Module 11.1: Hypothesis Tests and Types of Errors Flashcards
What are the steps of hypothesis testing?
1) State the hypothesis
2) Select the appropriate test statistic
3) Specify the level of significance
4) State the decision rule regarding the hypothesis
5) Collect the sample and calculate the sample statistics
6) Make a decision regarding the hypothesis
7) Make a decision based on the results of the test
What is the null hypothesis?
is the hypothesis that the researcher wants to reject.
What is the alternative hypothesis?
is what is concluded if there is sufficient evidence to reject the null hypothesis.
The alternative hypothesis can be one-sided or two-sided. Depends on the proposition being tested. If the hypothesis is “greater than 0” a 1 tail should be used. two-tailed should be used if “different th
What is the general decision rule for a two-tailed test?
Test statistic > upper critical value or test statistic < lower critical value.
What is the decision rule for a two-tailed z-test at a 95% confidence interval?
test statistic < -1.96 or test statistic > -1.96
What is the test statistic? What is the formula?
difference between the sample statistic and the hypothesized value, scaled by the standard error of the sample statistic.
Foruma = sample statistic - hypothesized value / standard error of the sample statistic.
What are the two types of errors when drawing inferences from a hypothesis test?
Type 1 error - the rejection of the null hypothesis when it is actually true. The significance level is the probability of making a type I error.
Type 2 error - the failure to reject the null hypothesis when it is actually false.
How do you conduct a decision rule?
1) Determine one or two tailed test
2) the significance level we require
3) distribution of test statistic.
4) if test statistic is greater or less than the value X, reject the null.
What is the power of a test?
Probability of correctly rejecting the null hypothesis when it is false. Formula is 1 - probability of making type 2 error.
What will increase the probability of a type 2 error?
decreasing the significance level will increase the probability of failing to reject a false null.
decreasing the sample size
What is the relationship between Type 1 and Type 2 error? Inverse or not?
Inverse, when Type 1 error increases, Type 2 error decreases
