Dr. Allen Back. Oct. 7, 2016
|
|
|
- Wilfred Wiggins
- 5 years ago
- Views:
Transcription
1 Dr. Allen Back Oct. 7, 2016 al
2 Was it Fair? The first draft lottery during the Vietnam War: 366 balls labeled by dates. Mixed up and pulled out in a random order. al
3 Was it Fair? Scatterplot al
4 Was it Fair? Boxplots for each month al
5 Was it Fair? Scatterplot with Line al
6 Was it Fair? Correlation Display al
7 Was it Fair? Correlation Display al Around 1 in a thousand chance of a correlation coefficient this far from 0 if the lottery was fair.
8 Was it Fair? Around 1 in a thousand chance of a correlation coefficient this far from 0 if the lottery was fair. The balls were probably not mixed well enough. al
9 How Many Rooms Can x Clean? x crews working for a building contractor go out each night and clean y rooms. Understand the relationship? al
10 How Many Rooms Can x Clean? Scatterplot al
11 How Many Rooms Can x Clean? Num summary al
12 How Many Rooms Can x Clean? RoomsCleaned Summary al
13 How Many Rooms Can x Clean? Scatterplot with Line al
14 How Many Rooms Can x Clean? Display al
15 How Many Rooms Can x Clean? Display al
16 How Many Rooms Can x Clean? Display al RoomsCleaned = 3.70 Num
17 How Many Rooms Can x Clean? Residual Plot al
18 How Many Rooms Can x Clean? There are important deviations from the the assumptions of an ideal linear regression model here. al
19 by Locality (rm outliers?, transform?) vs Housing Prices in 1996 Crime Rate is Crimes Per 1000 Housing Prices in Dollars al
20 by Locality (rm outliers?, transform?) scatterplot al
21 by Locality (rm outliers?, transform?) with regression line al ĤP = 577 CR + 177K r 2 =.06 (SMALL)
22 by Locality (rm outliers?, transform?) regression display al
23 by Locality (rm outliers?, transform?) Residuals al
24 by Locality (rm outliers?, transform?) Now analyze without the Center City Outlier al
25 by Locality (rm outliers?, transform?) scatterplot al
26 by Locality (rm outliers?, transform?) with regression line al ĤP = 2290 CR + 225K r 2 =.18 (vs..06 before)
27 by Locality (rm outliers?, transform?) regression display al
28 by Locality (rm outliers?, transform?) Residuals al
29 by Locality (rm outliers?, transform?) Now transform from CR to 1 CR. al
30 by Locality (rm outliers?, transform?) scatterplot al
31 by Locality (rm outliers?, transform?) with regression line al ĤP = 1.3M But Center City included. 1 CR K r 2 =.17
32 by Locality (rm outliers?, transform?) regression display al
33 by Locality (rm outliers?, transform?) Residuals al
34 For both men and women: 1 IQ s average about SD about 15 al
35 A large study showed: 1 For men with IQ of 140, average wife s IQ was For women with IQ of 120, average husband s s IQ was Note the Z score of 140 is twice the Z score of The above kind of comparison is typical because of the two regression lines. al
36 al
37 e.g. if r =.5, 1 Ẑ w = rz m, Z m = Ẑ w = Ẑ m = rz w, Z w = Ẑ m =.667. al
38 Baseball s All-Time by Michael J. Schell PUP 1999 al
39 al
40 al
41 Corrections for Late career batting decline. (first at bats) Hitting Feasts/Famines Z-scores (using mid-decade averages) (Std Dev for Assessing Talent Pool Variability) Ball Park Differences al
42 Adjusting for Late Career Declines al
43 For Z-scores al
44 Ball Parks Do Matter! al
45 Hits are to Win Games! al
46 An Interesting Idea: The leftover change in batting average after taking into account the regression of Mean Adjusted Batting Average on Winning Percentage is viewed as a Ballpark effect. al
47 al
48 Establishing ation Association strong. (Attempts Basically Hill s Criteria) al
49 Establishing ation Association strong. Association consistent. (Attempts Basically Hill s Criteria) al
50 Establishing ation (Attempts Basically Hill s Criteria) Association strong. Association consistent. Higher doses give stronger responses. al
51 Establishing ation (Attempts Basically Hill s Criteria) Association strong. Association consistent. Higher doses give stronger responses. Alleged cause precedes effect. al
52 Establishing ation (Attempts Basically Hill s Criteria) Association strong. Association consistent. Higher doses give stronger responses. Alleged cause precedes effect. Alleged cause is plausible. al
53 Establishing ation (Attempts Basically Hill s Criteria) Association strong. Association consistent. Higher doses give stronger responses. Alleged cause precedes effect. Alleged cause is plausible. Rule out other plausible explanations. al
54 Establishing ation al (Attempts Basically Hill s Criteria) Association strong. Association consistent. Higher doses give stronger responses. Alleged cause precedes effect. Alleged cause is plausible. Rule out other plausible explanations. This is hard to do reliably.
