Lecture 4 Prob Contd
... to repeat the experiment a huge number of times, each time recording the number of successes, we would have a huge collection of integers between 0 and n. The preceding formulas give the mean and standard deviation we would calculate from that huge collection. Example: 3.47 p.108 revisited. Here n = ...
... to repeat the experiment a huge number of times, each time recording the number of successes, we would have a huge collection of integers between 0 and n. The preceding formulas give the mean and standard deviation we would calculate from that huge collection. Example: 3.47 p.108 revisited. Here n = ...
Clicker_chapter20
... the shape of the sampling distribution of p̂ close enough to normal to use the normal distribution to compute probabilities on p̂ ? ...
... the shape of the sampling distribution of p̂ close enough to normal to use the normal distribution to compute probabilities on p̂ ? ...
3. Joint Distributions of Random Variables
... 1. −1 ≤ ρ(X , Y ) ≤ 1. 2. If |ρ(X , Y )| = 1, then there is a deterministic linear relationship between X and Y , Y = aX + b. When ρ(X , Y ) = 1, then a > 0. When ρ(X , Y ) = −1, a < 0. 3. If random variables X and Y are independent, then ρ(X , Y ) = 0. Note that the condition ρ(X , Y ) = 0 is not s ...
... 1. −1 ≤ ρ(X , Y ) ≤ 1. 2. If |ρ(X , Y )| = 1, then there is a deterministic linear relationship between X and Y , Y = aX + b. When ρ(X , Y ) = 1, then a > 0. When ρ(X , Y ) = −1, a < 0. 3. If random variables X and Y are independent, then ρ(X , Y ) = 0. Note that the condition ρ(X , Y ) = 0 is not s ...
