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Class Notes for Statistics at Virginia Polytechnic Institute and State University (VT)


VIRGINIA TECHSTAT 3006Z ZhangFall

STAT 3006 Lecture Notes - Lecture 23: Variance Inflation Factor, Multicollinearity, Correlation And Dependence

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VIRGINIA TECHSTAT 3615TranFall

STAT 3615 Lecture 7: Bio stat chapter 7

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VIRGINIA TECHSTAT 3615TranFall

STAT 3615 Lecture Notes - Lecture 91: Unimodality

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VIRGINIA TECHSTAT 3615TranFall

STAT 3615 Lecture 8: Bio stat chapter 7

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VIRGINIA TECHSTAT 3006Z ZhangFall

STAT 3006 Lecture Notes - Lecture 26: Confidence Interval, Statistic, Standard Deviation

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VIRGINIA TECHSTAT 3615RussellFall

STAT 3615 Lecture 30: Lecture 12.2 Notes Chapter 17-18

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VIRGINIA TECHSTAT 3615RussellFall

STAT 3615 Lecture Notes - Lecture 24: Statistical Inference, Statistic, Point Estimation

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VIRGINIA TECHSTAT 2004JW BrownFall

STAT 2004 Lecture Notes - Lecture 7: Ap Statistics, Scatter Plot

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Chapter vii scatter plots, association, & correlation. Most common and most effective way to display data: clearly illustrate trends, patterns, relatio
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VIRGINIA TECHSTAT 3006Z ZhangFall

STAT 3006 Lecture Notes - Lecture 14: Scatter Plot, Dependent And Independent Variables

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Two variables are associated if knowing the value for one variables gives you information about the value for the other. This is often discussed as a r
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VIRGINIA TECHSTAT 2984L HouseSpring

STAT 2984 Lecture 2: STAT-2984 - Notes - 2 - Data Size

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Measuring the size of data: number of dimensions (variables, pixels, words) High level number of observations (rows, documents, images), Low level size
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VIRGINIA TECHSTAT 2984L HouseSpring

STAT 2984 Lecture 5: STAT-2984 - Notes - 5 - Structured Data

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Recall ~ filename. r refers to a scriptfile/textfile specifically used for r. Determine the dimensions of a dataset by dim(dat). Character objects retu
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VIRGINIA TECHSTAT 3005H C TaveraSpring

STAT 3005 Lecture Notes - Lecture 5: Sample Space, Bernoulli Distribution, Binomial Distribution

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The binomial distribution is one of the most important discrete distributions. The outcome is binary (i. e yes/no or success/failure). For example, thi
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