Ch 5-6 Midterm Flashcards
Simple random sample
Process that selects sample of “n” objects so each member of population has same probability of being selected
Why we achieve greater accuracy by obtaining random sample
- Difficult to measure every item
- Proper selected samples can be used to obtain estimates of population characteristics
- By using probability distribution we can determine error with estimates
Sampling distribution
Probability distribution of sample mean
Sample distribution of sample mean
Population mean
When variance of Sample mean decreases…
Sample size “n” increases
When do we use standard normal distribution for sample mean?
When sample mean is normal distribution
Central limit theorem
Distribution of sample approximated a normal distribution (bell curve) as sample size increaes
Law of large numbers
Sample mean will approach population mean as sample size “n” becomes large regardless of distribution
Acceptance intervals
Intervals within which sample mean has high probability of occurring given we know variance and mean
Probability of range using CDF
P(a < x < b) = F(b) - F(a)
Properties of density function
- Area under pdf f(x) = 1.0
- f(x) > 0 for all values x
- Probability X lies between a and b under pdf
Expected value
Average of values taken as numbers of N
What does mean provide
Measure of centre of Distribution
What does variance provide
Measure of dispersion
Linear functions of random variable
W = a + bX