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STAT 100: STATISTICAL LITERACY
How to be an informed consumer of statistical analysis. Experiments and observational studies, summarizing and displaying data, relationships between variables, quantifying uncertainty, drawing statistical inferences. S100 cannot be taken for credit if credit has already been rec...
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Terms: N/A | Credits: 3
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STAT 300: INTRODUCTION TO APPLIED STATISTICAL METHODS
Introduction to methods for analyzing quantitative data. Graphical and numerical descriptions of data, probability models of data, inference about populations from random samples. Regression and analysis of variance. Lecture and laboratory. Credit given for only one of S300 or K3...
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Terms: N/A | Credits: 4
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STAT 301: APPLIED STATISTICAL METHODS FOR BUSINESS
Introduction to methods for analyzing data arising in business, designed to prepare business students for the Kelley School's Integrative Core. Graphical and numerical descriptions of data, probability models, fundamental principles of estimation and hypothesis testing, applicati...
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Terms: N/A | Credits: 3
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STAT 310: STATISTICAL TECHNIQUES
Introduction to probability and statistics. Elementary probability theory, conditional probability, independence, random variables, discrete and continuous probability distributions, measures of central tendency and dispersion. Concepts of statistical inference and decision: esti...
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STAT 320: INTRODUCTION TO STATISTICS
Basic concepts of data analysis and statistical inference, applied to 1-sample and 2-sample location problems, the analysis of variance, and linear regression. Probability models and statistical methods applied to practical situations using actual data sets from various disciplin...
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Terms: N/A | Credits: 3
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STAT 420: INTRODUCTION TO STATISTICAL THEORY
Fundamental concepts and principles of data reduction and statistical inference, including the method of maximum likelihood, the method of least squares, and Bayesian inference. Theoretical justification of statistical procedures introduced in S320.
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Terms: N/A | Credits: 3
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STAT 425: NONPARAMETRIC THEORY AND DATA ANALYSIS
Survey of methods for statistical inference that do not rely on parametric probability models. Statistical functionals, bootstrapping, empirical likelihood. Nonparametric density and curve estimation. Rank and permutation tests.
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Terms: N/A | Credits: 3
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STAT 426: BAYESIAN THEORY AND DATA ANALYSIS
Introduction to the theory and practice of Bayesian inference. Prior and Posterior probability distributions. Data collection, model formulation, computation, model checking, sensitivity analysis.
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STAT 431: APPLIED LINEAR MODELS I
Part I of a two-semester sequence on linear models, emphasizing linear regression and the analysis of variance, including topics from the design of experiments and culminating in the general linear model.
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STAT 432: APPLIED LINEAR MODELS II
Part II of a two-semester sequence on linear models, emphasizing linear regression and the analysis of variance, including topics from the design of experiments and culminating in the general linear model.
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Terms: N/A | Credits: 3
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