STATISTICS FOR BUSINESS & ECONOMICS

 

                                           STA 2023 Syllabus

 

 

Prerequisites:  High school algebra.

 

 

Terms Offered: Fall, Spring, and Summer

 

Text: A Brief Course in Business and Statistics, Second Edition.  Authors:  Mendenhall, Beaver, & Beaver, Thomson Publisher

 

Coverage:

 

                        Chapter 1 - All

                        Chapter 2 – Sections 1-4, 6-10, 12, 14, 15

                        Chapter 3 – Sections 1 –4, 6-8

                        Chapter 4 – Sections 1-3, 5, 6

                        Chapter 5 – Sections 1-4, 6, 7

                        Chapter 6 – Sections 1-4, 6, 7

                        Chapter 7 – Sections 1-4, 6*, 7, 8, 10, 11

                        Chapter 8 – Sections 1-5**, 7, 8, 10, 13

 

Topics:

 

  1. Statistics as a science:  Definition.  Basic statistical terminology.  Populations

and samples.  Parameters and statistics.  The role of statistics in experiment research.

 

  1. Descriptive statistics:  Statistical tables and graphs.  Histograms.  Measures of central tendency (arithmetic mean, median, mode).  Measures of variability (range, variance, standard deviation).   Tchebysheff’s Theorem and the empirical rule.  Coefficient of variation.  Percentiles and quartiles.

 

  1. Probability:  Role of probability in statistics.   Experiments and experimental outcomes.  Sample space, events, union, intersection, and complements of events.  Mutually exclusive events, independent events, and conditional probability.  Additive and multiplicative rules.

 

  1. Probability distributions of random variables: Experimental outcomes and random variables. Discrete and continuous random variables. Discrete probability distributions. Mathematical Expectation.

 

  1. Discrete random variables:  Binomial distributions, mean, variance, use of binomial formula and probability tables.  Poisson distributions, mean, variance, use of Poisson formula and probability tables.  Applications.

 

  1. The normal distribution:  The parameters of the normal distribution.  The standard normal distribution.  Tabulated areas under the standard normal curve.  The standardization formula.   Applications.   The normal approximation to the binomial.

 

  1. Sampling Distributions:  The central limit theorem.  Distribution of the mean of a sample from a normal population.   Large-sample sampling distributions of sample means and proportion for one and two populations.

 

  1. Large-sample estimator:  Point and interval estimation.  Interpretation of these estimators.  Unbiased estimators.  Large-sample estimation of means and proportions for one and two populations.

 

  1. Large-sample tests of hypotheses:  Large-sample hypothesis testing for means       

      and proportions for one and two populations.  Observed significance levels.

 

 

* Section 7.6: Omit pages 242-245 – small sample estimation

 

**Section 8.3:  Omit pages 286-289 – t-test

    Section 8.5:  Omit pages 299-303 – t-test