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We will endeavor to locate the emergence of the Science Fiction (SF) genre and unravel how SF came to be the preeminent literature of the 20th and 21st centuries. To accomplish this, we will read and watch significant examples of SF from its long history beginning with Mary Shelley’s Frankenstein. To demonstrate what you have learned, you will have brief, daily writing assignments, three non-cumulative exams, and a research essay. In addition to the readings, viewings, and lectures, students are strongly encouraged to add their SF knowledge to our discussions.

We will endeavor to locate the emergence of the Science Fiction (SF) genre and unravel how SF came to be the preeminent literature of the 20th and 21st centuries. To accomplish this, we will read and watch significant examples of SF from its long history beginning with Mary Shelley’s Frankenstein. To demonstrate what you have learned, you will have brief, daily writing assignments, three non-cumulative exams, and a research essay. In addition to the readings, viewings, and lectures, students are strongly encouraged to add their SF knowledge to our discussions.

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.