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Stat 31, Section 1, Last Time Hypothesis Tests –H -, H 0 or H + version of testing –P-values – small for strong evidence –1-sided (strong evidence for “>” or “<“) –2-sided (strong evidence for “different”) Cutoffs –Yes – no (P-val < 0.05, or not?) –Gray level (interpret level…)

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Hypothesis Testing, III CAUTION: Read problem carefully to distinguish between: One-sided Hypotheses - like: Two-sided Hypotheses - like:

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Hypothesis Testing Hints: Use 1-sided when see words like: –Smaller –Greater –In excess of Use 2-sided when see words like: –Equal –Different Always write down H 0 and H A –Since then easy to label “more conclusive” –And get partial credit….

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Hypothesis Testing E.g. Text book problem 6.32: In each of the following situations, a significance test for a population mean, mu is called for. State the null hypothesis, H 0 and the alternative hypothesis, H A in each case….

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Hypothesis Testing E.g. 6.32a Experiments on learning in animals sometimes measure how long it takes a mouse to find its way through mazes. The mean time is 18 seconds for one particular maze. A researcher thinks that a loud noise will cause the nice to complete the maze faster. She measures how long each of 10 mice takes with a noise as stimulus. = time to finish with loud noise.

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Hypothesis Testing E.g. 6.32b The examinations in a large history class are scaled after grading so that the mean score is 50. A teaching assistant thinks that his students have a higher average score than the class as a whole. His students can be considered as a sample from the population of all students he might teach, so he compares their score with 50. = average score for all students of this TA

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Hypothesis Testing E.g. 6.32c The Census Bureau reports that households spend an average of 31% of their total spending on housing. A homebuilders association in Cleveland wonders if the national finding applies in their area. They interview a sample of 40 households in the Cleveland metropolitan area to learn what percent of their spending goes toward housing. = avg. % for housing in Cleveland

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Hypothesis Testing E.g. Textbook problem 6.34 Translate each of the following research questions into appropriate and

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Hypothesis Testing E.g. 6.34a Census Bureau data shows that the mean household income in the area served by a shopping mall is $62,500 per year. A market research firm questions shoppers at the mall to find out whether the mean household income of mall shoppers is higher that that of the general population. = average income of mall shoppers

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Hypothesis Testing E.g. 6.34b Last year, your company’s service technicians took an average of 2.6 hours to respond to trouble calls from business customers who had purchased service contracts. Do this year’s data show a different average response size? = average response time

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Hypothesis Testing HW on setting up hypotheses: 6.31, 6.33

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Hypothesis Testing Connection between Confidence Intervals and Hypothesis Tests: Reject at Level 0.05 P-value < 0.05 dist’n Area < 0.05 0.95 margin of error

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Hypothesis Testing & CIs Reject at Level 0.05 Notes: 1.This is why EXCEL’s CONFIDENCE function uses = 1 – coverage prob. 2.If only care about 2-sided hypos, then could work only with CIs (and not learn about hypo. tests)

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Hypothesis Testing & CIs HW: 6.63, 6.64 (a. [59.99,63.59] b. No, 61.3 inside c. No, 63 inside)

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Hypothesis Testing The three traps of Hypothesis Testing (and how to avoid them…) Trap 1: Statistically Significant is different from Really Significant (don’t confuse them)

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Hypothesis Testing Traps Trap 1: Statistically Significant is different from Really Significant E.g. To test a painful diet program, 10,000 people were put on it. Their average weight loss was 1.7 lbs, with s = 73. Assess “significance” by hypothesis testing.

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Hypothesis Testing Traps Trap 1: Statistically Significant is different from Really Significant See Class Example 23: Trap 1 https://www.unc.edu/~marron/UNCstat31-2005/Stat31Eg23.xls P-value = 0.0099 Strongly Statistically Significant Careful: Is this practically significant?

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Hypothesis Testing Traps Trap 1, e.g: Is this practically significant? NO! Not worth painful diet to lose 1.7 lbs. Resolution: Hypo. testing resolves question: Could observed results be due to chance variation? Answer here is no, since n is really large.

