Summary of course contents:
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Basic statistical concepts: Population, sample, variability, sources of variability, parameter, experiment, replication, statistical reasoning.
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Descriptive statistics: numerical methods (including mean, median, percentiles, variance, and standard deviation) and graphical methods (including histograms).
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Basic probability concepts: sample space, events, probability, independence and conditional probability.
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Probability models: discrete and continuous distributions, expectation and variance, and interpretations.
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Binomial and normal distributions.
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Sampling and sampling distributions: distribution of sample means and the difference between two independent sample means.
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Distribution of sample proportions and the difference between two independent proportions.
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Introduction to statistical inference for large and small samples: point and interval estimation for means and proportions in one-sample and two-sample settings.
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Significance testing in these settings, including interpretation of results.
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Analysis of categorical data: point estimation, chi-squared goodness of fit test, chi-squared test of independence.
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Analysis of bivariate data: concepts of correlation and regression, the least squares line.
Illustrative reading:
An elementary statistics text such as:
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"A First Course in Statistics" by James T. McClave and Terry Sinich
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"Introduction to Probability and Statistics" by Mendenhall, Beaver and Beaver
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"Mind On Statistics" by Jessica Utts and Robert Heckard
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"Statistics: the Exploration and Analysis of Data" by J. Devore and R. Peck
Potential Overlap:
This course is intended to serve as the basic pre-calculus introduction to statistics and should not pose problems of course overlap at the introductory level for which it is intended. This course is identical in content to Statistics 13V.