Confidence Intervals
This is the most common confidence level.
What is a 95% confidence interval?
This is the table used to calculate p-value for a z-test statistic.
What is Table A?
This condition/theorem states that the shape of the sampling distribution will always be normal.
What is the Central Limit Theorem? (CLT)
This is the formula for finding the degrees of freedom.
What is n-1?
This is the formula for margin of error.
What is critical value) (standard deviation of statistic)?
This refers to the interval of plausible values for a parameter calculated from the data.
What is a confidence interval?
This is the type of distribution that is used for z-tests.
What is a Normal distribution?
Sample sizes that meet the Large Counts condition have an n value that is greater than or equal to this number, and they are better because they yield more precise estimates of parameters and narrower confidence intervals.
What is 30?
This is the table you use in your formula booklet to calculate the p-value for a t-test statistic, and it has degrees of freedom on the side.
What is Table B?
This is a statistic that provides an estimate of a population parameter, and has no bias plus low variability.
What is a point estimator?
This is the formula for a confidence interval.
What is point estimate +/- (critical value)(standard deviation of statistic)?
This is the standard deviation formula for a z-test.
σp hat = root ( p(1-p) / n )
The formula (np and n(1-p) 10) helps us determine important information regarding the shape of the distribution for proportion.
What is the Large Counts condition?
This is how a t-distribution can be described and what it looks like.
What is a symmetric, single-peaked, bell-shaped distribution that is centered at 0 and has more area in the ‘tails’ than a Normal distribution?
When you need a sample size for a certain confidence interval, this is the value of p-hat you can use, considering its margin of error is the largest.
What is p-hat=0.5?
A single confidence interval only has these two possibilities when it comes to capturing the true parameter value.
What is 100% (containing the parameter value) or 0% (not containing the parameter value)?
You need this parameter to get a z-test statistic, but you don’t for t-tests, which is why t-tests are more useful in real-life contexts.
What is the population standard deviation?
The design must meet this condition in order to gain a scope of interest on the population and cause/effect.
What is the random condition?
These are the types of inferences that would entail a t-test.
What are inferences for means?
This is the type of variable that inferences about a population mean come from.
What is a quantitative variable?
This is how to interpret a 90% confidence interval where 4.05% to 4.95% of flights to Brazil from the PDX airport are late by at least an hour.
What is “We are 90% confident that the interval from 0.0405 to 0.0495 captures the true proportion of flights to Brazil from the PDX airport that are delayed by an hour or more”?
This is the type of inference that would entail a z-test.
What is an inference for a proportion?
This condition accounts for dependence between variables by ensuring that the standard deviation formula will be approximately correct.
What is the 10% condition?
This is the reason for the t-distribution having a larger spread than a Normal distribution.
What is replacing the population standard deviation with the sample standard deviation Sx, which results in more variability?
This is the type of variable that inferences about a population proportion come from.
What is a categorical variable?