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Topics include predicate logic, recurrence relations, graphs, trees, digital logic, computational complexity and elementary computability.

Topics include predicate logic, recurrence relations, graphs, trees, digital logic, computational complexity and elementary computability.

Topics for the course include sample spaces and probabilities, discrete distributions (Binomial, Negative Binomial, Geometric, Hypergeometric, Poisson, and Gamma), continuous distributions (Uniform, Normal, Chi-squared), expectation and variance, hypothesis testing, interval estimation and confidence intervals. There will be extensive use of MS Excel and R, a statistical software program. At the end of the course, students should be able make meaningful connections between statistics and other areas of study, including and social sciences.

Topics for the course include sample spaces and probabilities, discrete distributions (Binomial, Negative Binomial, Geometric, Hypergeometric, Poisson, and Gamma), continuous distributions (Uniform, Normal, Chi-squared), expectation and variance, hypothesis testing, interval estimation and confidence intervals. There will be extensive use of MS Excel and R, a statistical software program. At the end of the course, students should be able make meaningful connections between statistics and other areas of study, including and social sciences.

Topics for the course include sample spaces and probabilities, discrete distributions (Binomial, Negative Binomial, Geometric, Hypergeometric, Poisson, and Gamma), continuous distributions (Uniform, Normal, Chi-squared), expectation and variance, hypothesis testing, interval estimation and confidence intervals. There will be extensive use of MS Excel and R, a statistical software program. At the end of the course, students should be able make meaningful connections between statistics and other areas of study, including and social sciences.

Topics for the course include sample spaces and probabilities, discrete distributions (Binomial, Negative Binomial, Geometric, Hypergeometric, Poisson, and Gamma), continuous distributions (Uniform, Normal, Chi-squared), expectation and variance, hypothesis testing, interval estimation and confidence intervals. There will be extensive use of MS Excel and R, a statistical software program. At the end of the course, students should be able make meaningful connections between statistics and other areas of study, including and social sciences.