true or false: outliers affect both mean and mode
false - outliers only affect mean
small samples tend to under/over estimate the range
underestimate
true or false: the 68-95-99.7 rule only applies to normally distributed data
true
sampling distribution
probability distribution of an estimate based on all possible samples of a given size from a population
standard error of an estimate
standard deviation of its sampling distribution -> predicts the sampling error of the estimate
confidence interval
all values for the parameter lying within the 95% confidence interval are plausible
- values outside are unlikely
pseudoreplication
the error that occurs when samples are not independent, but they are treated as though they are
event
a potential subset of all the possible outcomes
what does it mean for two events to be mutually exclusive
when the events cannot both be true simultaneously
what does it mean for two events to be independent
if the occurrence of one event gives no information about whether the other will occur
conditional probability
probability of an event occurring given that a condition is met
probability distribution
describes the true relative frequency of all possible values of a random variable
true or false: p-value is a conditional probability
true - it is the Pr[test statistic or more extreme | null hypothesis is true]
null distribution
probability distribution of outcomes when a random sample is taken from a hypothetical population in which the null hypothesis is true
when do you reject the null hypothesis
p-value < significance level
type I error
mistakenly rejecting a true null hypothesis
type II error
not rejecting a false null hypothesis
probability of type I error
alpha/significance level
probability of type II error
beta if null hypothesis is false
power/statistical power
ability of a test to reject a false null hypothesis
critical value of test statistic
value(s) beyond which the null hypothesis can be rejected
confidence interval to use if given alpha
(1-alpha)%
