Statistics Week 4, Hypothesis Testing

1. Hypothesis Testing Steps
1. Formulate the hypothesis
1. 2 alternative mutually exclusive propositions
2. Null hypothesis, H0 - a statement that is accepted correct
3. Alternative hypothesis, H1 - statement that must be true if H0 is false (alternative case)
4. Tests involving a single population parameter are called one-sample tests; tests involving two populations are called two-sample-tests
5. ex: Customer service time is a one-sample test
6. ex: before/after test (ie effectiveness of police prevention program) are two-sample
7. 4 possible outcomes
1. H0 is true
2. H0 is false
3. H0 is true, but the hypothesis test incorrectly rejects it (Type I error), probability of Type I error is alpha (level of significance)
4. H0 is false, but the hypothesis test incorrectly fails to reject it (Type II error), equal to 1-alpha, called the confidence coefficient
5. Beta, the confidence coefficient = 1- alpha
6. Power of the test = 1-Beta
8. Calculation of a test-statistic- a function of the mean, variance
2. select a level of significance which defines the risk of drawing an incorrect conclusion that a true hypothesis is false
3. determine a decision rule
1. divide the sampling distribution into a rejection region and non-rejection region
2. null hypothesis could be for example that call time is on average 30 mins
4. collect data and calculate a test statistic
5. apply the decision rule and draw a conclusion