Confidence Intervals Review

These flashcards cover key vocabulary and concepts related to confidence intervals, as outlined in the lecture notes.

Confidence Interval

A range of values used to estimate the true parameter of a population.

Margin of Error

The maximum amount by which the sample estimate might differ from the true population parameter.

Sample Size (n)

The number of observations or data points collected in a sample.

Population Proportion

The ratio of members of a population possessing a certain attribute.

Standard Deviation (s)

A measure of the amount of variation or dispersion of a set of values.

Critical Value

A factor used to compute the margin of error for confidence intervals, determined by the desired confidence level.

Simple Random Sample (SRS)

A sample selected from a population in a way that every member has an equal chance of being included.

90% Confidence Level

The degree of certainty that a confidence interval contains the true population parameter, specifically 90% of the time.

95% Confidence Interval

The interval within which we expect the true population parameter to fall 95% of the time.

Difference in Proportions

The difference between the proportions of two different groups being compared.

Point Estimate

A single value estimate of a parameter based on sample data.

Effect of Sample Size on Confidence Interval

Increasing the sample size typically decreases the width of the confidence interval.

Random Sampling Error

The error that occurs due to random variation in a sample used to estimate a population parameter.

Undercoverage

A sampling error that occurs when some members of the population are inadequately represented in the sample.

Nonresponse Bias

A potential bias when respondents differ significantly from nonrespondents.

Interpretation of ±5% Margin of Error

The true percentage may be between 77% and 87% based on the sample proportion of 82%.

Central Limit Theorem

A fundamental theorem stating that the distribution of sample means approaches a normal distribution as the sample size increases.

Population Mean (μ)

The average of a set of values from the entire population.

Statistical Significance

A term that indicates the likelihood that a relationship or difference between variables is caused by something other than mere random chance.

Hypothesis Testing

A statistical method used to decide whether there is enough evidence to reject a null hypothesis.

Confidence Interval Width

The range of values within which the true population parameter is estimated to lie; affected by the confidence level and sample size.