1 / 44

Lecturer’s desk

Screen. Cabinet. Cabinet. Lecturer’s desk. Table. Computer Storage Cabinet. Row A. 3. 4. 5. 19. 6. 18. 7. 17. 16. 8. 15. 9. 10. 11. 14. 13. 12. Row B. 1. 2. 3. 4. 23. 5. 6. 22. 21. 7. 20. 8. 9. 10. 19. 11. 18. 16. 15. 13. 12. 17. 14. Row C. 1. 2.

alyson
Download Presentation

Lecturer’s desk

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Screen Cabinet Cabinet Lecturer’s desk Table Computer Storage Cabinet Row A 3 4 5 19 6 18 7 17 16 8 15 9 10 11 14 13 12 Row B 1 2 3 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 Row C 1 2 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 Row D 1 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 Row E 1 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 Row F 27 1 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 28 Row G 27 1 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 29 10 19 11 18 16 15 13 12 17 14 28 Row H 27 1 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 Row I 1 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 1 Row J 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 28 27 1 Row K 26 2 25 3 24 4 23 5 6 22 21 7 20 8 9 10 19 11 18 16 15 13 12 17 14 Row L 20 1 19 2 18 3 17 4 16 5 15 6 7 14 13 INTEGRATED LEARNING CENTER ILC 120 9 8 10 12 11 broken desk

  2. Introduction to Statistics for the Social SciencesSBS200, COMM200, GEOG200, PA200, POL200, or SOC200Lecture Section 001, Spring, 2013Room 120 Integrated Learning Center (ILC)10:00 - 10:50 Mondays, Wednesdays & Fridays. Welcome

  3. Please click in My last name starts with a letter somewhere between A. A – D B. E – L C. M – R D. S – Z

  4. Use this as your study guide By the end of lecture today3/6/13 Logic of hypothesis testing Steps for hypothesis testing Levels of significance (Levels of alpha) what does alpha of .05 mean? what does p < 0.05 mean? what does alpha of .01 mean? what does p < 0.01 mean? Type I vs Type II Error One-tail versus Two-tailed test http://today.msnbc.msn.com/id/33411196/ns/today-today_health/

  5. Schedule of readings Before next exam (April 5th) Please read chapters 7 – 11 in Ha & Ha Please read Chapters 2, 3, and 4 in Plous Chapter 2: Cognitive Dissonance Chapter 3: Memory and Hindsight Bias Chapter 4: Context Dependence

  6. Homework due – No homework due No Class on Friday Have a safe and happy spring break

  7. Lab sessions Labs continue This week (even Friday)

  8. Confidence Interval of 95%Has and alpha of 5%α = .05 Critical z 2.58 Critical z -2.58 Confidence Interval of 99% Has and alpha of 1% α = .01 99% Area in the tails is called alpha Critical z 1.96 Critical z -1.96 95% Critical Z separates rare from common scores 90% Critical z 1.64 Critical z -1.64 Confidence Interval of 90% Has and alpha of 10% α = . 10

  9. Rejecting the null hypothesis • The result is “statistically significant” if: • the observed statistic is larger than the critical statistic • observed stat > critical stat If we want to reject the null, we want our t (or z or r or F or x2) to be big!! • the p value is less than 0.05 (which is our alpha) • p < 0.05 If we want to reject the null, we want our “p” to be small!! • we reject the null hypothesis • then we have support for our alternative hypothesis

  10. Deciding whether or not to reject the null hypothesis.05 versus .01 alpha levels What if our observed z = 2.0? How would the critical z change? -1.96 or +1.96 p < 0.05 Yes, Significant difference Reject the null Remember, reject the null if the observed z is bigger than the critical z -2.58 or +2.58 Not a Significant difference Do notReject the null

  11. Deciding whether or not to reject the null hypothesis.05 versus .01 alpha levels What if our observed z = 1.5? How would the critical z change? -1.96 or +1.96 Not a Significant difference Do Not Reject the null Remember, reject the null if the observed z is bigger than the critical z -2.58 or +2.58 Not a Significant difference Do Not Reject the null

