HYPOTHESIS TESTING
WHAT?
way that statistics are used to form a decision about a population parameter
process of using data and statistical procedure to decide whether to reject or not to reject a hypothesis (statement) about a population parameter value or about the distribution characteristics
TYPES OF HYPOTHESIS
Ho : the null hypothesis
H1 : the alternative hypothesis
- statement in which a population parameter has specific value
- the starting point for investigation
- initially assumed to be true, thus to be tested
- statement about the same population parameter that is used in null hypothesis
- statement that specifies the population parameter has a different value
- rejection of null hypothesis imply the acceptance of the alternative hyothesis
TERMS
Critical Region
⭐ a set of values of the test statistics for which the null hypothesis will be rejected
Test Statistic
⭐ a function of sample data on which the decision is to be based
Critical Value
⭐ the first or boundary value in the critical region
TYPES OF ERRORS
Type I Error
⭐ the acceptance of H1 when Ho is true
⭐ the probability of commiting this error is called level of significance and denoted by a (alpha)
Type II Error
⭐ failure to reject Ho when H1 is true
⭐ the probability of commiting this error denoted by B (beta)
PROCEDURE
- Define the question to be tested and formulate a hypothesis
- Choose appropriate test statistics and calculate the sample statistics value. Choice of test statistics depends on probability distribution of random variables
- Establish test criterion by determining critical value and region
- Draw conclusions whether to accept or to reject the null hypothesis
ONE TAIL AND TWO TAIL TEST
P-VALUES