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Hypothesis Testing Traps Trap 1, e.g: Is this practically significant? Answer here is no, since n is really large. But this is different from question: Do results show a big difference?

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Hypothesis Testing Traps Trap 2: Insignificant results do not mean nothing is there, Only: Didn’t have strong enough data to actually prove results. E.g. Class 23, Trap 2 https://www.unc.edu/~marron/UNCstat31-2005/Stat31Eg23.xls

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Hypothesis Testing Traps Trap 3: Try enough tests, and you will find “something” even where it doesn’t exist. Revisit Class Example 21, Q4 https://www.unc.edu/~marron/UNCstat31-2005/Stat31Eg21.xls We saw about 5% of CIs don’t cover. So, (using CI – Hypo Test connection), expect about 5% of tests to choose H A, (and claim “strong evidence) even when H 0 true.

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Hypothesis Testing Traps Strategies to avoid Trap 3: 1.Scientific Method: Form Hypothesis tests once. 2.For repeated tests: use careful adjustments: (beyond scope of this course) Get help if needed

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Hypothesis Testing Traps HW: 6.69, 6.71, 6.73, 6.75, 6.77

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And now for something completely different… A statistician’s view on politics… Some Current Controversial Issues: North Carolina State Lottery Replace Social Security by Individual Retirement Plans Debate is passionate, (natural for complex and important issues) But what is missing?

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And now for something completely different… Review Ideas on State Lotteries, from our study of Expected Value Not an obvious choice because: Gambling is (at least) unsavory: –Religious objections –Some like it too much –Destroys some lives

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And now for something completely different… State Lotteries, not an obvious choice: The only totally voluntary tax: –Nobody required, unlike all other taxes –Money often used for education –Good or bad, given state of economy??? Highest tax burden on the poor –Poor enjoy playing much more –Higher taxes on poor better for society??? –Tendency towards “rich get richer”???

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And now for something completely different… What about Individual Retirement Plans: Main Benefit: On average individual investments return greater yields than government investments So can we conclude: “Overall we are all better off”??? Since more total money to go around?

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And now for something completely different… Very common mistake in this reasoning: Notice “on average” part of statement Should also think about variation about the average???

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And now for something completely different… Variation about average Issue 1: Should think of population of people Average is over this population Except some to do great And expect some to lose everything What will the percentage of losers be? What do we do with those who lose all? What will that cost?

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And now for something completely different… Variation about average Issue 2: Also are averaging over time Overall gains of stock market happen only over this average Some need $$$ when market is down How often will this happen? How do we deal with it?

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And now for something completely different… Main concept I hope you carry away from this course: Variation is a fundamental concept Look for it Think about it Ask questions about it (Vital to informed citizenship)

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And now for something completely different… Australian joke about Variation: Did you hear about the man who drowned in a lake with average depth 6 inches?

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And now for something completely different… Australian joke about Variation: He understood “average”, but not variation about the average

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And now for something completely different… Really have such lakes? Yes, in Australia

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And now for something completely different… Suggestions of such issues (politics, controversy…) for discussion are welcome….

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Hypothesis Testing Other views of hypothesis testing: View 2: Z-scores Idea: instead of reporting p-value (to assess statistical significance) Report the Z-score A different way of measuring significance

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Hypothesis Testing – Z scores E.g. Fast Food Menus: Test Using P-value = P{what saw or m.c.| H 0 & H A bd’ry}

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Hypothesis Testing – Z scores P-value = P{what saw or or m.c.| H 0 & H A bd’ry}

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Hypothesis Testing – Z scores P-value This is the Z-score Computation: Class E.g. 22, Part 6 https://www.unc.edu/~marron/UNCstat31-2005/Stat31Eg22.xls Distribution: N(0,1)

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Hypothesis Testing – Z scores P-value So instead of reporting tail probability, Report this cutoff instead, as “SDs away from mean $20,000” HW: 6.59, but use NORMDIST, not Table D

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Hypothesis Testing View 3: level testing Idea: instead of reporting P-value, choose a fixed level, say 5% Then reject H 0, i.e. find strong evidence… When P-value < 0.05 (more generally ) (slight recasting of yes-no version of testing) HW: 6.53 (careful, already assigned above)

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