Introduction to statistical theory, including the nature of statistical methods,
exploratory data analysis, the rules of probability, frequency distributions, probability distributions
(Binomial, Poisson, hypergeometric, uniform, normal), sampling distributions, estimation and hypothesis
testing, one- and two-sample procedures, regression and correlation. Learning to do statistical analysis
using computers is required of all students and is an integral part of the course.
At the successful completion of this course, the student will be able to demonstrate the following with consistency and understanding:
1) Find the mean, median, mode, range and standard deviation of a frequency distribution given as single data, weighted data or classed data
2) List the outcomes of an experiment using a sample space or tree diagram and/or determine the number of possible outcomes of the experiment.
3) Using formulas, Venn diagrams, cross tabulations, find the probability for the complement, union and intersection of events and for conditional probabilities
4) Using formulas or tables, find the probability of an event in a Binomial, Poisson, hypergeometric, uniform or normal distribution
5) Apply the Central Limit Theorem accurately
7) Produce a confidence interval for a population mean or proportion
8) Test a hypothesis about the population mean or proportion