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Hypothesistesting2

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Hypothesistesting2

1. 1. For dummies !!
2. 2. <ul><li>A hypothesis is a prediction about the outcome of an experiment. In market research this could be the result of the out come of a focus or field study </li></ul>
3. 3. <ul><li>Hypothesis testing is a procedure through which sample data is used to evaluate the credibility of a hypothesis </li></ul>
4. 4. <ul><li>State a hypothesis </li></ul><ul><ul><ul><li>Usually in terms of the value of a experiment parameter. </li></ul></ul></ul><ul><ul><ul><li>If the data are consistent with the hypothesis, conclude that the hypothesis was reasonable, and fail to reject it </li></ul></ul></ul>
5. 5. <ul><li>Shoppers in a store playing music shop spend more. </li></ul><ul><li>Independent Variable: </li></ul><ul><ul><li>Music in the store </li></ul></ul><ul><li>Dependent Variable: </li></ul><ul><ul><li>Amount spent in store </li></ul></ul>
6. 6. <ul><li>Obtain a random sample of shoppers who go to stores with music </li></ul><ul><li>Check shop spending </li></ul><ul><li>Compare sample data to hypothesis </li></ul><ul><li>Make decision: </li></ul><ul><ul><ul><li>Reject the hypothesis </li></ul></ul></ul><ul><ul><ul><li>Fail to reject the hypothesis </li></ul></ul></ul>
7. 7. <ul><li>The effect of the Independent Variable (treatment effect) is assumed to: </li></ul><ul><ul><ul><li>Add (or subtract) a constant from every individual’s score </li></ul></ul></ul>
8. 8. <ul><li>Can’t prove hypothesis </li></ul><ul><ul><ul><li>Proof requires evidence for all cases </li></ul></ul></ul>
9. 9. <ul><li>Determine the number of samples (groups, conditions) </li></ul><ul><ul><ul><li>One </li></ul></ul></ul><ul><ul><ul><li>Two </li></ul></ul></ul><ul><ul><ul><li>k (three or more) </li></ul></ul></ul>
10. 10. <ul><li>If there are two or more samples, determine whether they are independent or dependent </li></ul><ul><ul><ul><li>Same group (repeated-measures) </li></ul></ul></ul><ul><ul><ul><li>Match on some other variable(s) known to influence DV (matched-subjects) </li></ul></ul></ul>
11. 11. <ul><li>If there is one sample and the Dependent Variable is at the Interval or Ratio Level of Measurement, is the standard deviation of the population (  , sigma) known: </li></ul><ul><ul><ul><li>If  is known, use a One-Sample z-Test </li></ul></ul></ul><ul><ul><ul><li>If  is unknown, use a One-Sample t-Test </li></ul></ul></ul>
12. 12. <ul><li>Identify the independent variable </li></ul><ul><li>Identify the dependent variable and its level of measurement </li></ul><ul><li>Identify the population to which inferences will be made </li></ul>
13. 13. <ul><li>Determine the appropriate inferential statistical test </li></ul><ul><ul><ul><li>Number of samples </li></ul></ul></ul><ul><ul><ul><li>Nature of samples (if applicable) </li></ul></ul></ul><ul><ul><ul><li>Level of measurement of DV </li></ul></ul></ul><ul><li>State the null hypothesis </li></ul><ul><li>State the alternative hypothesis </li></ul>
14. 14. <ul><li>State Decision Rule: </li></ul><ul><ul><ul><li>If the p-value of the obtained test statistic is less than .05, reject the Null Hypothesis </li></ul></ul></ul><ul><li>Use SPSS to compute the obtained test statistic </li></ul><ul><li>Make decision </li></ul><ul><li>Interpret results </li></ul>
15. 15. <ul><li>State the hypotheses </li></ul>
16. 16. <ul><li>State the null hypothesis </li></ul>
17. 17. <ul><li>The null hypothesis predicts that the Independent Variable (treatment) will have no effect on the Dependent Variable for the population </li></ul>
18. 18. <ul><li>The alternative hypothesis predicts that the Independent Variable (treatment) will have an effect on the Dependent Variable for the population </li></ul>
19. 19. <ul><li>Researcher has reason to believe before conducting the test that a difference will lie in a specified direction </li></ul><ul><ul><ul><li>Prior research </li></ul></ul></ul><ul><ul><ul><li>Theory </li></ul></ul></ul>
20. 20. <ul><li>Researcher has no reason to believe that there will be a difference in a specified direction </li></ul>
21. 21. <ul><li>Because of sampling error, there is likely to be a discrepancy between the sample mean and the population mean </li></ul>
22. 22. <ul><li>Obtained test statistic </li></ul>
23. 23. <ul><li>Reject the null hypothesis </li></ul><ul><ul><ul><li>If sample data is unlikely to have been drawn from a population where the null hypothesis is true </li></ul></ul></ul><ul><ul><ul><li>If the p-value of the obtained test statistic is less than .05 </li></ul></ul></ul>
24. 24. <ul><li>Either: </li></ul><ul><ul><ul><li>Treatment had an effect, could not demonstrate it </li></ul></ul></ul><ul><ul><ul><ul><ul><li>or </li></ul></ul></ul></ul></ul><ul><ul><ul><li>Treatment had no effect </li></ul></ul></ul>
25. 25. Actual State of Affairs Belief Decision H 0 is True H 0 is False H 0 is False Reject H 0 Type I Error False Positive  Correct Rejection 1 -  Power H 0 is True Fail to Reject H 0 Correct Failure to Reject 1 -  Type II Error False Negative 
26. 26. <ul><li>Committed when H 0 is rejected as false although it is true </li></ul>
27. 27. <ul><li>Committed when H 0 is not rejected although it is false </li></ul>
28. 28. <ul><li>Probability that the test will correctly reject a false null hypothesis </li></ul>
29. 29. <ul><li>When a treatment effect exists </li></ul><ul><ul><ul><li>A study may fail to discover it (Type II error, fail to reject a false null hypothesis) </li></ul></ul></ul><ul><ul><ul><li>A study may discover it (reject a false null hypothesis) </li></ul></ul></ul>
30. 30. <ul><li>Reducing alpha (.05 --> .01 --> .001) </li></ul><ul><ul><ul><li>Reduces power </li></ul></ul></ul><ul><ul><ul><li>Inverse relationship between Type I and Type II errors </li></ul></ul></ul>
31. 31. <ul><li>Some inferential statistical tests are more powerful </li></ul>
32. 32. Did Not Commit Crime Committed Crime Guilty Type I Error Convict Innocent Person Correct Verdict Convict Guilty Person Not Guilty Correct Acquittal Fail to Convict Innocent Person Type II Error Fail to Convict Guilty Person
33. 33. <ul><li>Alpha: probability of committing a Type I error </li></ul><ul><ul><ul><li>Reject H 0 although it is true </li></ul></ul></ul><ul><ul><ul><li>Symbolized by  </li></ul></ul></ul>
34. 34. <ul><li>Obtained result attributed to: </li></ul><ul><ul><ul><li>Real effect (reject H 0 ) </li></ul></ul></ul><ul><ul><ul><li>Chance </li></ul></ul></ul>