Producing Data: Experiments BPS - 5th Ed. Chapter 9 1.

Slides:



Advertisements
Similar presentations
DESIGNING EXPERIMENTS
Advertisements

BPS - 5th Ed. Chapter 91 Producing Data: Experiments.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 13 Experiments and Observational Studies.
Chapter 51 Experiments, Good and Bad. Chapter 52 Experimentation u An experiment is the process of subjecting experimental units to treatments and observing.
BPS - 5th Ed. Chapter 91 Producing Data: Experiments.
Experiments and Observational Studies.  A study at a high school in California compared academic performance of music students with that of non-music.
Essential Statistics Chapter 81 Producing Data: Experiments.
Copyright © 2010 Pearson Education, Inc. Chapter 13 Experiments and Observational Studies.
Experiments and Observational Studies. Observational Studies In an observational study, researchers don’t assign choices; they simply observe them. look.
Chapter 13 Notes Observational Studies and Experimental Design
Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 13 Experiments and Observational Studies.
Slide 13-1 Copyright © 2004 Pearson Education, Inc.
Chapter 51 Experiments, Good and Bad. Chapter 52 Thought Question 1 In studies to determine the relationship between two conditions (activities, traits,
BPS - 3rd Ed. Chapter 81 Producing Data: Experiments.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 4 Gathering Data Section 4.3 Good and Poor Ways to Experiment.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 4: Designing Studies Section 4.2 Experiments.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.
Designing Samples Chapter 5 – Producing Data YMS – 5.1.
Experiments and Causal Inference ● We had brief discussion of the role of randomized experiments in estimating causal effects earlier on. Today we take.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.
Chapter 3.1.  Observational Study: involves passive data collection (observe, record or measure but don’t interfere)  Experiment: ~Involves active data.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
AP STATISTICS Section 5.2 Designing Experiments. Objective: To be able to identify and use different experimental design techniques. Experimental Units:
CHAPTER 9: Producing Data: Experiments. Chapter 9 Concepts 2  Observation vs. Experiment  Subjects, Factors, Treatments  How to Experiment Badly 
CHAPTER 9: Producing Data Experiments ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.
CHAPTER 9 Producing Data: Experiments BPS - 5TH ED.CHAPTER 9 1.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.
BPS - 5th Ed. Chapter 91 Producing Data: Experiments.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.
+ Experiments Observational Study versus Experiment In contrast to observational studies, experiments don’t just observe individuals or ask them questions.
CHAPTER 9: Producing Data Experiments ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
CHAPTER 9: Producing Data Experiments ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
Experiments Textbook 4.2. Observational Study vs. Experiment Observational Studies observes individuals and measures variables of interest, but does not.
Statistical Thinking Experiments, Good and Bad
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
CHAPTER 4 Designing Studies
Essential Statistics Producing Data: Experiments
CHAPTER 4 Designing Studies
CHAPTER 4 Designing Studies
CHAPTER 4 Designing Studies
CHAPTER 9: Producing Data— Experiments
Chapter 4: Designing Studies
Statistical Reasoning December 8, 2015 Chapter 6.2
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
Chapter 4: Designing Studies
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
Chapter 4: Designing Studies
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
Basic Practice of Statistics - 5th Edition Producing Data: Experiments
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
10/22/ A Observational Studies and Experiments.
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
Chapter 4: Designing Studies
CHAPTER 4 Designing Studies
Chapter 4: Designing Studies
Presentation transcript:

Producing Data: Experiments BPS - 5th Ed. Chapter 9 1

How Data are Obtained BPS - 5th Ed. Chapter 9 2 Observational Study Observes individuals and measures variables of interest but does not attempt to influence the responses Describes some group or situation Sample surveys are observational studies Experiment Deliberately imposes some treatment on individuals in order to observe their responses Studies whether the treatment causes change in the response.

Experiment versus Observational Study BPS - 5th Ed. Chapter 9 3 Both typically have the goal of detecting a relationship between the explanatory and response variables. Experiment creates differences in the explanatory variable and examine any resulting changes in the response variable (cause-and-effect conclusion) Observational Study observes differences in the explanatory variable and notice any related differences in the response variable (association between variables)

Why Not Always Use an Experiment? BPS - 5th Ed. Chapter 9 4 Sometimes it is unethical or impossible to assign people to receive a specific treatment. Certain explanatory variables, such as handedness or gender, are inherent traits and cannot be randomly assigned.

