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Frequently Asked Question

Question:
MATH 1442 Elementary Statistical Methods

Answer:
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 Textbook:  Essentials of Statistics, 4th ed. by Mario F. Triola, Pearson Education, Inc.

                        ISBN:  0-321-64149-3

Catalog Description:   This course is a non-calculus introduction to statistics. Topics include the presentation and interpretation of data (using histograms and other charts, measures of location and dispersion, and exploratory data analysis), elementary probability and probability distribution functions (binomial, normal, t, chi-square), confidence intervals, hypothesis testing, correlation and linear regression, analysis of variance, and the use of statistical software.

Prerequisites:   A grade of “C” or better in MATH 0303 or MATH 0442 or placement by Accuplacer Exam.  Other prerequisites include ENGL 0301 and READ 0303.

Semester Credit Hours:   (4-4-0)

Course Outcomes:   This course will prepare the student to better understand a world ruled by statistics including their utility possible bias. For students whose curriculum includes data analysis, this course will provide the groundwork for experimental design and analysis. This course is to provide the student with an understanding of statistical concepts and problem-solving methods for use in his/her chosen field or in further mathematics studies. The goals of the course will be achieved by the following course outcomes. After the successful completion of this course, you will be able to do the following skills:

  1. To read and be able to critically interpret scientific statistical information.
  2. Be able to organize and present data in a variety of formats.
  3. Understand the fundamentals of probability.
  4. Understand measures of central tendencies and dispersion.
  5. Interpret the standard normal, binomial, and student t distribution tables.
  6. Sampling and making inferences about populations using distributions is the fundamental goal of this course.  Distributions used will include the binomial, uniform, student t, and the normal.
  7. Construct confidence intervals and interpret the probability of a true population mean falling within an interval.
  8. Design and test hypotheses based on the normal sampling and proportional sampling.
  9. An introduction to linear correlations and regressions.