55 Establishing ation al (Attempts Basically Hill s Criteria) Association strong. Association consistent. Higher doses give stronger responses. Alleged cause precedes effect. Alleged cause is plausible. Rule out other plausible explanations. This is hard to do reliably. ation is much clearer!
56 Basic ation Strategies 1) Control extraneous sources of variation. al
57 Basic ation Strategies 1) Control extraneous sources of variation. 2) Randomize to deal with uncontrollable sources of variation. al
58 Basic ation Strategies 1) Control extraneous sources of variation. 2) Randomize to deal with uncontrollable sources of variation. 3) Replicate to increase accuracy and gain greater confidence in the scope of your conclusions. al
59 Basic ation Strategies 1) Control extraneous sources of variation. 2) Randomize to deal with uncontrollable sources of variation. 3) Replicate to increase accuracy and gain greater confidence in the scope of your conclusions. 4) Block when possible to increase accuracy/sensitivity and better control variability. al
60 Sampling Words Sample vs. Population Sample Statistic vs. Population Parameter Sampling Frame (not in your text?) Voluntary Response Sample (not in your text?) Convenience Sample Biased Sample Simple Random Sample (SRS) al
61 Sampling Words Census Strata Stratified Random Sample Cluster Sample Multistage Sample al
62 Sampling Words Matching in an observational study cohort Undercoverage (not in your text?) Non-Response Bias Response Bias (not in your text?) Leading Questions Sampling Variability al
63 Stratification Strata groups of homogeneous individuals. Stratified Random Sample same probability of choice within each group. al
64 Stratification Strata groups of homogeneous individuals. Stratified Random Sample same probability of choice within each group. Advantages include: Every stratum well represented. Can be more accurate for a given sample size. Strata with greater variability should be better represented. al
65 Types of Bias Response bias vs. voluntary response bias vs. non-response bias? al
66 Types of Bias Response bias vs. voluntary response bias vs. non-response bias? Response Bias: problems in the questions or how they are asked. al
67 Types of Bias Response bias vs. voluntary response bias vs. non-response bias? Voluntary Response Bias: problems in surveys where only volunteers participate. al
68 Types of Bias Response bias vs. voluntary response bias vs. non-response bias? Non-Response Bias: problems associated with which people are missing in the final results. al
69 Types of Bias Response bias vs. voluntary response bias vs. non-response bias? Undercoverage: groups somewhat missing from the sampling frame. al
70 s Observational Study vs. Prospective vs Retrospective Study Factor in an experiment Level Treatment al
71 s Control Group Single-Blind vs. Double-Blind One Factor vs. Two Factor Placebo Placebo Effect al
72 s Block Block Matched Pairs Confounding Variables Statistically Significant Effect al
73 Factors and Levels Factors vs. Levels vs. Treatments? al
74 Factors and Levels Factors vs. Levels vs. Treatments? Factor in an : Variable being manipulated. al
75 Factors and Levels Factors vs. Levels vs. Treatments? Levels: Values of a factor. al
76 Factors and Levels Factors vs. Levels vs. Treatments? Treatment: What is actively done to the experimental units. al
77 Block Related Block vs. Block vs. Matched Pairs al
78 Block Related Block vs. Block vs. Matched Pairs Block: homogenous group similar in some important way. al
79 Block Related Block vs. Block vs. Matched Pairs Block : random within each block. al
80 Block Related Block vs. Block vs. Matched Pairs Matched Pairs : block size of 2. al
Dr. Allen Back. Sep. 30, 2016
Dr. Allen Back Sep. 30, 2016 Extrapolation is Dangerous Extrapolation is Dangerous And watch out for confounding variables. e.g.: A strong association between numbers of firemen and amount of damge at
Vocabulary. Bias. Blinding. Block. Cluster sample
Bias Blinding Block Census Cluster sample Confounding Control group Convenience sample Designs Experiment Experimental units Factor Level Any systematic failure of a sampling method to represent its population
aps/stone U0 d14 review d2 teacher notes 9/14/17 obj: review Opener: I have- who has
aps/stone U0 d14 review d2 teacher notes 9/14/17 obj: review Opener: I have- who has 4: You should be able to explain/discuss each of the following words/concepts below... Observational Study/Sampling
AP Statistics Exam Review: Strand 2: Sampling and Experimentation Date:
AP Statistics NAME: Exam Review: Strand 2: Sampling and Experimentation Date: Block: II. Sampling and Experimentation: Planning and conducting a study (10%-15%) Data must be collected according to a well-developed
Chapter 5: Producing Data
Chapter 5: Producing Data Key Vocabulary: observational study vs. experiment confounded variables population vs. sample sampling vs. census sample design voluntary response sampling convenience sampling
Chapter 1: Exploring Data
Chapter 1: Exploring Data Key Vocabulary:! individual! variable! frequency table! relative frequency table! distribution! pie chart! bar graph! two-way table! marginal distributions! conditional distributions!
