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Probability, Random Sampling - Coggle Diagram
Probability
Percentile and Percentile Ranks
Tells the percentage of scores at or below a given score
Actual score that corresponds to a given percentile rank
Percentile rank always focuses on the area to the left of a score
To find percentile rank, convert the raw score into a z-score first
Always represented as a percentage, and not a z-score
Help describe a person's relative standing within a distribution
Normal Distribution
Normal distribution is symmetric and has a peak in center
most scores cluster around the mean
Frequencies decrease as you move farther away from the mean
Can be described using z-score sections instead of raw scores
Any normal distribution can use the same z-score percentages regardless of its mean or standard deviation
Unit Normal Table
List exact proportions for many different z-scores
Body is always the larger part of distribution
Tail is always smaller part
More precise and complete than using a normal curve graph
To find values for negative z-scores you use the same table value as the positive z-score
The likelihood that a specific outcome will occur
Conculsions based off of probability, not certainty
Calculated as a proportion of all possible outcomes
Often written as a proportion, decimal, or percentage
Values always range from 0 to 1
0 means impossible event, 1 means certain event
Helps to predict what samples are likely to come from a population
Researchers use sample results to make educated guesses about the populations
All outcomes together form a "whole"
Deck of playing cards has 52 possible outcomes
Inferential statistics uses probability to connect samples to populations
Cannot predict exact outcomes, but can predict the likelihood
Random Sampling
Every individual in a population has equal chance of being selected
Sample made this way is called a simple random sample
Independent Random sampling means each selection does not affect the next selection
Probabilities stay the same across draws
Helps to prevent bias in selecting participants
Each person in a population has a probability of being selected
Sampling with replacement keeps probabilities constant across selections