs to be completed in class or at home.

Attendance: Attendance will be taken on all or most days of class. Attendance is mandatory for all in-person classes at AU, and STAT 202 is no exception: you are expected to attend every class. That said, there can be compelling reasons why you may need to miss class, once in a while. Please email me if you are not going to attend within 24 hours after the class you missed class. Please indicate the reason, unless your absence is being excused by the Dean of Students---in which case, let me know this. Many students find having to miss class puts them at a disadvantage, so please only miss class for a good reason (such as sick, religious holidays for faith you practice, varsity meets for a team you are on, etc---not a complete list). Every day, new material builds upon the material previously covered. If you need to miss more than occasionally, even if it's for a good reason, please consider dropping the class. Last semester, I experimented with recording lectures for students who missed class, and students seemed pleased by the effort. I plan to offer this service again, but please note that a recorded lecture is no substitute for coming to class, where you can see what I write on the board and ask questions. Please be aware that I have not made attendance a part of your grade---so I put the responsibility on you. Attendance will be used to keep records, and will be a part of early warnings issued to you and your advisor should you perform unsatisfactorily in the class. Please try to come to class on time. It is disruptive to the class to try to update the attendance roll every time a new person walks in late, so if you arrive in class after your name is called you will be noted as absent for that day, but like I said, this notation won't affect your grade. Please see me if circumstances beyond your control require that you be a few minutes late to class on a regular basis.

Class time: Class time will be divided between lectures, quizzes (no credit), and labs. In addition, there will be plenty of class time devoted to working on homework with my supervision (active learning). You are permitted to access the book at any time during class, except during the no-credit quizzes and for-credit exams. Think of the no-credit quizzes as a dry run for the exams, so they will operate under the same rules.

Class Etiquette: Please participate in class by asking questions when you do not understand something. Invariably other students benefit from these questions. Please engage in discussions, and please engage with the class, generally. I find it easier to give good lectures when students are asking questions, and engaging with the material.

Academic Integrity: Cheating is not acceptable and will not be tolerated. Consider this: in subtle ways, cheating to get a better grade on an exam can result in lowering the grades of some of your classmates. Certainly this is true when a specific curve is used to assign grades. Even when I don't use curves explicitly, they can be implicit in decisions about writing and grading exams. I will handle all cases of suspected cheating according to the policies of American University. Specifically, I am required to report cases of academic dishonesty to the Dean of the College of Arts and Sciences. Cheating is giving or receiving unauthorized assistance on exams, from other students or other people, from notes, from books, or from the web. AU’s academic code is found at

Tentative Weekly Plan:

Week 1 Jan 14 No HW Due Chapter 1: Introduction, STATS Starts Here
1.1 What is Statistics?
1.2 Data
1.3 Variables

Chapter 2: Displaying and Describing Data

2.1 Summarizing and Displaying a Categorical Variable
2.2 Displaying a Quantitative Variable
2.3 Shape
2.4 Center
2.5 Spread
Week 2 Jan 21 H0, H1, H2 Chapter 3: Relationships Between Categorical Variables—Contingency Tables
3.1 Contingency Tables
3.2 Conditional Distributions
3.3 Displaying Contingency Tables
3.4 Three Categorical Variables
Week 3 Jan 28 H3 Chapter 4: Understanding and Comparing Distributions.
4.1 Displays for Comparing Groups
4.2 Outliers
4.3 Time plots: Order, Please!
4.5 Re-expressing Data: A First Look

Chapter 5: The Standard Deviation as Ruler and the Normal Model

5.1 Using the Standard Deviation to Standardize Values
5.2 Shifting and Scaling
5.3 Normal Models
5.4 Working with Normal Percentiles
5.5 Normal Probability Plots
Week 4 Feb 4 H4, H5
Lab 1 Due Feb 7
Chapter 6: Scatterplots, Association and Correlation
6.1 Scatterplots
6.2 Correlation
6.3 Warning: Correlation Does Not Imply Causation
6.4 Straightening Scatterplots
Week 5 Feb 11 H6 Chapter 7: Linear Regression
7.1 Least Squares: The Line of “Best Fit”
7.2 The Linear Model
7.3 Finding the Least Squares Line
7.4 Regression to the Mean
7.5 Examining the Residuals
7.6 R-Squared : the Variation Accounted for by the Model
7.7 Regression Assumptions and Conditions
Week 6 Feb 18 H7
Exam 1: Feb 19
Chapter 8. Regression Wisdom
8.1 Examining Residuals
8.2 Extrapolation: Reaching Beyond the Data
8.3 Outliers, Leverage, and Influence
8.4 Lurking Variables and Causation
8.5 Working with Summary Values
Week 7 Feb 25 H8
Lab 2 Due: Feb 28
Chapter 10 Sample Surveys
10.1 The Three Big Ideas of Sampling
10.2 Populations and Parameters
10.3 Simple Random Samples
10.4 Other Sampling Designs
10.5 From the Population to the Sample: You Can’t Always Get What You Want
10.6 The Valid Survey
10.7 Common Sampling Mistakes, or How to Sample Badly

Chapter 11 Experiments and Observational Studies

11.1 Observational Studies
11.2 Randomized, Comparative Experiments
11.3 The Four Principles of Experimental Designs
11.4 Control Groups
11.5 Blocking
11.6 Confounding
Week 8 Mar 3 H10, H11 Chapter 12 From Randomness to Probability
12.1 Random Phenomena
12.2 Modeling Probability
12.3 Formal Probability

Chapter 13 Probability Rules!

