Chapter 8 Hypothesis Testing
Chapter 8: Hypothesis Testing:
8.1 Review and Preview:
The two main activities of inferential statistics are using sample data to (1) estimate a population parameter (such as estimating a population parameter with a confidence interval), and (2) test a hypothesis or claim about a population parameter.
Hypothesis: a claim or statement about a property of a population
Hypothesis test/test of significance: a procedure for testing a claim about a property of a population
Population proportion is p, pop mean is mu (u), pop standard deviation is o with line on top
8.2 Basics of Hypothesis Testing:
Part 1: Basic Concepts of Hypothesis Testing
Rare Event Rule for Inferential Statistics: If, under a given assumption, the probability of a particular observed event is extremely small, we conclude that the assumption is probably not correct.
Working with the Stated Claim: Null and Alternative Hypotheses
Null hypothesis denoted by H0 is a statement that the value of a population parameter (such as proportion, mean or standard deviation) is equal to some claimed value (null is used to indicate no change or no effect or no difference).
Alternative hypothesis denoted by H1 or Ha or HA is the statement that the parameter has a value that somehow differs from the null hypothesis. The symbolic form of the alternative hypothesis must use , or the does not equal to sign.
Identifying H0 and H1: 1 Identify the specific claim or hypothesis to be tested, and express it in symbolic form. 2. Given the symbolic form that must be true when the original claim is false. 3. Using the two symbolic expressions obtained so far, identify the null hypothesis and the alternative hypothesis. Alt. is the expression that does not contain equality. Null is the one that the parameter equals the fixed value being considered.
Converting Sample Data to a Test Statistic
Test statistic is a value used in making a decision about the null hypothesis. It is found by converting the sample
8.1 Review and Preview:
The two main activities of inferential statistics are using sample data to (1) estimate a population parameter (such as estimating a population parameter with a confidence interval), and (2) test a hypothesis or claim about a population parameter.
Hypothesis: a claim or statement about a property of a population
Hypothesis test/test of significance: a procedure for testing a claim about a property of a population
Population proportion is p, pop mean is mu (u), pop standard deviation is o with line on top
8.2 Basics of Hypothesis Testing:
Part 1: Basic Concepts of Hypothesis Testing
Rare Event Rule for Inferential Statistics: If, under a given assumption, the probability of a particular observed event is extremely small, we conclude that the assumption is probably not correct.
Working with the Stated Claim: Null and Alternative Hypotheses
Null hypothesis denoted by H0 is a statement that the value of a population parameter (such as proportion, mean or standard deviation) is equal to some claimed value (null is used to indicate no change or no effect or no difference).
Alternative hypothesis denoted by H1 or Ha or HA is the statement that the parameter has a value that somehow differs from the null hypothesis. The symbolic form of the alternative hypothesis must use , or the does not equal to sign.
Identifying H0 and H1: 1 Identify the specific claim or hypothesis to be tested, and express it in symbolic form. 2. Given the symbolic form that must be true when the original claim is false. 3. Using the two symbolic expressions obtained so far, identify the null hypothesis and the alternative hypothesis. Alt. is the expression that does not contain equality. Null is the one that the parameter equals the fixed value being considered.
Converting Sample Data to a Test Statistic
Test statistic is a value used in making a decision about the null hypothesis. It is found by converting the sample