1. Aim: How do we test hypothesis? HW#6: complete last slide

2. Statistical Inference Researchers are interested in answering many types of questions These questions can be addressed through statistical hypothesis testing which is a decision-making process for evaluating claims about a population

3. Hypothesis Testing Hypothesis Testing is a decision making process for evaluating claims about a population. In hypothesis testing, the researcher must define the population under study, state the particular hypothesis that will be investigated, give the significance level, select a sample from the population, collect the data, perform the calculations required for the statistical test and reach a conclusion

4. Significance? In an experiment, a prediction is tested by manipulating the IV and measuring changes in the DV while attempting to control extraneous variables – This provides two sets of data: one from a control group and one from the experimental group The decision to be made is whether there is a significant difference in the two sets of results that can be attributed to the influence of the IV or whether the difference is due to irrelevant extraneous variables. Thus, statistical testing leads to inferences being made form the data as to the relationship between vairables

5. Significant Level The point at which it is decided to reject the chance explanation and attribute responsibility for the difference to the independent variable is called the significance level – The significant level is also known as alpha

6. Statistical Testing There are two statistical testing used for hypothesis concerning means: – z test – t test There are three methods used to test hypothesis: – Traditional method – P-value methods – Confidence interval method

7. Beginning hypothesis testing Every hypothesis-testing situation begins with the statement of hypothesis – Statistical Hypothesis: a conjecture about a population parameter. The conjecture may or may not be true

8. Two Types of Statistical Hypothesis There are two types of statistical hypothesis – Null Hypothesis: is a statistical hypothesis that states that there is no difference between a parameter and a specific value, or that there is no difference between two parameters – Alternative Hypothesis: statistical hypothesis that states the existence of a difference between a parameter and a specific value, or states that there is a difference between two parameters.

9. Example 1: Right Tailed A chemist invents an additive to increase the life of an automobile battery. If the mean lifetime of the automobile battery without the additive is 36 months, then her hypotheses are: In this situation, the chemist is interested only in increasing the lifetime of the batteries, so her alternative hypothesis is that the mean is greater than 36 months. The null hypothesis is that the mean is less than or equal to 36 months. This test is called right-tailed since the interest is in an increase only

10. Example 2: Two Tail Test A medical researcher is interested in finding out whether a new medication will have any undesirable side effects. The researcher is particularly concerned with the pulse rate of the patients who take the medication. Will the pulse rate increase, or remain unchanged after a patient takes the medication? Since the research knows that mean pulse rate for the population under study is 82 beats per minute, the hypotheses for this situation are The null hypothesis specifies that the mean will remain unchanged, and the alternative hypothesis states that it will be different. This test is called a two-tailed test since the possible side effects of the medicine could be to raise or lower the pulse rate.

11. Example 3: Left Tailed Test A contractor wishes to lower heating bills by using a special type of insulation in houses. If the average of the monthly heating bills is $78, her hypotheses about heating costs with the use of insulation are The test is a left-tailed test since the contractor is interested in lowering heating costs.

12. Stating the Hypotheses To state the hypotheses correctly, researchers must translate the conjecture or claim from words into mathematical symbols. The basic symbols are used as follow: Equal To =Less Than < Not Equal toGreater than or equal to Greater than >Less than or equal to

13. Stating the Hypotheses The null and alternative hypotheses are stated together, and the null hypotheses contains the equals sign, as known (where k represents a specific number) Two-Tailed TestRight-Tailed TestLeft-Tailed Test

14. Homework #6 State the null and alternative hypothesis for each conjecture 1.A researcher thinks that if expectant mothers use vitamin pills, the birth weight of the babies will increase. The average birth weight of the population is 8.6 pounds. 2.An engineer hypothesized that the mean number of defects can be decreased in a manufacturing process of compact disks by using robots instead of humans for certain tasks. The mean number of defective disks per 1000 is 18. 3.A psychologist feels that playing soft music during a test will change the results of the test. The psychologist is not sure whether the grades will be higher or lower. In the past the mean of the score was 73.