'2 var' diaporamas de présentation

??????????? ( Factor Analysis )

??????????? ( Factor Analysis ). ????. ????. SPOOD. ???. zjchencs@gmail.com. ????. ??? ?? ??? ????? ??? ???? ??? ????. YOUR SITE HERE. ??? ??. YOUR SITE HERE. ? ?. ????. ????. ????. ????. YOUR SITE HERE. ???????????. ?? n ??? A. A x = l x. ???? n ?????. ??? ??

1.17k views • 96 slides

Statistics Jeopardy

845 views • 74 slides

Regression

Regression. Econ 240A. Retrospective. Week One Descriptive statistics Exploratory Data Analysis Week Two Probability Binomial Distribution Week Three Normal Distribution Interval Estimation, Hypothesis Testing, Decision Theory. Week Four. Bivariate Relationships

681 views • 52 slides

Lecture 2 : Association and Inference

Lecture 2 : Association and Inference. Karen Bandeen -Roche, PhD Department of Biostatistics Johns Hopkins University. July 12, 2011. Introduction to Statistical Measurement and Modeling. Data motivation. Osteoporosis screening

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Lecture 2 : Association and Inference

Lecture 2 : Association and Inference. Karen Bandeen -Roche, PhD Department of Biostatistics Johns Hopkins University. July 12, 2011. Introduction to Statistical Measurement and Modeling. Data motivation. Osteoporosis screening

491 views • 42 slides

Lectures prepared by: Elchanan Mossel elena Shvets

485 views • 39 slides

Lectures prepared by: Elchanan Mossel elena Shvets

394 views • 39 slides

Review of Expected Values

Review of Expected Values. Review of Expected Values. Random Variable (RV) : Outcome of an experiment Value unknown until experiment is completed Expected Value of Random Variable X, E(X): Also known as the Mean Value

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CHAPTER 16 Standard Deviation of a Discrete Random Variable

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6-4 Normal Approximation to the Binomial Distribution

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6-4 Normal Approximation to the Binomial Distribution

294 views • 27 slides

Expected values and variances

Expected values and variances. Formula. For a discrete random variable X and pmf p(X): Expected value: Variance: Alternate formula for variance: Var(x)=E(X^2)-[E(X)]^2 Standard Deviation: =sqrt(variance). Answers to some questions.

533 views • 25 slides

Lecture 3: Resemblance Between Relatives

Lecture 3: Resemblance Between Relatives. Heritability. Central concept in quantitative genetics Proportion of variation due to additive genetic values (Breeding values) h 2 = V A /V P Phenotypes (and hence V P ) can be directly measured Breeding values (and hence V A ) must be estimated

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High Productivity Languages for Parallel Programming Compared to MPI

280 views • 18 slides

Probability

Probability. Normal Distribution. What is Normal Distribution?. Any event can have at least one possible outcome. A trial is a single event. An experiment consists of the same trial being performed repeatedly under the same conditions.

318 views • 18 slides

Random Variables

Random Variables. Application of Random Variables. The Sum of the Variance. The sum of variance is a concept that is very important. It has been the subject of many AP questions and it is an idea that you should understand. (NOTE: This is for independent random variables only!)

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321 views • 15 slides

???? Random Variables

???? Random Variables. ???????. ???????? (outcome) ??????????????? (random variable) ????????? X, Y ???? ??????????????????? X: S ?R ? ???? X ???????? X ????? ( ???? ) ?????????. ???????. ?????????????????????????????????? (discrete random variable) ?

235 views • 13 slides

??? ????????

??? ????????. [ ???? ] 1 ??????? ? ??? X i ??? i ????????????? ??????????? ? 1 ? X i ?????? ? 2 ?????????????? ? 3 ? n ????????????? 2 ???????? S ??? ? 1 ???????????????????? S ????

234 views • 12 slides

Proof of function of (multiple) random var.

Proof of function of (multiple) random var. Single: p 151-153 Sum of ind. Poisson: p 157,158 Sum of ind. Normal: p 160,161 Products of r.v: p165,166. if X is N( m , s ) ? Y is N(a m , a s ) if X is LN( l , z ) ? Y is LN(ln a + l , z ). if X is N( m , s ) ? Y is N(a m + b, a s ).

133 views • 7 slides