EGN 3443 STATISTICAL TOPICS IN ENGINEERING
COURSE DESCRIPTION and TENTATIVE SYLLABUS
EGN 3443 Statistical Topics in Engineering
FAMU/FSU catalog course description: Basic statistical analysis, samples and populations, variability, hypothesis formulation and data analysis. Use of computer software and interpretation of results.
Tentative syllabus: (Some of the listed topics may not be covered.)
WEEK TOPICS SECTIONS
1 & 2 Course organization
The use of MINITAB, an example
Statistics in Engineering (reading) 1.1 - 1.5
Data summary and descriptive statistics 6.1 – 6.7
Histogram
Stem-and-leaf diagram
Box-and-Whisker plot
Measures of central tendency
Measures of variability (or spread)
Measures of relative standing
The use of MINITAB for basic statistics
3 & 4 Probability: sample space and events 2.1 - 2.8
Marginal, joint, and conditional probabilities
Mutual exclusiveness and additive rule
Independence and multiplication rule
Summary of compound events
Bayes’s rule
Expectations, mean and standard deviation
5 & 6 Discrete random variables (r.v.) 3.1 – 3.7
Probability distribution and probability
mass function (pmf)
Cumulative distribution function (cdf)
Mean and variance of a discrete r.v.
Discrete uniform distribution
Bernoulli distribution
Hypergeometric distribution
Binomial distribution
Geometric and negative binomial distributions
Poisson distribution
Examination No. 1 (Tentative)
7 Continuous random variables and probability 4.1 – 4.12
density functions (pdf)
Continuous uniform distribution
Normal distribution and normal approximation
to the binomial and Poisson distributions
Exponential distribution
Erlang and gamma distributions
Weibull distribution
Lognormal distribution
8 Interval estimation: one-sample problems 8.1 – 8.7
Confidence interval for the mean (or proportion)
Sample size problem.
9 Test of a hypothesis; one-sample problems 9.1 – 9.6
Test for the mean (or proportion);
The p-value approach; sample size problem.
10 Inference on two-sample problems. 10.1 – 10.6
Inference on the difference of mean (or of
proportions)
Inference on the equality of variances
Examination No. 2 (Tentative)
11 Simple linear regression; assumptions and 11.1 – 11.11
examples
Least squares estimates of the slope and intercept
Inference in linear regression
Assessing the adequacy of he regression model
Correlation and coefficient of determination
12 Multiple linear regression; assumptions and 12.1 – 12.6
examples; polynomial predictors; indicator
predictors (if time permits.)
13 & 14 Analysis of Variance; the F-distribution; 13.1 – 13.4
Completely randomized designs
One-factor ANOVA
Two-factor ANOVA
Latin square design
Examination No. 3 (Tentative)
15 Course project
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