Download syllabus - ProbStat2012

Republic of the Philippines
Mindanao State University
ILIGAN INSTITUTE OF TECHNOLOGY
COLLEGE OF ENGINEERING
Iligan City
SYLLABUS
Course Number: ES 85
Course Title: Probability and Statistics in Engineering
Credits: 3 units (3 hrs. lec.)
Course Description: Introduction to probability, combinations, random variables; probability
distribution and frequency distribution; average and measures of
variation; linear regression and correlation; acceptance sampling;
applications in engineering.
Prerequisite: Math 61 (Analytic Geometry and Calculus III)
Textbooks: Probability and Statistics for Engineers and Scientists (7th edition)
By: Walpole, Myers, Myers, Ye
Reference:
1. Probability and Statistics for Engineers and Scientists (5th ed.)
By: Walpole, Myers, Ye
2. Design and Analysis of Experiments (3rd ed.)
By: D.C. Montgomery,
General Objectives:
1. To introduce the fundamental terms used in probability and statistics.
2. To gain working knowledge in statistical inference, sampling and data analysis.
3. To provide the students the basic probability and discrete and continuous random
variables.
4. To instill additional material on graphical methods as well as an introduction to sampling
distribution.
5. To apply one and two sample point and interval estimation and hypothesis testing.
6. To develop understanding and expertise on the statistical tools used in engineering
applications.
7. To cultivate the inventiveness and creative instinct of the students in designing which
methods of statistical analysis he is going to apply in the data results from experimental
samples.
Course outlines:
I. Introduction to Statistics and Data Analysis
Statistical inference, samples, populations, experimental design,
sampling procedure, measures of location, measures of variability,
discrete and continuous data, graphical methods and data description.
Duration
(hrs)
3.0
II. Probability
Sample space, events, sample points, probability of an event,
conditional probability, additive rule, multiplicative rule, Baye’s rule
III. Random Variable and Probability Distributions
Random variable, discrete probability, additive rule, continuous
probability distribution, joint probability distribution.
IV. Mathematical Expectation
Mean of random variables, variance and covariance, means and
variances of linear combinations of random variables, Chebyshev’s
theorem
First Preliminary Exam
V. Some Discrete Probability Distributions
Discrete uniform distribution, binomial and multinomial distribution,
hypergeometric distribution, poisson`s distributions
VI. Normal Distribution
Continuous uniform distribution, normal distribution (Gaussian),
normal curve, gamma and exponential
distribution, Weibull distribution
VII. Function of Random Variables
VIII. Fundamental Sampling Distributions and Data Description
Random sampling, sampling distribution, Chi-squared distribution, tdistribution, f-distribution
Second Preliminary Exam
IX. One- and Two-Sample Estimation Problems
Population parameters, estimating population means, estimating the
population variance, estimating the difference of two means, estimating
the population variance, estimating the population proportion,
estimating the difference of proportions of two population
X. One- and Two-Sample Tests of Hypotheses
One and two-tailed tests, test concerning means, choice of sample size,
test concerning variances, test concerning proporitions, test for
goodness-of-fit, test for equality of several proportions
XI. Simple Linear Regression and Correlation
Correlation analysis, regression analysis, linear regression coefficients,
analysis of variance method, data plots and transformations
Final Examination
Total
5.0
3.0
3.0
3.0
6.0
6.0
2.0
5.0
3.0
6.0
5.0
3.0
3.0
54.0