Confidence Intervals for Population Means: Summary Notes
Confidence Intervals for Population Means
Purpose of Confidence Intervals: Used to estimate population means using sample data, accounting for variability.
Constructing Confidence Intervals: Use sample mean x to create an interval for population mean μ.
Critical Values for Confidence Intervals
Critical Value z^ or t^: Determines the width of the confidence interval based on confidence level and sample size.
One-Sample Z Interval: Used when population standard deviation σ is known; formula: x ext{±} z^* rac{σ}{ ext{√}n}.
One-Sample T Interval: Used when σ is unknown; formula: x ext{±} t^* rac{s}{ ext{√}n}, where s is the sample standard deviation.
Conditions for Confidence Intervals
Random Sample: Data must come from a random sample of the population.
10% Condition: Sample size n should be less than 10% of the population size N when sampling without replacement.
Normal/Large Sample Condition: Population should be normally distributed or sample size should be large (n ext{≥} 30).
Margin of Error and Sample Size
Margin of Error (ME): Affected by sample size and confidence level; ME ext{= } t^* rac{s}{ ext{√}n}.
Increasing sample size decreases margin of error (proportional to rac{1}{ ext{√}n} ).
Sample size can be estimated from previous studies or pilot studies, as σ is often unknown.
Example of Constructing Confidence Intervals: Determine mean values (e.g., books read, physical measurements) from samples, ensure conditions met, calculate using corresponding intervals.