Hypothesis testing: compares data to the expectations of a specific null
hypothesis. Is the data are too unusual, assuming that the null hypothesis is true,
then the null hypothesis is rejected.
6.1 making and using hypotheses
Null hypothesis: specific claim about the value of a population parameter, made
for the purpose of argument. Good one is a statement that would be interesting
Alternative hypothesis testing: represents all other possible parameter values
except that stated in the null hypothesis.
Ho and Ha
6.2 Hypothesis testing: an example
two sided test: the alternative hypothesis includes values on both sides of the
value specified by the null hypothesis.
Test statistic: quantity calculated from the data that is used to evaluate how
compatible the results are with those expected under the null hypothesis
Null distribution: sampling distribution of outcomes for a test statistic under the
assumption that the null hypothesis is true.
p-value: probability of obtaining the data (or data showing as great or greater
difference from the null hypothesis) if the null hypothesis were true
Significance level: alpha, is a probability used as a criterion for rejecting the null
hypothesis. Is the P-value fo