Math 117: Elementary Statistics – Spring Term, 2008

 

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 describe 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 in a data set 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 web page. On this page is a link to the Math 117 page, where I will post homework assignments, solutions, handouts, etc.

 

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). A copy of the textbook is on 2-hour reserve at the library (under Mr. Clemons – Math 107).

 

Office Hours

Monday: 3:00 – 4:00, Wednesday: 3:00 – 4:30, Thursday: 2:00 – 3:00, Friday: 12:30 – 1:30

 

If these times do not work with your schedule, I am happy to make individual appointments for other times. 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). 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 each day (and post them to the 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 web page), 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 Fridays (see attached course schedule). This will be an in-class quiz that will take 15 – 20 minutes to finish. The quizzes are not meant to scare you, but rather to serve as a 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)

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 (4/8 or 4/10, depending on your section).

 

Exams

There will be two in-class exams during the term and a final exam. The first exam is on Wednesday, April 23 and the second exam is on Friday, May 30. The final exam is Monday, June 9 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%), lab assignments (10%), and exams (first exam – 20%, second exam – 25%, final exam – 35%). 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-

 

Coverage

This course will cover the material in the first 7 chapters of the textbook. I have enclosed a tentative course schedule, but the pace of the course will depend on you. If the pace is too fast to encourage learning, then we will slow down. If the pace is too slow to keep people awake, then we will speed up. I encourage feedback on the pace of the course, the textbook, the homework problems, and the class activities. Hopefully, we can work out an appropriate pace together.

 

Having Fun

Perhaps you think it is impossible to have fun while learning statistics, but I assure you we will try. Class discussion and questions will be an integral part of this course, and I hope you find them lively and interesting.

Tentative Course Schedule

 

Date

General Material

Corresponding Reading

M 3/31

Introduction

To Students: What is Statistics?

W 4/2

One-variable summaries: graphs, interpretation, numerical summaries, and transformations

Sections 1.1 – 1.2

F 4/4

One-variable summaries

Sections 1.1 – 1.2

M 4/7

One-variable summaries and normal distributions

Section 1.3

W 4/9

Normal distributions and scatterplots

Sections 1.3, 2.1

F 4/11

Quiz, correlation, and regression analysis

Sections 2.2 – 2.3

M 4/14

Regression analysis and diagnostics

Sections 2.3 – 2.4

W 4/16

Regression diagnostics, explaining association, experimental design

Sections 2.4 – 2.5, 3.1

F 4/18

Quiz and experimental design

Sections 3.2

M 4/21

Sampling design and review

Sections 3.3

W 4/23

Exam 1 (Chapters 1 – 3)

Reread Chapters 1 – 3

F 4/25

Sampling distributions and specific probability rules

Sections 3.4, 4.1 – 4.2

M 4/28

General probability rules and conditional probability

Section 4.5

W 4/30

Conditional probability and Bayes’ rule

Section 4.5

F 5/2

Quiz and random variables (distribution, mean, variance)

Sections 4.3 – 4.4

M 5/5

Random variables (distribution, mean, variance)

Sections 4.3 – 4.4

W 5/7

Means and variances of random variables, and binomial distribution

Sections 4.4, 5.1

F 5/9

No class – Reading Period

Catch up on reading and homework problems

M 5/12

Binomial distribution and normal approximation in the binomial setting

Section 5.1

W 5/14

Normal approximation in the binomial setting and Central Limit Theorem

Sections 5.1, 5.2

F 5/16

Quiz and Central Limit Theorem

Section 5.2

M 5/19

Linear combination of normal variables and confidence intervals

Sections 5.2, 6.1 

W 5/21

Confidence intervals and significance testing

Sections 6.1 – 6.2

F 5/23

Quiz and significance testing

Section 6.2

M 5/26

No class – Memorial Day

 

W 5/28

Significance testing and review

Section 6.2

F 5/30

Exam 2 (Chapters 4 – 6)

Reread Chapters 4 – 6

M 6/2

Limitations of inference and one-sample t procedures

Sections 6.3, 7.1 

W 6/4

Paired and two-sample t procedures

Sections 7.1 – 7.2

F 6/6

Two-sample t procedures and review

Section 7.2

M 6/9

Exam 3 (Chapters 1 – 7) – 1:30 pm

Reread Chapters 1 – 7