This is the symbol for population mean
What is μ?
Height, weight, and temperature are all examples of this type of data.
What is quantitative data?
The type of data needed for this test
What is categorical/qualitative data?
Rejecting the null hypothesis when it is actually true is called this type of error
What is a Type I error?
This is the theorem that states that the sampling distribution becomes normal as sample size increases
What is Central Limit Theorem?
Eye color and political party are examples of this type of data.
What is categorical/qualitative data?
This is the type of test used to see if a sample distribution matches the expected one.
What is a GOF test?
This symbol represents the probability of making a Type I error.
What is α?
This is the name of the standard deviation of the sampling distribution
What is standard error?
This type of graph is appropriate for displaying categorical data, whereas a histogram is used for quantitative data.
What is a bar chart (or pie chart)?
This is the formula for a chi-squared test statistic
Sum(expected-actual)^2/actual=X^2
Failing to reject a false null hypothesis is called this type of error.
What is a Type II error?
For the sampling distribution of p̂ to be normal, these two conditions have to be true
What is number of successes and failures have to be greater than 10?
A likert scale is an example of this level of measurement, where differences are not necessarily equal.
What is ordinal data?
This is the way degrees of freedom are calculated chi^2 2-way test
What is (rows-1) * (cols-1)
This is the term for the probability of correctly rejecting a false null hypothesis - equal to 1- β
What is the power of a test?
As the sample size, n, increases, standard error changes in this way
What is 1/(n^.5)
While observational data can show an association, this type of data collection is required to establish a causal relationship between variables.
What is a randomized experiment?
This is the minimum cell count required to perform a chi squared test
What is 5?
Increasing sample size affects Type II error and power in this way.
What is it that decreases Type II error and increases the power of the test?