Computer Science Department
College of Sciences & Mathematics

MAT121 Syllabus

  1. Course number and name

    MAT121 – Statistics I

  2. Credits and contact hours

    3 Credit Hours

  3. Instructor’s or course coordinator’s name

    Instructor: JoAnn H. Kump, Adjunct Professor of Mathematics

  4. Text book, title, author, and year

    A First Course in Statistics, McClave and Sincich, (With MathLab/Course Compass), Eleventh Edition, 2013.

  5. Specific course information
    1. brief description of the content of the course (catalog description)

      Basic concepts of statistics. Frequency distributions, measures of central tendency and variability, probability and theoretical distribution, significance of differences, and hypothesis testing.

    2. prerequisites or co-requisites

      Prerequisite: None.

    3. indicate whether a required, elective, or selected elective course in the program

      Required course.

  6. Specific goals for the course
    1. specific outcomes of instruction Students will be able to
      • Describe a dataset by producing appropriate graphs and calculating descriptive statistics.
      • Interpret graphs and descriptive statistics.
      • Calculate the probability of a simple or compound event. Understand the concepts of union, intersection, complement, conditional probability and mutually exclusive events.
      • Be able to calculate probabilities in binomial and normal distributions.
      • Form and interpret confidence intervals for a mean, proportion and differences in means and proportions.
      • Perform hypothesis test for a mean, proportion, difference in means (independent and dependent samples) and proportions and interpret the results.
      • Perform a linear regression to determine the relationship between two quantitative variables and make predictions using the linear regression equation. Interpret the correlation coefficient and coefficient of determination.
      • Be proficient in all of the above with some type of technology.
    2. explicitly indicate which of the student outcomes listed in Criterion 3 or any other outcomes are addressed by the course.

      Course addresses Student Outcomes (a) and (o).

  7. Brief list of topics to be covered
    • Statistics, Data, and Statistical Thinking
    • Methods for Describing Sets of Data, Measures of central tendency and variability
    • Probability
    • Random Variables and Probability Distributions
    • Inferences Based on a Single Sample: Estimation with Confidence Intervals
    • Inferences Based on a Single Sample: Test of Hypothesis
    • Comparing Population Means
    • Comparing Population Proportions
    • Simple Linear Regression