  12. Deciding whether or not to reject the null hypothesis.05 versus .01 alpha levels What if our observed z = -3.9? How would the critical z change? -1.96 or +1.96 p < 0.05 Yes, Significant difference Reject the null Remember, reject the null if the observed z is bigger than the critical z -2.58 or +2.58 p < 0.01 Yes, Significant difference Reject the null

  13. Deciding whether or not to reject the null hypothesis.05 versus .01 alpha levels What if our observed z = -2.52? How would the critical z change? -1.96 or +1.96 p < 0.05 Yes, Significant difference Reject the null Remember, reject the null if the observed z is bigger than the critical z -2.58 or +2.58 Not a Significant difference Do notReject the null

  14. Rejecting the null hypothesis • The result is “statistically significant” if: • the observed statistic is larger than the critical statistic • observed stat > critical stat If we want to reject the null, we want our t (or z or r or F or x2) to be big!! • the p value is less than 0.05 (which is our alpha) • p < 0.05 If we want to reject the null, we want our “p” to be small!! • we reject the null hypothesis • then we have support for our alternative hypothesis A note on decision making following procedure versus being right relative to the “TRUTH”

  15. . Decision making: Procedures versus outcome Best guess versus “truth” What does it mean to be correct? • Why do we say: • “innocent until proven guilty” • “not guilty” rather than “innocent” • Is it possible we got a verdict wrong? Review

  16. . The null hypothesis is typically that something is not present, that there is no effect, that there is no difference between population and sample or between treatment and control. Null Hypothesis A measure of sickness people taking drugpeople not taking drug (There are two distributions here, they are just on top of each other) (overlapping) people taking drug people not taking drug A measure of sickness A measure of sickness Null is FALSE Null is TRUE Drug does have effect Something going on Nothing going on No effect of drug There is no difference between the groups There is a difference between the groups Review

  17. Remember: “procedure” vs “TRUTH” . (There are two distributions here, they are just on top of each other) (overlapping) A measure of sickness people taking drug people not taking drug people taking drugpeople not taking drug A measure of sickness A measure of sickness Null is FALSE Null is TRUE Score should fall in this region critical stat critical stat critical stat critical stat Score should fall in one of these regions Score should fall in one of these regions Null is TRUE Null is FALSE No effect of drug Nothing going on Drug does have effect Something going on Review

  18. . Two ways to be right: Status of Null Hypothesis(actually, via magic truth-line) True Ho False Ho Do notReject Ho Decision madeby experimenter Reject Ho 1. “Reject a false null hypothesis” “there really is something going on” 2. “Do not reject a true null hypothesis” “there really is no difference between groups” You are right! Correct decision You are right! Correct decision Review

  19. . Two ways to be wrong: Status of Null Hypothesis(actually, via magic truth-line) True Ho False Ho Do notReject Ho Decision madeby experimenter Reject Ho 1. “Reject a true null hypothesis” say there’s a difference when there’s not (Type I)The score fell in the tails but the null was actually “TRUE” 2. “Do not reject a false null hypothesis” say there really is no difference between groupswhen there really is (Type II) The score fell in the middle but the null was still “FALSE” You are wrong! Type II error(miss) You are wrong! Type I error(false alarm) Review

  20. . Status of Null Hypothesis(actually, via magic truth-line) True Ho False Ho Do notReject Ho Decision madeby experimenter Reject Ho You are wrong! Type II error(miss) You are right! Correct decision You are wrong! Type I error(false alarm) You are right! Correct decision Review

  21. Please hand in your homework

  22. One versus two tail test of significance:Comparing different critical scores(but same alpha level – e.g. alpha = 5%) One versus two tailed test of significance 95% 95% 2.5% 5% 2.5% How would the critical z change? Pros and cons…

