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Match each concept with its definition. a) Bayes Theorem likelihood that an event of a random experiment will occur b) Central Limit Theorem c) correlation coefficient rejecting the null hypothesis when the null hypothesis is true. d) definition of independence The sum of n independently distributed random variables will tend to be normally distributed as n becomes large. e) exponential random variables f) F-distribution _ difference between the observed and the predicted value of some variable. e) mutually exclusive events outcome is not known with certainty in advance h) operating characteristic curve ) overfitting exact significance level of a statistical test; probability of obtaining a test statistic that is at least as extreme as the one observed if the null hypothesis is true. j) p-value k) probability set of all possible outcomes from a random experiment I) random experiment m) residual Pr(A|B) = Pr(3lA) PríA) Pr(B) n) Rule of Total Probability _Pr(A|B) = Pr(A) o) statistic _failure to reject the null hypothesis when the null hypothesis is false p) Sample space q) Type I error Pr(B) = Pr (B|A) Pr(A) + Pr(B|A') Pr(A') r) Type Il error summary value calculated from a sample of ahservations; usually an estimator of a population parameter ANB = 9

Match each concept with its definition. a) Bayes Theorem likelihood that an event of a random experiment will occur b) Central Limit Theorem c) correlation coefficient rejecting the null hypothesis when the null hypothesis is true. d) definition of independence The sum of n independently distributed random variables will tend to be normally distributed as n becomes large. e) exponential random variables f) F-distribution _ difference between the observed and the predicted value of some variable. e) mutually exclusive events outcome is not known with certainty in advance h) operating characteristic curve ) overfitting exact significance level of a statistical test; probability of obtaining a test statistic that is at least as extreme as the one observed if the null hypothesis is true. j) p-value k) probability set of all possible outcomes from a random experiment I) random experiment m) residual Pr(A|B) = Pr(3lA) PríA) Pr(B) n) Rule of Total Probability _Pr(A|B) = Pr(A) o) statistic _failure to reject the null hypothesis when the null hypothesis is false p) Sample space q) Type I error Pr(B) = Pr (B|A) Pr(A) + Pr(B|A') Pr(A') r) Type Il error summary value calculated from a sample of ahservations; usually an estimator of a population parameter ANB = 9

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Match each concept with its definition. likelihood that an event of a random experiment will occur a) Bayes Theorem b) Central Limit Theorem rejecting the null hypothesis when the null hypothesis is true. c) correlation coefficient d) definition of independence The sum of n independently distributed random variables will tend to be normally distributed as n becomes large. e) exponential random variables f) F-distribution difference between the observed and the predicted value of some variable. g) mutually exclusive events outcome is not known with certainty in h) operating characteristic curve advance i) overfitting exact significance level of a statistical test; probability of obtaining a test statistic that is at least as extreme as the one observed if the j) p-value null hypothesis is true. k) probability set of all possible outcomes from a random experiment I) random experiment m) residual Pr(A|B) Pr(B|A) Pr(A) Pr(B) n) Rule of Total Probability Pr(A|B) = Pr(A) o) statistic failure to reject the null hypothesis when the null hypothesis is false p) Sample space q) Type I error Pr(B) = Pr (B|A) Pr(A) + Pr(B|A') Pr(A') r) Type Il error summary value calculated from a sample of abservations; usually an estimator of a population parameter ANB = Ø
Transcribed Image Text:Match each concept with its definition. likelihood that an event of a random experiment will occur a) Bayes Theorem b) Central Limit Theorem rejecting the null hypothesis when the null hypothesis is true. c) correlation coefficient d) definition of independence The sum of n independently distributed random variables will tend to be normally distributed as n becomes large. e) exponential random variables f) F-distribution difference between the observed and the predicted value of some variable. g) mutually exclusive events outcome is not known with certainty in h) operating characteristic curve advance i) overfitting exact significance level of a statistical test; probability of obtaining a test statistic that is at least as extreme as the one observed if the j) p-value null hypothesis is true. k) probability set of all possible outcomes from a random experiment I) random experiment m) residual Pr(A|B) Pr(B|A) Pr(A) Pr(B) n) Rule of Total Probability Pr(A|B) = Pr(A) o) statistic failure to reject the null hypothesis when the null hypothesis is false p) Sample space q) Type I error Pr(B) = Pr (B|A) Pr(A) + Pr(B|A') Pr(A') r) Type Il error summary value calculated from a sample of abservations; usually an estimator of a population parameter ANB = Ø
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