Rose-Hulman - Department of Mathematics - Course Syllabus
MA223 - Engineering Statistics I - 2010-11
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Catalogue Description and Prerequisites
MA 223 Engineering Statistics I 4R-0L-4C F, W, S Pre: MA 112 This
is an introductory course in statistical data analysis. Topics covered
include descriptive statistics, introduction to simple probability concepts,
and random variables (including their linear combinations and expectations).
The Central Limit Theorem will be presented. Hypothesis testing and confidence
intervals for one mean, one proportion, and one standard deviation/variance
will be covered as well as hypothesis testing and confidence intervals
for the difference of two means. An introduction to one factor analysis
of variance and simple linear regression will be presented. A computer
package will be used for statistical analysis and simulation. Experimental
data from a variety of fields of interest to the science and engineering
majors enrolled will also be used to illustrate statistical concepts and
facilitate the development of the student's statistical thinking.
- How to obtain or generate data.
- How to present data using various graphical
- How to compute and interpret numerical summaries and graphical
displays of data, both to answer questions and to check conditions
(in order to use statistical procedures correctly).
- How to read articles
that include statistical information.
- How and when to apply laws of
probability and how these laws go hand-in-hand with statistical inference.
- How calculus and mathematics in general underlie the intuitive ideas
behind both probability and statistics.
- The concept of a sampling distribution
and how it applies to making statistical inferences based on samples
- How to choose an appropriate statistical test for a given situation
and/or parameter of interest.
- How to run a statistical test after
verifying that conditions for those tests are met.
- How to make appropriate
use of statistical inference.
- The concept of statistical significance
including significance levels and p-values.
- How to communicate
the results of a statistical analysis and communicate these results
in context of the problem situation.
- How to apply modern technology and
methods (e.g., bootstrapping) as an aid in descriptive and inferential
- How to apply statistical knowledge to various engineering
Textbook and other required materials
Textbook: Applied Statistics for Engineers and Scientists, 2nd edition
-Jay Devore (Cal Poly) and Nicholas Farnum (Cal State Fullerton)
Computer Usage: Minitab 15
- Univariate and bivariate data visualization (histograms, side-by-side
boxplots, scatterplots, times series plots, etc.)
- Univariate and bivariate
descriptive statistics (mean, median, standard deviation, IQR, least squares
line, correlation coefficient, etc.)
- Probability distributions (discussed
from a calculus point of view), normal distribution, binomial distribution
- Sample spaces and events, probability laws, conditional probability
and independence, simple system reliability
- Random variables (RV's):
discrete and continuous RV's, linear combinations of RV's, and mean and
variance of RV's
- Sampling (simple and stratified) and sampling distributions
of various statistics, Central Limit Theorem
- Hypothesis testing: null
and alternate hypotheses, type I and II errors, alpha, beta, power
inference: point estimation, bias, confidence intervals and hypothesis
tests of the population mean and proportion
- Two-sample inference: confidence
intervals and hypothesis tests of the difference between two means, randomization
- Nonparametrics: bootstrap procedure and application to one-sample and
- K-sample inference: one-factor analysis of variance
- Simple linear regression: estimation, hypothesis testing,
confidence intervals, residual analysis
Course Requirements and Policies
The following policies and requirements will apply to all sections and
A summary of the computer
Students will be expected to demonstrate a minimal level of competency with
a relevant statistical package. The statistical package will be an integral
part of the course and will be used regularly in class work, in homework assignments
and during quizzes/exams. Students will also be expected to demonstrate the
ability to perform certain elementary computations by hand. (See Performance
Not yet specificed.
Final Exam Policy
The following is an extract from the final
exam policy page. Consult the policy page for complete details.
The final exam will consist of two parts. The first
part will be "by hands" (paper,
pencil). No computing devices (calculators/computers) will be allowed during
the first part of the final exam. This part of the exam will cover both computational
fundamentals as well as some conceptual interpretation, though the level of
difficulty and depth of conceptual interpretation must take into account that
this part of the exam will be shorter than the second part of the exam.
No "cheat sheets", or prepared program on the calculator may be used. The second
part of the exams will cover all skills: concepts, calculation, modeling,
problem solving, and interpretation. Statistics tables, if needed, will be
Individual Instructor Policies
Your instructor will determine the following for
*Note that most instructors will enforce some type
of grade penalty for students with more than four unexcused absences.
the grading scheme, based on the various course components.
the number and format of hour exams, quizzes, homework
assignments, in class assignments, and projects,
the policies governing the work items above, e.g.,
all policies for classroom procedure, including group
work, class participation, laptop use and attendance*.