STT 201
STATISTICAL METHODS
SUMMER 2015
SYLLABUS
INSTRUCTOR INFORMATION
NAMES:
OFFICE:
TEL. NO
E-mail:
Dr. Elijah DIKONG
C501 Wells Hall,
884 - 1486
dikonge@msu.edu
OFFICE HOURS:
MW: 03:00 p.m.. - 04:00 p.m. and Th: 01:00 – 02:-00 p.m. or by
appointment
Laboratory Instructors:
Name
Section
s
E-mail
Phone
Office
Office hours
Karim, Rejaul
101
karimrej@msu.edu 8841923
C410
Wells
Tuesdays and
Thursdays: 12:20 p.m. –
1:50 p.m.
Karim, Rejaul
101
karimrej@msu.edu 8841923
C410
Wells
Tuesdays and
Thursdays: 12:20 p.m. –
1:50 p.m.
Help Room: Statistics Help Room A102 Wells Hall is staffed for certain hours of the
week with teaching assistants to give walk-in help. See Help Room schedule posted on
www.stt.msu.edu
Course Web Sites: http://www.stt.msu.edu [main website] and http://msu.lon-capa.org/
will provide course information.
Course Description: Probability and Statistics with computer applications. Data
analysis, probability models, random variables, tests of hypotheses, confidence intervals,
linear regression, weekly labs using statistical software.
LECTURES: MW F 12:40 p.m. – 2:30 p.m. @ 316 EBH [316 Ernst Bessey Hall]
Laboratory: All laboratory meetings of the class are in B102 WH
Section 101
DAYS: Tuesdays and
TIME: 10:20 a.m. – 12:10 p.m.
Thursdays
Section 101
DAYS: Tuesdays and
TIME: 10:20 a.m. – 12:10 p.m.
Thursdays
Text: Mind On Statistics: Special Custom Edition for Michigan State University by
Jessica M.UTTS/Robert F.HECKARD
Attendance: You are expected to attend all meetings of the class. If you must miss a
class, plan to get notes for that day from a classmate. Be advised that schedule on page 4
is tentative.
Lecture: The lectures are used to present basic ideas. STT 201 is a survey course of the
most practical and commonly encountered statistical concepts and methods. The course is
taught at an elementary mathematical level (college algebra). The textbook will be
followed fairly closely. The course is divided into four units as follows:
Unit 1: Chapters 1-4
FOLLOWED BY MIDTERM EXAMINATION 1
Unit 2: Chapters 7 – 9
FOLLOWED BY MIDTERM EXAMINATION 2
Unit 3: Chapters 10 – 11
Unit 4: Chapters 12 – 13
FOLLOWED BY FINAL EXAMINATION
Each MID-TERM EXAMINATION is worth 150 points. All TWO MIDTERM
examinations count toward course total.
Laboratory: The laboratory instructor directs Tuesday and Thursday laboratory sections.
Students will be using the statistical package Minitab, release 15, which is installed on
the computers in and B102 Wells Halls, as well as computers in all computer labs on
campus. Students are required to become familiar with the basic commands of Minitab in
order to access, store, create and analyze data. There will be 10 laboratory assignments
each worth 20 points. A laboratory assignment is handed out at the beginning of each of
11 labs and posted on the class website. To facilitate start up directions, please arrive at
your lab on time. The computer work can be completed during the laboratory
meeting and submitted at the end of each laboratory meeting. Three (3) points will
be deducted for any late submission past the due submission time and 4 points each
24 hours past due date. Any late work must be submitted directly to Professor
Dikong and not the laboratory instructor.
Note: All examinations including the comprehensive final examination are multiplechoice and are "closed book" and "closed notes". The examinations will contain questions
concerning text material and problems, classroom examples and discussions, and the use
of Minitab. Missing an exam without an advance valid excuse presented to the instructor
will result in a score of 0 points. Persons who must miss an exam because of medical or
family emergency or other exceptional circumstances should present a valid excuse to Dr.
Dikong, in advance of the examination whenever possible. There will be no excused
laboratories.
All students are expected to adhere to the University policy on academic integrity. It is
covered in the Spartan Life booklet under General Student Regulations. For more
information about this, please consult the handbook or visit the Spartan Life web sites at
