Math 117: Elementary Statistics – Spring Term, 2010

 

Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.

        H.G. Wells (1866 – 1946)

 

Course Goals

In general, a statistics course teaches you to both descriptively and inferentially explain the variation that occurs in real data. Upon completion of this course, you should know how to (among other things)

 

·         Graphically and numerically describe single variables and relationships between variables in a data set

·         Model single variable distributions (via the binomial or normal distributions) and model linear relationships between quantitative variables (via regression)

·         Collect data appropriate for your research question and with no (or limited) bias

·         Apply the rules and definitions of probability

·         Work with the sampling distributions of common statistics

·         Use sampling distributions of appropriate statistics to make inference about population values (via significance testing and confidence intervals)

  • Understand the general concept of inference, as well as its limitations
  • Realize that statistical analysis is important, applicable, interesting, and fun

 

Contact Information

Professor: Joy Jordan

Office:   410 Briggs Hall

Phone:   832-6894

E-mail:  joy.jordan@lawrence.edu

Web page:  www.lawrence.edu/fast/jordanj/

 

Please note the URL for my homepage. On this page is a link to the Math 117 web page, where I will post homework assignments, solutions, handouts, etc. You should visit this website regularly. Also note that I check email fairly regularly throughout the day (typically 3 times), but if you have an emergency or a message that is urgent, then you should definitely call, not email.

 

Required Textbook

Introduction to the Practice of Statistics, 5th Edition, Moore and McCabe, 2006, W.H. Freeman and Company

 

The textbook has a helpful companion website (a link to this site is included on the course web page). There is a new (6th) edition of this textbook, but in an effort to keep costs down for students, we use the 5th edition of the book (that is, used copies should be easy to find—you don’t need the CD that accompanies the book). Also, a copy of the textbook is on 2-hour reserve at the library (under Mr. Clemons – Math 107).

 

Office Hours

Monday: 12:30 – 1:30, Tuesday: 1:30 – 2:30, Wednesday: 10:00 – 11:00, Thursday: 2:00 – 3:00

 

If these times do not work with your particular class schedule, I am happy to make individual appointments for other times. (You need not make an appointment during regular office hours—just come in.) Please ask if you need help, and I will do all I can to assist you. That said, I expect you to come to office hours prepared (e.g., having done the reading, knowing the definitions) and not simply looking for easy answers. Besides office hours, anytime my door is open, feel free to come in and ask questions. If my door is closed, I am either out of the office, or I’m working and prefer not to be disturbed.

 

Homework

I will assign homework problems most days (and post them to the course website). These problems will not be collected, but they will be discussed in class, and they will be integral to your learning of the material. I will provide written solutions to all of the problems (they will be posted on the website), so you can check your work. My homework solutions should be thought of as required reading for the course, since certain (small) topics may be illustrated through homework problems rather than lecture. Please see me with any questions you have on the homework.

Quizzes

An announced quiz will be given on some Wednesdays (and one Friday—see attached course schedule). This will be an in-class quiz (given at the beginning of class) that will take 20 minutes to finish. The quizzes are not meant to scare you, but rather to regularly gauge your understanding and to serve as a motivational study aid. Quizzes will cover the major topics of the week, and will include questions requiring both problem solving and explanation. There will be no make-up quizzes, except for excused absences.

 

Computer Lab, Briggs 421 (Tuesday 9:50 – 11  or Thursday 3:10 – 4:20, depending on your section)

The weekly computer lab should be thought of as an extension of the lecture, and new material will sometimes be presented in lab. The lab will also be used to investigate and interpret real data (using statistical software). Hopefully it will be an aid to your understanding of the material. A lab syllabus will be given on the first day of lab (4/6 or 4/8, depending on your section).

 

Exams

There will be two in-class exams during the term and a final exam. The first exam is on Friday, April 23 and the second exam is on Friday, May 28 The final exam is Monday, June 7 at 1:30 p.m.