Confounding BPS - 5th Ed. Chapter 9 5 The problem: in addition to the explanatory variable of interest, there may be other variables (explanatory or lurking) that make the groups being studied different from each other the impact of these variables cannot be separated from the impact of the explanatory variable on the response

Confounding BPS - 5th Ed. Chapter 9 6 The solution: Experiment: randomize experimental units to receive different treatments (possible confounding variables should “even out” across groups) Observational Study: measure potential confounding variables and determine if they have an impact on the response (may then adjust for these variables in the statistical analysis)

Question BPS - 5th Ed. Chapter 9 7 A recent newspaper article concluded that smoking marijuana at least three times a week resulted in lower grades in college. How do you think the researchers came to this conclusion? Do you believe it? Is there a more reasonable conclusion?

Explanatory and Response Variables BPS - 5th Ed. Chapter 9 8 a response variable measures what happens to the individuals in the study an explanatory variable explains or influences changes in a response variable in an experiment, we are interested in studying the response of one variable to changes in the other (explanatory) variables.

Experiments: Vocabulary BPS - 5th Ed. Chapter 9 9 Subjects individuals studied in an experiment Factors the explanatory variables in an experiment Treatment any specific experimental condition applied to the subjects; if there are several factors, a treatment is a combination of specific values of each factor

An Uncontrolled Experiment A college offered a review course for the GMAT Usually it is a classroom course, but this year it was on-line Simple Design Students  Online Course  GMAT Scores The scores were 10% by the students this year than in the past? Conclusion: The on-line course is better. True or False? BPS - 5th Ed. Chapter 9 10

Lab vs. Field Experiments Looking at the GMAT course is it Lab or Field? It has many variables Different student make-up. (More motivated, older) Confounding has occurred between the lurking variables. In a controlled lab environment simple designs work well Subjects  Treatment  Measured Response Outside the lab, uncontrolled experiments often yield worthless results because of confounding with lurking variables. BPS - 5th Ed. Chapter 9 11

Comparative Experiments BPS - 5th Ed. Chapter 9 12 Experiments should compare treatments rather than attempt to assess the effect of a single treatment in isolation Problems when assessing a single treatment with no comparison: conditions better or worse than typical lack of realism (potential problem with any expt) subjects not representative of population placebo effect (power of suggestion)

Randomized Comparative Experiments BPS - 5th Ed. Chapter 9 13 Not only do we want to compare more than one treatment at a time, but we also want to make sure that the comparisons are fair: randomly assign the treatments each treatment should be applied to similar groups or individuals (removes lurking vbls) assignment of treatments should not depend on any characteristic of the subjects or on the judgment of the experimenter

Experiments: Basic Principles BPS - 5th Ed. Chapter 9 14 Randomization to balance out lurking variables across treatments Placebo to control for the power of suggestion Control group to understand changes not related to the treatment of interest

Completely Randomized Design BPS - 5th Ed. Chapter 9 15 In a completely randomized design, all the subjects are allocated at random among all of the treatments. can compare any number of treatments (from any number of factors)

Statistical Significance BPS - 5th Ed. Chapter 9 16 If an experiment (or other study) finds a difference in two (or more) groups, is this difference really important? If the observed difference is larger than what would be expected just by chance, then it is labeled statistically significant. Rather than relying solely on the label of statistical significance, also look at the actual results to determine if they are practically important.

Double-Blind Experiments BPS - 5th Ed. Chapter 9 17 If an experiment is conducted in such a way that neither the subjects nor the investigators working with them know which treatment each subject is receiving, then the experiment is double-blinded to control response bias (from respondent or experimenter)

Pairing or Blocking BPS - 5th Ed. Chapter 9 18 Pairing or blocking to reduce the effect of variation among the subjects different from a completely randomized design, where all subjects are allocated at random among all treatments

Matched Pairs Design BPS - 5th Ed. Chapter 9 19 Compares two treatments Technique: choose pairs of subjects that are as closely matched as possible randomly assign one treatment to one subject and the second treatment to the other subject Sometimes a “pair” could be a single subject receiving both treatments randomize the order of the treatments for each subject

Block Design BPS - 5th Ed. Chapter 9 20 In a block design, the random assignment of individuals to treatments is carried out separately within each block. a single subject could serve as a block if the subject receives each of the treatments (in random order) matched pairs designs are block designs A block is a group of individuals that are known before the experiment to be similar in some way that is expected to affect the response to the treatments.

Pairing or Blocking: Example from Text BPS - 5th Ed. Chapter 9 21 Compare effectiveness of three television advertisements for the same product, knowing that men and women respond differently to advertising. Three treatments: ads (need three groups) Two blocks: men and women Men, Women, and Advertising

Pairing or Blocking: Example from Text BPS - 5th Ed. Chapter 9 22 Men, Women, and Advertising