http://www.vps.msu.edu/SpLife/ .
Evaluation: Points are earned through two mid-term examinations (300 points), final
examination (200 points), ten laboratory projects (200 points).
POINTS TOWARD GRADE:
Source
Maximum
Points
300
200
200
700
2 mid-term examinations
Laboratory projects (10)
Final Examination
Total
Your total number of points will be converted into a percentage and your grade will be
determined by the following grading scale:
Numeric Grade
Point Range
Percentage (%)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.0
630 – 700
595 – 629
553 – 594
511 – 552
455 – 510
420 – 454
385 – 419
000 – 384
90% - 100%
85% - 89.9%
79% - 84.9%
73% - 78.9%
65% - 72.9%
60% - 64.9%
55% - 59.9%
0.0% - 54.9%
Disclaimer: The instructor reserves the right to make any changes he considers
academically advisable. Changes will be announced in class and posted on the
https://msu.lon-capa.org course website and also on www.stt.msu.edu website. It is your
responsibility to keep up with any changed policies.
IMPORTANT DATES:
05/18/2015
05/22/2015
05/25/2015
06/10/2015
07/01/2015
07/01/2015
First day of classes
Open Adds ends
Memorial Day – University Closed
Middle of Summer A; Last Day to drop with no grade
LAST DAY OF CLASSES
FINAL EXAMINATION
Suggested Exercises: We have selected some exercises from the textbook that illustrate
some of the ideas presented in class. Your solutions to these problems will not be
collected or graded. The answers to these exercises are found in the textbook, and your
solutions will not be collected or graded. If you encounter difficulty or are slow in
solving problems, you should re-study the material, seek help (at A102 Wells Building or
visit me during my office hours), and do additional exercises to improve your mastery of
the concepts and methods.
The textbook uses this terminology for its exercises: Exercise 3.13 refers to exercise 3.13
of Chapter 3, found on page 102; Exercise 8.27 refers to exercise 8.27 of Chapter 8,
found on page 308. These are among the suggested exercises listed below.
Chapter 1: 1.5, 1.11
Chapter 2: 2.1, 2.3, 2.5, 2.13, 2.17, 2.27, 2.29, 2.37, 2.39, 2.45, 2.51, 2.57, 2.63, 2.85,
2.87, 2.91, 2.93, 2.103
Chapter 3: 3.1, 3.3, 3.7, 3.13, 3.19, 3.37, 3.39, 3.43, 3.61, 3.63, 3.65, 3.81
Chapter 4: 4.1, 4.3, 4.5, 4.7, 4.15, 4.17, 4.19, 4.21
Chapter 7: 7.8, 7.9, 7.21, 7.23, 7.25, 7.29, 7.39, 7.41, 7.45, 7.47, 7.57, 7.59, 7.95, 7.105
Chapter 8: 8.1, 8.3, 8.9, 8.11, 8.13, 8.15, 8.25, 8.27, 8.29, 8.31, 8.39, 8.43, 8.45, 8.47,
8.51, 8.53, 8.63, 8.67, 8.69, 8.71, 8.77, 8.91, 8.92
Chapter 9: 9.1, 9.9, 9.13, 9.15, 9.23, 9.37, 9.39, 9.41, 9.47, 9.55, 9.59, 9.61, 9.69, 9.113
Chapter 10: 10.5, 10.7, 10.11, 10.15, 10.19, 10.21, 10.23, 10.35, 10.45, 10.57, 10.63
Chapter 11: 11.3, 11.5, 11.11, 11.13, 11.25, 11.27, 11.43, 11.51, 11.53, 11.83
Chapter 12: 12.3, 12.7, 12.21, 12.49, 12.51, 12.55, 12.63, 12.83
Chapter 13: 13.9, 13.17, 13.23, 13.25, 13.35, 13.39, 13.49, 13.59
In addition to the above exercises, practice review problems directly related to midterm examinations will be posted on the website www.stt.msu.edu and on
LON_CAPA
Tentative Schedule:
Week of
Monday
Wednesday
Friday
Lab
MAY 18
Lecture, discussion
Chapters 1 and 2
Lecture, discussion
Chapters 2 and 3
Lecture, discussion
Chapters 3
Labs 1
and 2
MAY 25
Memorial Day –
University closed
Lecture, discussion
Chapter 3
Labs 3
and 4
JUNE 01
Midterm Exam 1
Lecture, discussion
Chapters 7 and 8
Lecture, discussion
Chapter 4 +
Midterm Exam 1
Review
Lecture, discussion
Chapters 7 and 8
JUNE 08
Lecture, discussion
Chapter 9
Lecture, discussion
Chapter 9
Lab 7
and 8
JUNE 15
Midterm Exam 2
Lecture, discussion
Chapter 10
Lecture, discussion
Chapter 9 + Review
Midterm Exam 2
Lecture, discussion
Chapter 10
JUNE 22
Lecture, discussion
Chapter 11
Lecture, discussion
Chapter 13 + Final
Exam Revision
Lecture, discussion
Chapter 12
FINAL
EXAMINATION
JUNE 29
Lecture, discussion
Chapter 13
Lab 5
and 6
Labs 9
and 10
No Lab
No Lab
Advice for Students: DON’T FALL BEHIND!! This class moves at a rapid pace.







