Statistical Methods Chapter 6
What is true about a distribution with a negative z-score (where is the body; where is the tail)
Tail is on the left; body is on the right
Which of the following is true about the Unit Normal Table?
The body is always the larger part
Binomial Distribution
Two categories (ex. heads/tails) P= .5 q= .5
In a binomial distribution; X can have a value of
x=0 or X=1 p+q= 1
ALL probability values are between:
0 and 1
Independent Random Sample (random sampling)
Each individual has an equal chance of being selected and that the probability of being selected stays constant from one selection to the next if more than one individual is selected
Which of the following is/are requirement(s) of an independent random sample?
Every individual has an equal chance of being selected The probability cannot change (constant probability) There must be replacement
Simple Random Sample
Every individual in the population has an equal chance of being selected
Difference between simple random sampling and independent random sampling
In independent random sampling the probability of being selected must stay constant from one selection to the next, but in simple random sampling it does not.
What is the purpose of probability?
It tells us what samples are likely in a population. It tells us how likely we were to get the sample we got. It allows us to use sample data to make conclusions about populations Tells us how "extreme" a score is
Independent Random Sample =
Sampling WITH replacement The term "Independent" refers to the fact that the probability of selecting any particular individual is independent of the individuals already selected from the sample
Independent Random Sampling IS:
Simple Random sampling PLUS - the probability of being selected stays constant from one selection to the next
Probability
likelihood that a particular event will occur Defined as a fraction or proportion of all the possible outcomes: probability of A = number of outcomes classified as A/ total number of possible outcomes
