Course Description
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Three credits.
This course pretty much follows the textbook: basic probability distributions, point
and interval estimation, tests of hypotheses, correlation and regression, analysis of
variance, experimental design, non-parametric procedures.
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Descriptive Statistics:
graphical methods and numerical methods
. (Chapter 2)
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Probability:
calculating probability of an event, counting rules, conditional probabil-
ity, independent events, law of total, bayes’s theorem, venn diagram, tree-diagram,
contingency tables
. (Chapter 3)
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Random Variables and their Probability Distribution:
discrete random variables,
probability distribution, jointly distributed Random Variables, independence, condi-
tional distribution, expected value, variance, covariance, moment generating func-
tion, Tchebysheff’s inequality, weak law of large numbers.
(Chapter 4)