HS 67Ch9: Experiments1 Chapter 9 Producing Data: Experiments.

Slides:



Advertisements
Similar presentations
DESIGNING EXPERIMENTS
Advertisements

MAT 1000 Mathematics in Today's World. Last Time 1.What does a sample tell us about the population? 2.Practical problems in sample surveys.
BPS - 5th Ed. Chapter 91 Producing Data: Experiments.
Chapter 51 Experiments, Good and Bad. Chapter 52 Experimentation u An experiment is the process of subjecting experimental units to treatments and observing.
2: Types of Studies1. 2 In Chapter 2: 2.1 Surveys 2.2 Comparative Studies.
Experiments. Vocabulary  Response Variable – One that measures an outcome or result of study (dependent variable, y)  Explanatory Variable – One that.
BPS - 5th Ed. Chapter 91 Producing Data: Experiments.
Chapter 13: Experiments and Observational Studies
Statistical Thinking Experiments in the Real World
AP Statistics Section 5.2 A Designing Experiments
Introduction to the Design of Experiments
Essential Statistics Chapter 81 Producing Data: Experiments.
BPS - 3rd Ed. Chapter 81 Producing Data: Experiments.
Experiment Subjecting the sample to a controlled treatment. Explanatory variables explain or cause a change in the response variable. These determine the.
October 15. In Chapter 2: 2.1 Surveys 2.2 Comparative Studies.
 Get out your homework and materials for notes!  If you have your parent letter signed and/or supplies, please place it on my desk.
Chapter 51 Experiments, Good and Bad. Chapter 52 Thought Question 1 In studies to determine the relationship between two conditions (activities, traits,
Collection of Data Chapter 4. Three Types of Studies Survey Survey Observational Study Observational Study Controlled Experiment Controlled Experiment.
BPS - 3rd Ed. Chapter 81 Producing Data: Experiments.
Agresti/Franklin Statistics, 1 of 56  Section 4.3 What Are Good Ways and Poor Ways to Experiment?
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 4 Gathering Data Section 4.3 Good and Poor Ways to Experiment.
Experiments and Causal Inference ● We had brief discussion of the role of randomized experiments in estimating causal effects earlier on. Today we take.
Chapter 61 Experiments in the Real World. Chapter 62 Thought Question 1 Suppose you are interested in determining if drinking a glass of red wine each.
Chapter 3.1.  Observational Study: involves passive data collection (observe, record or measure but don’t interfere)  Experiment: ~Involves active data.
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.
Producing Data (C11-13 BVD) C13: Experiments and Observational Studies.
Designing Experiments 5.2. Vocabulary Experimental Units: the individuals on which the experiment is done Subjects: when the experimental units are humans.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 4: Designing Studies Section 4.2 Experiments.
BPS - 5th Ed. Chapter 91 Producing Data: Experiments.
{ Chapter 6.2 Part 2. Experimental Design Terms Terms: Response variable – measures outcome (dependent, y) Explanatory variable – attempts to explain.
Chapter 3 Producing Data. Observational study: observes individuals and measures variables of interest but does not attempt to influence the responses.
Producing Data: Experiments BPS - 5th Ed. Chapter 9 1.
CHAPTER 9: Producing Data Experiments ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
Ten things about Experimental Design AP Statistics, Second Semester Review.
Experiments Textbook 4.2. Observational Study vs. Experiment Observational Studies observes individuals and measures variables of interest, but does not.
 Get out your homework and materials for notes!  If you have your parent letter, supplies, or AP contract, please put them on my desk.
Statistical Thinking Experiments, Good and Bad
Get out your homework and materials for notes!
Get out your homework and materials for notes!
CHAPTER 4 Designing Studies
CHAPTER 4 Designing Studies
Warm-up A newspaper article about an opinion poll says that “43% of Americans approve of the president’s overall job performance.” Toward the end of the.
WARM-UP A factory has 20 assembly lines producing a popular toy. The company wishes to inspect a representative sample of 100 toys. Through sampling,
Essential Statistics Producing Data: Experiments
CHAPTER 4 Designing Studies
Experimental Design Ch 12
MATH 2311 Sections 6.2 & 6.3.
Warmup 1. One study of cell phones and the risk of brain cancer looked at a group of 469 people who have brain cancer. The investigators matched each.
Producing Data, Randomization, and Experimental Design
Producing Data, Randomization, and Experimental Design
Tuesday, October 25, 2016 Warm-up
CHAPTER 4 Designing Studies
Ten things about Experimental Design
Wednesday, October 26, 2016 Warm-up Examine Vocabulary…
CHAPTER 4 Designing Studies
Do Now- Identify the sampling method (Cluster or stratified)
Statistical Reasoning December 8, 2015 Chapter 6.2
Designing Experiments
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
Designing Experiments
Experimental Design Statistics.
CHAPTER 4 Designing Studies
CHAPTER 4 Designing Studies
Principles of Experimental Design
CHAPTER 4 Designing Studies
Presentation transcript:

