Week 6 - Hypothesis Testing for Business Decisions Flashcards
Define ‘Hypothesis testing’?
A statistical inference method used to test the value of population parameters.
Define ‘Null hypothesis’?
A statement about the value of one or more population parameters which we test and aim to disprove.
Define ‘Alternative hypothesis’?
A statement that we aim to prove about one or more population parameters; the opposite of the null hypothesis.
Define ‘Test Statistic’?
A value derived from sample data that is used to determine whether the null hypothesis should be rejected.
Define ‘Region of rejection’?
The range of values of the test statistic where the null hypothesis is rejected; it is also called the ‘critical region’.
Define ‘Critical value’?
The value in a distribution that cuts off the required probability in the tail for a given confidence level.
Define ‘Type I error’?
The rejection of a null hypothesis that is true and should not be rejected.
Define ‘Type II error’?
The non-rejection of a null hypothesis that is false and should be rejected.
Define ‘Level of significance’?
The probability of rejecting a null hypothesis which is in fact true.
Define ‘Confidence coefficient (1-alpha)’?
The probability of not rejecting a null hypothesis when it is true and should not be rejected.
Define ‘Confidence level’?
The confidence coefficient expressed as a percentage
What is the ‘Risk of type II error (B)’?
The chance that the null hypothesis will not be rejected when it is incorrect.
Define ‘Power of a statistical test’?
The probability that you reject the null hypothesis when it is false and should be rejected.
What is the ‘T-test of hypothesis for the mean’?
A test about the population mean that uses a t distribution.
Define the term ‘Robust’?
A test or procedure that is not seriously affected by the breakdown of assumptions.
What is ‘Randomisation’?
A process used in an experiment to ensure that selection bias is avoided.
Define ‘Data snooping’?
Using a set of data more than once for inference or selecting a model.
