The course affords the student an early opportunity to see how the pieces of an applied problem fits together. Frequency distribution, percentiles, measures of central tendency and variability, normal distribution and curve, populations, samples, sampling distribution of means, sampling distribution of proportion, null and alternative hypotheses, type I and type II errors, tests of means, confidence intervals, decision procedures, correlation, chi-square, simple analysis of variance and design of experiments. Statistical techniques relevant to business applications. Primary emphasis is placed upon identification of appropriate statistical methods to use, proper interpretation and appropriate presentation of results. Topics include descriptive statistics, probability concepts, the normal probability distribution, estimation techniques, tests of hypotheses, simple and multiple linear regression.
Statistical software is used to implement many of the statistical methods.
An introduction to theories and methods of mathematics that are relative to computer science. The techniques of differentiation and integration are covered without the theory of limits and continuity. Applications in business and biological science are considered. Analysis of axiomatic systems, axiomatic development of elementary Euclidean geometry and non-Euclidean geometry. This course is a historical summary of the development of mathematics.