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Statistics PDF

Kenyon Equivalent: MATH 106: ELEMENTS OF STATISTICS = 1/2 unit credit



This is a basic course in statistics. Emphasis is placed on actively engaging students through the use of statistical software such as Minitab, simulations, class activities and demonstrations. Course requirements include collecting, organizing, and interpreting data. Students will be expected to write technical papers summarizing experiments and studies. The major curricular topics are:


EXPLORING UNIVARIATE DATA: Visual and numerical summaries of data – histograms; dotplots; stemplots; boxplots; measures of center, spread, and location; cumulative frequency charts and plots; linear transformations; assessing normality; and comparing distributions (back-to-back stemplots, side-by-side boxplots, etc.).


EXPLORING BIVARIATE DATA: Scatter plots, correlation, least squares regression, and linear transformations. Causation versus association. Visual and numerical summaries for two-way tables.


DESIGN OF EXPERIMENTS: Simple comparative experiments and block designs. The use of randomization, eliminating bias, control and experimental groups, placebo effect, replication, etc.


SAMPLING: Census, observational study, simple random sample, stratified sample, cluster samples, systematic samples, biases (e.g., response bias, nonresponse bias, wording of questions, etc.), and sampling variability.


PROBABILITY: Basic probability models, random variables, expected values (means) and variances of random variables, general probability rules, linear combinations of random variables. Discrete Distributions – Binomial, Geometric, and Uniform. Continuous Distributions – Chi-square, Normal, t, and Uniform.


SAMPLING DISTRIBUTIONS: Counts, proportions, means, and totals. Simulation of sampling distributions with statistical software.


STATISTICAL INFERENCE: Confidence intervals and hypothesis tests for measures of center (mean and median), a proportion, differences in means (dependent and independent), differences in proportions, and linear regression models. The concept of power. Chi-square tests for association and equality of proportions.

 

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