Chapter Three Flashcards
(21 cards)
Statistical inference
The process of drawing conclusions about the entire population based on sample information
Parameter
Number that describes some aspect of a population
Mean notations
Population: mu
Sample: x-bar
Standard deviation notations
Population: sigma
Sample: s
Proportion notations
Population: p
Sample: p-hat
Correlation notations
Population: rho
Sample: r
Slope notation
Population: B
Sample: b
How best can we estimate population parameters
Through the use of simple random samples, which are the best estimate of the parameter value
How do sample statistics vary?
Close together sample averages: low variability from sample to sample
Far sample averages: high variability
Sampling distribution
Distribution of sample statistics computed for different samples of the same size
What does sampling distribution tell us?
How sample statistics vary from sample to sample
Standard error
Standard deviation of the sample statistic
Increased sample size equals
Decreased variablity
The center of a sampling distribution tells
The location of the population parameter
Margin of error
Number that reflects the precision of a sample statistic as an estimate for the true parameter
Confidence interval
Indicates how sure we are that an interval contains the true parameter
Interval estimate
Gives a range of plausible values for a population parameter
95% confidence interval formula
Stat +/- 2* SE
When is the 95% confidence interval used
For symmetric and bell shaped sampling distributions
Bootstrapping
Approximating a sampling distribution and estimating the standard error using one sample’s information
95% confidence interval formula
Stat +/- 2* SE
