Math-336 Intermediate Probability and Statistics II (4)
Instructor: Dr. Ari Wijetunga
Department: Mathematics
Office: Maclean 375C
Office Telephone: 477-4007
E-mail: wijetung@mnstate.edu
Office Hours: See my webpage
Classroom Building and Room: Maclean 169
Website: web.mnstate.edu/wijetung
Course Description: Bivariate random variables and expectations, Sampling distributions, Estimation,
One and two sample tests of hypotheses, Chi-Square tests, Analysis of variance, Completely
randomized and randomized block designs, Least square estimation, Simple and multiple linear
regression, Hypotheses testing and confidence intervals for regression parameters, Testing of models,
Model selection procedures, Multicolinearity, Introduction of qualitative variables, estimation of
parameters and tests of hypotheses, Checking validity of model.
Number of credit hours: 4.0
Prerequisite: Math 335
Text: Miller and Freund’s Probability and Statistics for Engineers, Eighth Edition
Reference: Statistics for Engineering and the Sciences, Fifth Edition, Mendenhall and Cincich
Course Objectives: Student should learn the statistical techniques given in the course description and
acquire enough knowledge to analyze data using a statistical package such as MINITAB and interpret the
results precisely.
Instructional Strategies: Lectures plus discussions and do problems in class. Analyze data using
MINITAB in class. Discuss real life problems and analyze data and interpret results.
Course requirements: Complete all homework assignments, Quizzes and examinations.
Grading policy: Four Hour-examinations – 15% each, Quizzes and homework- 20% and the Final
examination (Comp) –20%. 90% -A, 80%-B, 70%-C, 60%-D, below 60% -F
Course Outline
Section
5.10
6.1
6.2
6.3
6.4
7.1
7.2
7.4
7.5
7.6
7.7
7.8
8.1
8.2
8.3
8.4
9.1
9.2
9.3
9.4
9.5
12.1
12.2
12.3
12.4
11.1
11.2
11.3
11.4
11.5
11.6
11.7
Topic
Joint Distributions
Population and samples
The sampling distribution of the
mean ( known s.d)
The sampling distribution of the
mean ( unknown s.d)
Sampling distribution of the
variance
Point estimation
Interval estimation
Tests of hypotheses
Null hypotheses and tests of
hypotheses
Hypotheses concerning one
mean
The relation between tests and
confidence intervals
Operating characteristic curves
Comparing two treatments
Comparison-Two independent
large samples
Comparison-Two independent
small samples
Comparison-Matched pairs
Estimation of proportions
Hypotheses concerning one
proportion
Hypotheses concerning several
proportions
Analysis of rxc tables
Goodness of fit
Some general principles
Completely Randomized Design
Randomized Block Design
Multiple Comparisons
Method of Least squares
Inference based on least square
estimators
Curvilinear regression
Multiple regression
Checking the adequacy of the
model
Correlation
Multiple linear regression-
Remarks
Minitab demonstrations
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Minitab
Material will be provided
Material will be provided
Material will be provided
Material will be provided
Material will be provided
Material will be provided
matrix notation
Model selection procedures
Multicolinearity
Qualitative variables
Estimation, interpretation and
testing
Checking validity of modelresidual analysis
Transformations
Minitab
Minitab
Minitab
Disability Services: Students with disabilities who believe they may need an accommodation in this
class are encouraged to contact Greg Toutges Coordinator of Disability Services at 477-5859 (Voice)
or1-800-627-3529 (MRS/TTY), CMU 114 as soon as possible to ensure that the accommodations are
implemented in a timely fashion.
Attendance Policy: See Student Handbook http://web.mnstate.edu/sthandbook/POLICY/index.htm
Academic Honesty: See student Handbook
http://web.mnstate.edu/sthandbook/POLICY/index.htm