  23. One versus two tail test of significance5% versus 1% alpha levels How would the critical z change? 2.5% .5% 5% 2.5% 1% .5% -1.64 or +1.64 -1.96 or +1.96 -2.33 or +2.33 -2.58 or +2.58

  24. One versus two tail test of significance5% versus 1% alpha levels What if our observed z = 2.0? How would the critical z change? -1.64 or +1.64 -1.96 or +1.96 Remember, reject the null if the observed z is bigger than the critical z Reject the null Reject the null -2.33 or +2.33 -2.58 or +2.58 Do notReject the null Do notReject the null

  25. One versus two tail test of significance5% versus 1% alpha levels What if our observed z = 1.75? How would the critical z change? -1.64 or +1.64 -1.96 or +1.96 Do not Reject the null Remember, reject the null if the observed z is bigger than the critical z Reject the null -2.33 or +2.33 -2.58 or +2.58 Do notReject the null Do notReject the null

  26. One versus two tail test of significance5% versus 1% alpha levels What if our observed z = 2.45? How would the critical z change? -1.64 or +1.64 -1.96 or +1.96 Remember, reject the null if the observed z is bigger than the critical z Reject the null Reject the null -2.33 or +2.33 -2.58 or +2.58 Do notReject the null Reject the null

  27. A survey was conducted to see whether men or women superintendents make more money. The null hypothesis is a. men make more money b. women make more money c. no difference between amount of money made d. there is a difference between the amount of money made correct Let’s try one

  28. A survey was conducted to see whether men or women • superintendents make more money. If the null hypothesis was rejected we will conclude that • a. men make more money • b. women make more money • no difference between amount of money made • d. there is a difference between the amount of money made correct Let’s try one

  29. A survey was conducted to see whether men or women • superintendents make more money. A Type I error would be • a. claiming men make more money, when they don’t • b. claiming women make more money, when they don’t • claiming no difference between amount of money made, when there is a difference • d. claiming there is a difference between the amount of money made, when there is no difference correct Let’s try one

  30. A survey was conducted to see whether men or women • superintendents make more money. A Type II error would be • a. claiming men make more money, when they don’t • b. claiming women make more money, when they don’t • claiming no difference between amount of money made, when there is a difference • d. claiming there is a difference between the amount of money made, when there is no difference correct Let’s try one

  31. A survey was conducted to see whether men or women • superintendents make more money. What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  32. A survey was conducted and it was predicted that men would make more money than women. Please test to see whether men • superintendents make more money. What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  33. A survey was conducted and it was predicted that men would make more money than women. They tested to see whether men superintendents make more money. It turns out in this study that women superintendents actually made more money. What can we conclude? a. We reject the null hypothesis b. We do not reject the null hypothesis c. This is not a significant difference No enough information is given e. Both B and C are true correct Fun Fact: In a one-tailed test, if the results are in the UNPREDICTED direction, it is impossible to reject the null hypothesis (and therefore it is “not significant”) Let’s try one

  34. A survey was conducted and it was predicted that men would make more money than women. They tested to see whether men • superintendents make more money. It turns out in this study that men superintendents actually made more money. What can we conclude? • a. We reject the null hypothesis • b. We do not reject the null hypothesis • c. This is not a significant difference • No enough information is given • e. Both B and C are true correct Let’s try one

  35. We want to know whether people are sicker in the summer months or the winter months. Please test to see if there is a difference between the two times of year. What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  36. We want to know whether people are sicker in the summer months or the winter months. Please test to see if people are sicker in the winter than the summer. What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  37. We want to know whether people like cats or dogs better. • What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  38. We want to know whether people like cats better than dogs. • What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  39. We want to know whether blondes have more fun. • What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  40. We want to know whether blondes or brunettes have more fun. • What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  41. We want to know whether SUVs or Pickups get better mileage. • What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  42. We want to know whether SUVs get better gas mileage than Pickups. What type of test is this? • a. One-tailed test • b. Two-tailed test • Three-tailed test • d. No enough information is given correct Let’s try one

  43. Thank you! See you next time!!

More Related