Probability and Normal Distribution

Random sampling is the process of sampling from a population where

each observation has an equal chance of being selected

Sampling with Replacement is after you select an item from the population, you

put it back before making the next selection

In sampling with replacement, the total number of items

stays the same, so the probability don’t change from one draw to the next

Sampling without Replacement is after you select an item from the population, you

don’t put it back before making the next selection

In sampling without replacement, the total number of item

don’t stay the same, you lost 1, so the probability will change from one draw to the next

Population predicts the

likelihood of different sample outcomes

Inferential statistics uses

sample data to make conclusion or estimate about the population

Standard Normal Distribution has a mean of

0

Standard Normal Distribution has a SD of

1

Given Z-score, to find proportion

look at the proportion of the Z-score in either tail or body in Unit Normal Table

Given proportion, to find z-score

look at the proportion in either tail or body in Unit Normal Table to find Z-score

p (Z > 1.50) means

more than 1.50, look at the tail

p (Z < 1.50) means

less tha 1.50, look at the body

p (-1.80 < Z < 0.20), means

1 - tail of 0.20 and 1.80

p (X < 1.50), μ = 100, σ = 15 → first find 

Z-score

Then

use Unit Normal Table to find the proportion that’s the body (bc less than)