LOGIC, PROBABILITY AND STATISTICS
This course will introduce students to the fundamentals of logic, probability and statistics as well as the use of the three in information systems applications. The course is divided into two separate parts: the first part covers Logic, and the second part covers Probability and Statistics.
Course Objectives:
• Students will learn how to formalize information and how to reason to produce logical conclusions
• Students will learn the fundamental concepts and applications of probability and statistics including: theory of distribution of random variables, the basic theory and techniques of parameter estimation and tests of hypotheses.
• After learning this course, students will be expected to perform statistical analyses for small samples and use popular statistics packages such as SAS, SPSS, S-Plus, R, or Matlab, to perform simple and sophisticated analyses for large samples.
Expected Learning outcomes:
Upon successful completion of this course, students should be:
• Knowledge
o Able to explain the fundamental concepts of logic, probability, and statistics.
o Able to reason systematically to produce logical conclusions.
o Able to describe several well-known distributions, including Binomial, Geometrical, Negative Binomial, Pascal, Normal and Exponential Distribution.
o Able to describe the concepts of various parameter estimation methods, like method of moments, maximum likelihood estimation and confidence intervals.
• Skills
o Able to apply the central limit theorem to sampling distribution
o Able to use estimation techniques to determine point estimates, confidence intervals, and sample size.
o Able to apply the appropriate Chi-squared tests for independence and goodness of fit
o Able to perform and analyze hypotheses tests of means, proportions and variances using both onesampled and two-sampled data sets.
o Able to implement the analyses in SAS, S-PLUS, R or MATLAB
• Attitudes
o Able to solve problems independently
o Able to appreciate the diversity of the applications of central limit theorem
o Able to appreciate the diversity of the applications of hypothesis testing