 

Study Tips

Before starting a homework assignment, it’s vitally important you first understand the concepts and definitions. Read the textbook and class notes carefully before starting an assignment (and ask me if you have questions). Also, students often say they understand individual concepts, yet they get easily confused when reading a new problem and deciding which method to apply. In preparation for an exam, you should obviously do many practice problems. To make these problems more like exam problems (where you’re not sure what section they’re from), you can do end-of-chapter problems and/or you can create your own practice test by retyping homework, lecture, and quiz problems into Word, and then randomly arranging the problems. Furthermore, be sure you can carefully explain each step of your answer—this ensures you understand the whole solution process (rather than simply memorizing specific situations).

 

Grading

Your final grade is based on a weighting of quizzes (10%), computer lab assignments (10%), and exams (first exam – 25%, second exam – 25%, final exam – 30%). The letter grades will be assigned as follows, corresponding to Lawrence’s GPA system (note: the cutoff is the lowest percentage that receives that letter grade):

 

Cutoff

Grade

93.75

A

90.00

A-

86.25

B+

83.75

B

80.00

B-

76.25

C+

73.75

C

70.00

C-

66.25

D+

63.75

D

60.00

D-

 

Class Atmosphere and Life Balance

Even though this is a large class, I strongly encourage questions from students, responses to my queries, and lively discussion. You are warmly welcome to participate in class, regardless of whether you have the “right” answer. Please join the conversation.

 

Because I love statistics so much, I will encourage you to work hard to learn the material. But please realize that your self-worth is not associated with your letter grade on a particular quiz or exam (or even with your final course grade). You are all good people, regardless of your official class performance on tasks.

 

Furthermore, I think as a society in general, and at Lawrence in particular, we are over-scheduled and allow precious little downtime and quiet reflection. I encourage you to think carefully about the intensity and number of courses, activities, and obligations in your life, and to seek balance as much as possible. (I’m happy to talk with you more about this—that is, we can discuss life as well as statistics.)

Tentative Course Schedule (with corresponding textbook reading)

 

Date

General Material

Reading

M 3/29

Introduction

To Students: What is Statistics?

W 3/31

One variable – graphs, interpretation, numerical summaries, and transformations

Sections 1.1 – 1.2

F 4/2

One-variable summaries

Sections 1.1 – 1.2

M 4/5

Normal distributions

Section 1.3

W 4/7

Quiz and normal distributions

Section 1.3

F 4/9

Scatterplots and correlation

Sections 2.1 – 2.2 

M 4/12

Regression analysis

Sections 2.3 – 2.4

W 4/14

Quiz  and regression analysis (and diagnostics)

Sections 2.3 – 2.4

F 4/16

Explaining association and experimental design

Sections 2.5,  3.1 – 3.2

M 4/19

Experimental design and sampling design

Sections 3.2 – 3.3

W 4/21

Sampling distributions and review

Section 3.4

F 4/23

Exam 1 (Chapters 1 – 3)

Reread Chapters 1 – 3

M 4/26

Probability definitions and specific probability rules

Sections 4.1 – 4.2

W 4/28

Conditional probability, independence, and general probability rules

Section 4.5

F 4/30

Bayes’ rule (tree diagrams) and probability review

Section 4.5

M 5/3

Random variables (distribution, mean, variance)

Sections 4.3 – 4.4

W 5/5

Quiz and random variables (distribution, mean, variance)

Sections 4.3 – 4.4

F 5/7

No class – Reading Period

Catch up on reading and homework problems

M 5/10

Means and variances of random variables, and binomial distribution

Sections 4.4, 5.1

W 5/12

Binomial distribution

Section 5.1

F 5/14

Quiz and normal approximation in the binomial setting

Sections 5.1

M 5/17

Central Limit Theorem and linear combination of normal variables

Section 5.2 

W 5/19

Quiz and linear combination of normal variables

Section 5.2

F 5/21

Confidence intervals

Section 6.1

M 5/24

Confidence intervals and significance testing

Sections 6.1 – 6.2

W 5/26

Significance testing and review

Section 6.2

F 5/28

Exam 2 (Chapters 4 – 6)

Reread Chapters 4 – 6

M 5/31

No class – Memorial Day

 

W 6/2

One-sample (and paired-data) t procedures

Sections 6.3, 7.1

F 6/4

Two-sample t procedures and review

Section 7.2

M 6/7

Exam 3 (Chapters 1 – 7) – 1:30 pm

Reread Chapters 1 – 7