13.1 The General Addition Rule
13.2 Conditional Probability and the Multiplication Rule
13.3 Independence
Week 9 Mar 10 None Spring Break, No Class
Week 10 Mar 17 H12, H13 Chapter 14 Random Variables
14.1 Center: The Expected value
14.2 Spread: The Standard Deviation

Chapter 15 Probability Models

15.1 Bernoulli Trials:
15.2 The Geometric
15.3 The Binomial Model
Week 11 Mar 24 H14, H15 Chapter 16 Sampling Distribution Models and Confidence Intervals for Proportions
16.1 The Sampling Distribution Model for a Proportion
16.2 When Does the Normal Model Work? Assumptions and Conditions
16.3 A Confidence Interval for a Proportion
16.4 Interpreting Confidence Intervals: What Does 95% Confidence Really Mean?
16.5 Margin of Error: Certainty vs. Precision
16.6 Choosing the Sample Size
Week 12 Mar 31 H16
Lab 3 Due: Apr 3
Chapter 17 Confidence Intervals for Means
17.1 The Central Limit Theorem
17.2 A Confidence Interval for the Mean
17.3 Interpreting Confidence Intervals
17.4 Picking Our Interval up by Our Bootstraps

Chapter 18 Testing Hypotheses

18.1 Hypotheses
18.2 P-values
18.3 The Reasoning of Hypothesis Testing
18.4 A Hypothesis Test for the Mean
18.5 Intervals and Tests
18.6 P-Values and Decisions: What to Tell About a Hypothesis Test
Week 13 Apr 7 H17, H18
Exam 2: Apr 8
Chapter 19 More About Tests and Intervals
19.1 Interpreting P-Values
19.2 Alpha Levels and Critical Values
19.3 Practical vs. Statistical Significance
19.4 Errors
Week 14 Apr 14 H19 Chapter 20 Comparing Groups
20.1 A Confidence Interval for the Difference Between Two Proportions
20.2 Assumptions and Conditions for Comparing Proportions
20.3 The Two Sample Z-Test: Testing the Difference Between Proportions
20.4 A Confidence Interval for the Difference Between Two Means
20.5 The Two-Sample t-Test: Testing for the Difference Between Two Means
20.6 Randomization Tests and Confidence Intervals for Two Means
20.7 Pooling
Week 15 Apr 21 H20
Apr 24: Lab 4 Due
Chapter 21 Paired Samples and Blocks
21.1 Paired data
21.2 The Paired t-Test
21.3 Confidence Interval for Matched Pairs
21.4 Blocking
  • Last Day of Class, H21 due, Friday Apr 24.

Support Services: A wide range of services is available to support you in your efforts to meet the course requirements.

  • Mathematics & Statistics Tutoring Lab (Myers Building, room 103) provides tutoring in Mathematics and Statistics. Lab hours are Monday-Thursday 11 am – 8 pm, Friday 11 am – 3 pm, and Sunday 3 pm – 8 pm. Strongly recommended!!!
  • One-on-one tutoring is also available for math through Calc II and stats through Intermediate Statistics. Students may sign up for 45-minute appointments, up to 2 times per week. Students can schedule appointments at
  • Academic Support and Access Center (x3360, MGC 243) offers study skills workshops, individual instruction, tutor referrals, Supplemental Instruction, writing support, and technical and practical support and assistance with accommodations for students with physical, medical, or psychological disabilities. Writing support is also available in the Writing Center, Battelle-Tompkins 228.
  • Counseling Center (x3500, MGC 214) offers counseling and consultations regarding personal concerns, self-help information, and connections to off-campus mental health resource.
  • Sexual Assault Resources. It’s never the survivor’s fault. There are many people you can talk to if you or someone you care about has been sexually assaulted, including: AU's Office of Advocacy Services for Interpersonal and Sexual Violence (OASIS):

Class Mascot: Meet Knoll, my pet rabbit. Knoll will serve as the mascot for our class! You can see more of his pictures on his Instagram page (maintained by my wife) with the handle "knollisbusy". Through his Instagram page, Knoll occasionally sends out words of encouragement for AU students, especially around exam times---together with cute pictures.