STAT 291 Statistics for the Mathematical Sciences I (3)
Topics in probability and statistics: descriptive methods, conditional and unconditional probability, discrete and continuous distributions, one-sample estimation and hypothesis testing.
Meets the General Education Mathematical Sciences requirement. (Offered fall semester only.)
MATH 108 Intuitive Calculus with Applications or MATH 111 Calculus I with a C- or better
- Comfort with quantitative topics.
- Familiarity with summation notation and usage. This notation is used in
both descriptive analysis and when working with discrete distributions.
- Understanding of elementary proofs.
- Ability to differentiate and integrate functions of one variable so that
probabilities and moments can be considered for practical continuous distributions.
| Required Course Materials:
J. Devore, Probability and Statistics for Engineering and the Sciences,
8th edition, Cengage, 2012 (ISBN: 9780538733526)
L. Marlin Eby, Ph.D., Professor of Mathematics and Statistics
- Students majoring in Mathematics, Mathematics-with-Certification, Physics, Physics-with-Certification.
- Students who select this course from a required menu majors in Computer and Information Science with Computer Science concentration, Economics (B.A.),
Education-with-Certification (4-8) with Mathematics concentration, Education-with-Certification (4-8) with Science and Mathematics concentration, Nutrition Science.
- Students who select this course, a more mathematical introductory statistics course than STAT 269, to meet the General Education Mathematical Sciences requirement.
- To become familiar with both descriptive and inferential analyses.
- To use probability in applied models and as the bridge between descriptive
and inferential analysis.
- To intuitively understand each concept
- To understand when possible and appropriate, the rigor of a mathematical
- To integrate topics by identifying commonalties.
- To understand the limitations of each analysis through consideration of
- To express general concepts in terms of the application.
- To communicate results, clearly and completely, in a manner appropriate
to nonquantitative audiences.
- To be introduced to the computer's capabilities in solving practical
problems, using the computer for analysis only after understanding how to
perform the analysis manually.
General Education Objectives for the Mathematical Sciences
- To identify methods and assumptions of the mathematical sciences.
- To understand at least one of the three mathematical sciences of computing, mathematics, and statistics
from a liberal arts perspective.
- To think logically, analytically, and abstractly through engagement in quantitative problem-solving
- Descriptive Statistics: pictorial and tabular methods and measures of location
and variability, and position.
- Probability: axioms and properties, counting techniques, conditional probability,
- Discrete Distributions: probability and moment calculations in general;
binomial and Poisson distributions.
- Continuous Distributions: probability and moment calculations in general;
normal, gamma (including exponential and chi-squared), and beta distributions.
- Sampling Distributions: Central Limit Theorem.
- One-Sample Interval Estimation: properties and assumptions; confidence
intervals for a mean, proportion, and variance (standard deviation); sample
- One-Sample Hypothesis Testing: properties and assumptions; tests on a
mean, proportion, and variance (standard deviation); power calculation;
relationship to interval estimation; sample size determination.
Revised: October 2013; August 2011 (textbook)