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Course Plan
SS 2017
Probability and Statistics for Engineers
Math 208
Course Code
:
Math 208
Credit
:
3
No of Lectures in a Week
:
4 Hours
Lecture
:
Wednesday (12:00 - 14:00)
:
Friday (09:00 - 11:00)
Level
:
Environment Engineering 2nd year / 2nd semester
Course Instructor
:
Dr. Samir Shrestha
COURSE DESCRIPTION
MATH 208 consists of 11 units. The course includes Introduction to Statistics and Data
Description; Probability; One Dimensional Random Variable; Functions of One Dimensional
Random Variable and Mathematical Expectation; Some Important Discrete Random Variable;
Normal Distribution; Random Sample and Sampling Distribution; Estimation; Tests of
Hypothesis; Simple Linear Regression and Correlation and Statistical Quality Control.
GOAL
Upon Completion of MATH 208, students will be able to:
 Define mean, median, mode, range, quartile deviation, mean deviation, standard deviation,
variance, coefficient of variation, skewness, kurtosis, random experiment, sample space,
events, probability, conditional probability, mathematical expectation, probability
distribution, random variable, discrete random variable, probability mass function, Binomial
distribution, Poisson distribution, continuous random variable, Normal distribution, Standard
Normal Distribution, population, sample, census, sampling, sampling distribution, estimate,
estimator, parameter, statistic, Ch-square distribution, t-distribution, F-distribution, null
hypothesis, alternative hypothesis, correlation and regression, coefficient of determination,
statistical process control, control charts, etc.

Illustrate various properties and relationship among Dot plots and Scatter plots; frequency
distribution and histogram; stem-and-leaf plot and Box plot; Pareto diagram; mean, median
and mode; range, quartile deviation, mean deviation and standard deviation; skewness and
kurtosis; mutually exclusive and collectively exhaustive events; dependent events and
independent events; mathematical expectation; discrete random variable and continuous
random variable; Binomial distribution; Poisson distribution; normal distribution and
standard normal distribution; sampling distribution of mean and of variance; Chi-square
distribution; t-distribution; F-distribution; correlation and regression; control charts for
individual measurements and for attributes; etc.


Solve various problems using the properties of different measures of central tendency;
different measures of dispersion; addition theorem and multiplication of probability; Bayes’
theorem; mathematical expectation; Binomial distribution, Poisson distribution and normal
distribution; Central limit theorem; point estimation and interval estimation; sampling
distributions; tests of hypothesis; correlation and regression; control charts; etc.
Apply the concepts and properties of central tendency, dispersion, probability, distributions,
sampling, estimation, correlation, regression, control charts to real life and engineering
problems to become the best one.
EXAMS AND GRADING
At least two internal examinations each with 20 marks will be taken during the semester. All the
examinations will be written one. Internal exam papers will be returned to the students. Any
questions about grading or detection of grading errors in the exams must be reported
immediately within a week of receiving the exam paper. All students must take all the
exams and submit the term paper.
 The final grade (for 20 marks) will be determined by the average of the internal marks.
 The 5 marks will be for Assignments.
HOME ASSIGNMENT
Home assignment after completion of each chapter will be provided to the students with the
deadline of submission and students should submit the assignment on or before the deadline.
Home assignment submitted after deadline will not be accepted and results 0 "zero" marks for it.
ATTENDENCE
Students are expected to attend all the classes in which they are registered. Action for absence
will be taken according to the university rule. Failure to attend lectures regularly may affect the
evaluation of a student's academic and professional attitude and could result in a failing grade for
the course.
MISSED IN SEMESTER EXAMINATIONS
If the student is unable to attend one of the scheduled examinations, the instructor must be
notified before the examination. This may be done by notifying any course instructors of this
course or in the department by any means. A request for an “excused examination” does not
guarantee acceptance. In addition, a written letter of explanation requesting that the absence be
excused will need to be presented. Depending on the reason of absence, a make-up exam will be
given which may contain material from all previous exams. With the exception of highly
extenuating circumstances, failure to follow the prescribed procedures or failure to attend the
announced make-up examination will result in 0 (zero) marks for that exam.
LECTURES
01
TOPICS
08
09
10
11
Graphic representation of data- dot plots, scatter plots, frequency curves, histogram,
stem-and-leaf display, box plot, pareto chart.
Central tendency- mean, median, mode, mean of combined groups, comparision of
mean, median and mode.
Measures of variability- range, mean deviation, standard deviation, variance,
coefficient of variation.
Probability- random experiment, sample space, events, mutually exclusive vents,
collectively exhaustive events, addition theorem of probability.
Independent and dependent events, multiplication theorem of probability.
Conditional probability, Bayes theorem.
Random variable, types of random variable, discrete random variable, probability
distribution of discrete random variable,
Mathematical expectation of random variables and its application.
Binomial distribution.
Application of Binomial distribution
Poisson distribution.
12
Test I
13
14
16
17
18
19
20
21
22
23
Continuous random variable, probability density function, normal distribution.
Normal distribution (cont’d…), Central limit theorem, normal approximation to
binomial distribution.
Population, sample, census, sampling, estimate, estimator, parameter, statistic, Chisquare distribution.
t-distribution, F-distribution.
Inference, Point estimation
Interval estimation.
Tests of hypothesis
Tests of hypothesis (cont’d..)
Correlation and Regression.
Statistical Quality Control.
Statistical Quality Control (cont’d..)
24
Test II
02
03
04
05
06
07
15
Remark: Each lecture is of 2 hours.
RECOMMENDED TEXT BOOK:
1. Probability and Statistics in Engineering (4th Edition), by William W. Hines, Douglas.
Montgomery, David M. Goldsman and Connie M. Borror, John Wiley and Sons, Inc. 2003
REFERENCE BOOK:
1. Miller and Freund’s Probability and Statistics (7th Edition), by Richard A. Johnson,
Prentice Hall of India, Pvt. Ltd.
2. Statistics Concepts and Application, Nabendu Pal and Sahadeb Sarkar, Prentice Hall of
India Pvt. Ltd. 2005
3. Probability and Statistics, Purna Chandra Biswal, Prentice Hall of India Pvt. Ltd. 2005.
4. Modern Elementary Statistics, John E. Freund, 10th edition, Prentice Hall Int.
5. Statistics for Management, R.I. Levin and D.S. Rubin, 6th edition.