Come to class and recitation prepared.
o Read the chapter before lecture.
o Reread the chapter after lecture to see if you have follow up questions.
o Do the suggested exercises before recitation and come prepared with
questions.
Form a study group.
Learn how to use your calculator.
Keep a notebook of vocabulary.
Keep a list of reference examples.
Get help if you need it- from the professor, teaching assistant of the Statistics
Help Room.
ATTENDANCE: You are expected to attend all meetings (laboratories/lectures)
of the class. If you miss a class for whatever reason, you are responsible for all
materials, assignments, and deadlines missed. While office hours provide an
opportunity for further clarification of materials covered in class, they will not
substitute for classes.

ACADEMIC HONESTY: The Department of Statistics and Probability adheres
to the policies of academic honesty as specified in the General Student
Regulations 1.0, Protection of Scholarships and Grades, and in the All-University
of Integrity of scholarship and Grades which are included in Spartan Life: Student
Handbook and Resource Guide. Students who plagiarize will receive a grade 0.0
on the assignment, test or quiz.

ADA: To arrange for accommodation a student should contact the Resource
Center for People with Disabilities (353-9642) http://www.rcpd.msu.edu/

LECTURE NOTES: Please visit the class website http://www.stt.msu.edu or
https://msu.lon-capa.org before each class meeting. Print out the summary of the
next lecture and the corresponding class-work, and bring them to class. On the
class website you will also find the syllabus, mid-term review exercises,
laboratory assignments with their due dates, updated course outline, and other
pertinent information.

EXTRA CREDIT POLICY: Every week I will assign three or more exercises
on chapters discussed the previous weeks as extra credit exercises. These
exercises are not mandatory. Unannounced quizzes, attendance (taken at random
days), office visits, will all account for the total extra-credit points you earn.
TAKE ADVANTAGE OF THIS POLICY TO CONTINUALLY CURVE
YOUR CLASS GRADE THROUGHOUT THE SEMESTER.
MORE ON STUDENT CONDUCT








