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11.3: Using Inference to make Decisions AP Statistics NPHS

11.3: Using Inference to make Decisions AP Statistics NPHS. Choosing a Level of Significance: Things to think about. (1) How plausible is H 0 ? A study that finds that smoking increases the risk of Alzheimer's. You read a study that claims to have evidence that smoking is really good for you.

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11.3: Using Inference to make Decisions AP Statistics NPHS

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  1. 11.3: Using Inference to make DecisionsAP StatisticsNPHS

  2. Choosing a Level of Significance: Things to think about (1) How plausible is H0? • A study that finds that smoking increases the risk of Alzheimer's. • You read a study that claims to have evidence that smoking is really good for you. (2) What are the consequences of rejecting H0? • You find evidence that cats sleep more than dogs. • You find evidence that a new drug may have harmful side-effects…but your company has invested millions of dollars in an ad campaign for the drug.

  3. Statistical Significance vs. Practical Importance • You decide to run a significance test to see if a particular SAT prep program increases scores on the Math portion. You know from previous research that the average score on the Math section is 510 with a standard deviation of 50. You take a sample of 200 students and find that they have an average score of 515. Use a 5% level of significance. • H0: μ = 510 • Ha: μ > 510 • P-Value: 0.02167 • We can reject the null hypothesis that the prep program does not improve scores…but is a 5 point increase worth anything?

  4. Beware Outliers!!! • Pesky little outliers can destroy the significant of otherwise significant data. • They can also make data appear significant when it actually is not. • Always do a graphical analysis of your data • The effect you are searching for should be evidence in your plots • Confidence intervals can help you get a better idea

  5. Beware Outliers!!! • Be aware of “dropouts” from statistical analysis. • Make sure that all the data is represented in the analysis.

  6. Lack of Significance • Example 11.14 • In an experiment to compare methods for reducing transmission of HIV, subjects were randomly assigned to a treatment group and a control group. Result: the treatment group and the control group had the same rate of HIV infection. Researchers described this as an “incident rate ratio” of 1.00. (>1.00 means greater rate of infection among treatment group, <1.00 means greater rate among control). • The 95% confidence interval for the incident rate ratio was reported at 0.63 to 1.58. • Can you really say that the treatment has no effect?

  7. Lack of Significance • Design a study so that it has a high probability of finding a real effect. • What could you do to increase the chances of finding an effect?

  8. Invalid Statistical Inference • Hawthorne effect • What is the term for a study where neither the subject nor the administrator knows who is getting what treatment?

  9. Invalid Statistical Inference • The importance of an SRS from the population of INTEREST.

  10. Multiple Analyses • A study using an alpha level of 0.05 is run for 20 different types of soda to see if there is an association between drinking soda and scoring well on a math test. • It is found that one soda, Mountain Dew, did increase scores. • Why is this not good evidence of an effect?

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