HS 67Ch9: Experiments1 Chapter 9 Producing Data: Experiments

HS 67Ch9: Experiments2 Experimentation Recall the distinction between experimental designs and observational designs In experimental studies, the investigator exposes individuals to a treatment to ascertain its effects

HS 67Ch9: Experiments3 Vocabulary Subjects = individuals participating in an experiment Factors = specific experimental conditions or interventions applied to subjects Treatment = a combination of a specific set of factors

HS 67Ch9: Experiments4 Example: Effects of Advertising Undergraduate students viewed a 40-minute video program that included ads for a digital camera Two explanatory variables (factors): –Message length: 30-second vs. 90-second –Repetition: commercial shown 1, 3, or 5 times Three response variables –recall of the ads after viewing –attitude toward the camera –intention to purchase

HS 67Ch9: Experiments5 Illustrative Example: Treatments Factor A: length of the commercial (2 levels) Factor B: Number of repetitions (3 levels) treatmentsThus: 2 × 3 = 6 treatments Factor B: Repetitions 1 time3 times5 times Factor A: Length 30 seconds seconds 456 Treatment 3 = 30-second ad five times

HS 67Ch9: Experiments6 Comparison You cannot assess the effects of a treatment without a comparison group because: Many factors contribute to a response Conditions change on their own over time The placebo effect and other passive intervention effects are operative Comparison is first principle of experimentation: The effects of a treatment can be judged only in relation to what would happen in its absence

HS 67Ch9: Experiments7 Randomization Randomization = use of chance mechanisms to assign treatments Randomization balances lurking variables among treatments groups, mitigating confounding by lurking variables! Randomization is the second principle of experimentation

HS 67Ch9: Experiments8 Blinding Blinding = assessment of the response in subjects is made without knowledge of which treatment they are receiving Single blinding = subjects are unaware of treatment group Double blinding = subjects and investigators are blinded Blinding is the third principle of experimentation

HS 67Ch9: Experiments9 Illustrative Example: Quitting Smoking with Nicotine Patches u Explanatory variable: Nicotine patch / placebo patch u 60 subjects, 30 assigned to each treatment group u Response variable: Cessation of smoking (yes/no) u Design outline: Source: JAMA, Feb. 23, 1994, pp Random Assignment Group 1 30 smokers Treatment 1 Nicotine Patch Compare Cessation rates Group 2 30 smokers Treatment 2 Placebo Patch

HS 67Ch9: Experiments10 Randomizing Method Number subjects 01,…,60 Use table of random digits (TABLE B) Select a line arbitrarily (e.g., line102) 73|67|64|71|50|99|40|00|19|27 First four subjects are 50, 40, 19, and 27 Keep using table until you get 30 subjects in Group 1 The remaining subjects are assigned to Group 2

HS 67Ch9: Experiments11 Illustrative Example: Mozart, Relaxation and Performance on Spatial Tasks (Nature, 10/14/93, p. 611) u Subjects (30 undergraduate students) randomly assigned to one of three treatment groups u Group 1: Listen to Mozart u Group 2: Listen to relaxation tapes u Group 3: Silence u Response variable: change in IQ score Random Assignment Group 1 10 students Treatment 1 Mozart Compare Change in IQ score Group 3 10 students Treatment 3 Silence Group 2 10 students Treatment 2 Relaxation

HS 67Ch9: Experiments12 The Logic of Randomization Randomization encourages lurking variables to distribute evenly among treatment groups Difference in the response at end of treatment are then due to either –Treatment or –Chance assignment of treatments If the observed difference is larger than what would be expected just by chance, we say the results are statistically significant