The instructor has the responsibility to teach. Students have the right to learn.
Everyone needs to be respectful of the rights of other people in the class.
Please avoid frequent tardiness. Arriving late and/or leaving early is not
acceptable.
Disruptive behavior which impedes the teaching/learning process will not be
tolerated – use of cell phones, audio devices (except tape recorders used to
record), and abusive language are prohibited.
Discussion is encouraged in my classroom. However, please be respectful
when the instructor or other students are speaking: listen attentively, disagree
politely, and at all times avoid ridiculing others. Finding mistakes in my
lectures is, however, encouraged, and is part of the fun.
Talking or whispering during lectures or presentations is not acceptable.
MSU policies regarding harassment will be enforced.
Class lasts entire period. Do not begin packing up or repeatedly checking the
clock (indicating your impatience) before class is dismissed.
Any form of cheating is considered a serious offense and will be dealt with
according to MSU guidelines. All persons involved are considered
responsible, including the person from whom others copy. Thus it is your
responsibility to place your materials in such a way that others will not have
an opportunity to copy them. You may be asked to sit in specific seats so as to
spread out exams takers.
CLASS SURVEYS
There will be ONE in-class survey and ONE online survey that are mandatory for each
student to participate in.
DESCRIPTION OF CHAPTERS
CHAPTER 1: What Is Statistics?
 Introductory Video
 Case Study Illustration: Does Aspirin Reduce Heart Attack Rates?
 Types of Statistics (Descriptive and Inferential)
Chapter 2: Descriptive Statistics
 Some Relevant Statistical Terminologies (data, raw datasets, observations,
population versus sample, parameters versus statistics, variables, categorical,
quantitative, ordinal variables, explanatory and response variables, outliers)
 Numerical Summaries of Quantitative Data (Measures of Central Location –
mean, median; Measures of Variability or Spread – Range, Standard Deviation,
Inter-quartile Range; Measures of Position – Maximum, Minimum, Quartiles)
 Effects of outliers on measures of center and spread
 Displaying Quantitative Data (Boxplots, Histograms, Stem-and-leaf Displays,
Dot-plots)
 Describing the distribution of a quantitative variable
 Displaying Categorical Data (Bar charts, Pie charts)
Chapter 3: Linear Relationships between Quantitative Two Variables
 Scatterplots, positive association, negative association, line of best fit, correlation
coefficient, coefficient of determination, residuals, influence of outliers on
regression and correlation
Chapter 4: Relationships between Categorical Variables
 Contingency (Two-Way) tables, Table of percentages, Conditional percentages,
Row percentages, Column percentages
Chapter 7: Probability





Definition of probability
Probabilistic terminologies: Random experiment, sample space, outcome, event,
simple event, compound event
Operations with events: Intersection of events, union of events, mutually
exclusive or disjoint events, complement of an event
Probability rules: Complementation, addition, general addition, multiplication
Conditional probability and Bayes’ Formula (through tree diagrams)
Chapter 8: Random Variables






Definition of a random variable; discrete and continuous random variables;
Probability distribution function (pdf); cumulative probability function (cdf);
Expected value (mean), variance, and standard deviation of a discrete random
variable; properties of discrete random variables;
Binomial Random Variable: Binomial experiments, binomial distribution; mean,
variance, and standard deviation of a binomial random variable;
Normal Random Variable: Normal density curves; z – scores; normal and
standard normal distributions;
The normal approximation to the binomial distribution;
Chapter 9: Understanding Sampling Distributions: Statistics as Random Variables




Sampling distribution for one sample proportion;
Sampling distribution for difference between two sample proportions;
Sample distribution for one sample mean;
Sampling distribution for the difference between two sample means;
Chapter 10: Estimating Proportions with Confidence


Confidence interval for a population proportion, p;
Confidence intervals for the difference in two population proportions;
Chapter 11: Estimation Means with Confidence


Confidence interval for a population mean;
Confidence interval for the difference in two population means;
Chapter 12: Testing Hypotheses about Proportions



z – Test for one proportion;
Type I, Type II errors;
z – Test for the difference in two proportions;
Chapter 13: Testing Hypotheses about Means



One – sample t – Test;
Type I, Type II errors;
Two – sample t – Test (pooled);
Chapter 14: Inference about Simple Regression (NOT TAUGHT THIS
SEMESTER)

Simple linear regression model: Population and Sample Versions;
Chapter 15: Inference for Categorical Variables (NOT TAUGHT THIS
SEMESTER)

Chi – Square Test of a relationship between two variables (Section 15.1 – to be
studied independently)
REMARK ON FINAL EXAMINATION (FE)
THE FINAL EXAMINATION WILL BASED ON UNITS 3 – CHAPTERS 10 – 11
AND UNIT 4 – CHAPTERS 12 AND 13. EACH QUESTION WILL WORTH 4
POINTS.
Number of questions:
50
Distribution of final examination questions:
Unit 3
in the neighborhood of 25 questions
Unit 4
in the neighborhood of 25 questions