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STAT 301

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