Unit 3 vocab Flashcards
Margin of error
Upper bound = point estimate + E
Lower bound = point estimate - E
Normal Distrobution
A bell-shaped probability distribution defined by the mean and standard deviation
Confidence interval
For an unknown parameter consists of an interval of numbers based on a point estimate
Standard error
The standard deviation of the sampling distribution of x bar, standard deviation x bar, is called the standard error of the mean.
( Indicated how different the population mean is likely to be from a sample mean)
(Basically the standard deviation of x bar is called the standard error)
Level of confidence
Represents the expected proportion of intervals that will contain the parameter if a large number of different samples is obtained
Point estimate
The value of a static that estimates the value of a parameter
(Numerical summary of a population it is the mean in some instances)
Sampling distribution
Of a static is a probability distribution for ALL possible values of the statistic computed from a sample size of n
Sample proportion
P hat, sample proportion, in a statistic that estimates the population proportion, p
P hat = x/n
Standard normal distribution
Mean = 0 standard deviation = 1
Probability density function
is used to determine the probability of a continuous random variable
Confidence interval
For an unknown parameter represents the expected proportion of intervals that will contain the parameter if a large number of different samples is obtained
The central Limit Theorem
Let X be any distribution with a mean and standard deviation. If random samples of size n are taken from the X distribution, then the x bar distribution will approach a normal distribution with a mean and standard deviation sigma/ square root of n as the sample size n increases. If the distrobution is unknown or not normal, then n > or = 30.
(the distribution of sample means approximates a normal distribution as the sample size gets larger, regardless of the population’s distribution.)
