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Probability and Statistics for Data Science and Bioinformatics
STAT 5353
School of Natural Sciences and Mathematics
Probability; Kolmogorov's axioms; independence; random variables; discrete and continuous distributions; expected values; joint, marginal and conditional distributions; Monte Carlo simulation; sampling distributions; law of large numbers; central limit theorem; maximum likelihood estimation; confidence intervals and hypothesis testing involving one- and two-sample problems; linear regression; proofs of key results; practical examples illustrating the theory; and introduction to a statistical software package. 3 credit hours.
Prerequisite: Calculus through multivariate calculus and department consent required.
Offering Frequency: Each year
Grades: 160
Median GPA: A-
Mean GPA: 3.380
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Probability and Statistics for Data Science and Bioinformatics
STAT 5353
School of Natural Sciences and Mathematics
Probability; Kolmogorov's axioms; independence; random variables; discrete and continuous distributions; expected values; joint, marginal and conditional distributions; Monte Carlo simulation; sampling distributions; law of large numbers; central limit theorem; maximum likelihood estimation; confidence intervals and hypothesis testing involving one- and two-sample problems; linear regression; proofs of key results; practical examples illustrating the theory; and introduction to a statistical software package. 3 credit hours.
Prerequisite: Calculus through multivariate calculus and department consent required.
Offering Frequency: Each year
Grades: 160
Median GPA: A-
Mean GPA: 3.380
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