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Statistics - Exam 3
Question | Answer |
---|---|
Normal distribution with a mean equal to 0 and a standard deviation equal to 1 | standard normal distribution |
Value that serves as a best guess at the value of the population parameter | point estimator |
Range of values used to estimate a population parameter with a specific degree of confidence | confidence interval |
Probability that the interval actually does contain the population parameter | degree of confidence |
value measuring some characteristic of a population | parameter |
complete collection of people, objects, scores, etc. to studied | population |
any sub collection of data drawn from a population | sample |
Characteristics of the standard normal distribution: | 1) central mean, median and mode 2) symmetric 3) curve never touches x axis 4) areas under curve represent probabilities |
Concepts of the Central Limit Theorem: | 1) If random variable x is normally distributed, then the sample mean will be as well for ANY sample size 2) If random variable x is NOT normally distributed then sample mean WILL BE normally distributed if the sample size is large enough (n>30) |
Why use n-1 degrees of freedom? | accounts for error found in small samples |
As sample size increases results __________. | narrow |
As confidence interval increases results ___________. | widen |
Why are interval estimators better than point estimators? | because interval estimators provide an upper and lower boundary increasing the likelihood that the parameter will fall within those bounds |
variance of a sample symbol | s² |
standard deviation of a sample symbol | s |
variance of a population symbol | σ² |
standard deviation of a population symbol | σ |
mean of a sample symbol | x with a line above it |
mean of a population symbol | µ |
proportion of a population symbol | P |
proportion of a sample symbol | p with a hat |