STAT 301: Probability and Statistics I
Prerequisites: A grade of C or better in MATH 172
Credit Hours: (4)
Introduction to descriptive statistics and probability theory. A survey of the most
common probability distributions. One sample confidence intervals and hypothesis tests.
Note(s): Scientific and Quantitative Reasoning designated course.
Detailed Description of Course
The following topics will be covered:
1) Introduction of descriptive statistics
2) Counting Techniques and probability
3) Discrete distributions (binomial, Poisson, geometric, hypergeometric)
4) Continuous distributions (uniform, normal, exponential, beta)
5) Mathematical expectation (mean, variance, and covariance for functions of random
variables)
6) Sampling distributions of sample mean and sample proportion, Central Limit
Theorem
7) Moments and moment generating functions
8) Point and interval estimation for one sample (a) proportion, (b) mean with
known and unknown Variance
9) Hypothesis tests for one sample (a) proportion, (b) mean with known and unkown
Variance
10) Introduction to maximum likelihood estimation if time permits
Detailed Description of Conduct of Course
Course delivery methods may include classroom lectures, discussion, group work, and
examples.
Goals and Objectives of the Course
Students are expected to learn the basic principles of probability and statistics
and to demonstrate the use of these principles in problem solving. Students will be
able to use the tools of probability and statistics to conceptualize and solve problems.
Students will be able to:
1) Use basic statistical terminology appropriately
2) Create and interpret appropriate graphs and statistics to describe sets of
data
3) Calculate probability of events using counting techniques and probability rules
4) Apply and use various discrete and continuous probability distributions to
solve problems and calculate mean and variance of said distributions
5) Identify the sampling distributions of sample mean and sample proportion, and
apply the Central Limit Theorem
6) Find and use moment generating functions to calculate mean and variance
7) Conduct one-sample confidence intervals and hypothesis tests on mean and proportion
Assessment Measures
Assessment of the student's success in the course will be based on tests, homework
problems, and other possible assessment measures, the number and weights of which
are left to the instructor's discretion.
Other Course Information
None
Review and Approval
November 7, 2017
September 2, 2014
September 2001 Review Stephen Corwin, Chair
March 01, 2021