Unit 1 Exploring and Understanding Data
Unit 1 Exploring and Understanding Data Area Principle Bar Chart Boxplot Conditional Distribution Dotplot Empirical Rule Five Number Summary Frequency Distribution Frequency Polygon Histogram Interquartile
Sampling. (James Madison University) January 9, / 13
Sampling The population is the entire group of individuals about which we want information. A sample is a part of the population from which we actually collect information. A sampling design describes
Experimental Design There is no recovery from poorly collected data!
Experimental Design There is no recovery from poorly collected data! Vocabulary List n Look over the list of words. n Count how many you feel you know. n Place a dot on the number line above that number.
Understandable Statistics
Understandable Statistics correlated to the Advanced Placement Program Course Description for Statistics Prepared for Alabama CC2 6/2003 2003 Understandable Statistics 2003 correlated to the Advanced Placement
Examining Relationships Least-squares regression. Sections 2.3
Examining Relationships Least-squares regression Sections 2.3 The regression line A regression line describes a one-way linear relationship between variables. An explanatory variable, x, explains variability
AP Stats Review for Midterm
AP Stats Review for Midterm NAME: Format: 10% of final grade. There will be 20 multiple-choice questions and 3 free response questions. The multiple-choice questions will be worth 2 points each and the
UNIT I SAMPLING AND EXPERIMENTATION: PLANNING AND CONDUCTING A STUDY (Chapter 4)
UNIT I SAMPLING AND EXPERIMENTATION: PLANNING AND CONDUCTING A STUDY (Chapter 4) A DATA COLLECTION (Overview) When researchers want to make conclusions/inferences about an entire population, they often
Chapter 3. Producing Data
Chapter 3 Producing Data Types of data collected Anecdotal data data collected haphazardly (not representative!!) Available data existing data (examples: internet, library, census bureau,.) Gather own
Chapter 1 - Sampling and Experimental Design
Chapter 1 - Sampling and Experimental Design Read sections 1.3-1.5 Sampling (1.3.3 and 1.4.2) Sampling Plans: methods of selecting individuals from a population. We are interested in sampling plans such
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Exam Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Identify the W's for the description of data. 1) A survey of bicycles parked outside college
Unit 3: Collecting Data. Observational Study Experimental Study Sampling Bias Types of Sampling
Unit 3: Collecting Data Observational Study Experimental Study Sampling Bias Types of Sampling Feb 7 10:12 AM The step of data collection is critical to obtain reliable information for your study. 2 Types
Outline. Practice. Confounding Variables. Discuss. Observational Studies vs Experiments. Observational Studies vs Experiments
1 2 Outline Finish sampling slides from Tuesday. Study design what do you do with the subjects/units once you select them? (OI Sections 1.4-1.5) Observational studies vs. experiments Descriptive statistics
REVIEW FOR THE PREVIOUS LECTURE
Slide 2-1 Calculator: The same calculator policies as for the ACT hold for STT 315: http://www.actstudent.org/faq/answers/calculator.html. It is highly recommended that you have a TI-84, as this is the
HPS301 Exam Notes- Contents
HPS301 Exam Notes- Contents Week 1 Research Design: What characterises different approaches 1 Experimental Design 1 Key Features 1 Criteria for establishing causality 2 Validity Internal Validity 2 Threats
3. For a $5 lunch with a 55 cent ($0.55) tip, what is the value of the residual?
STATISTICS 216, SPRING 2006 Name: EXAM 1; February 21, 2006; 100 points. Instructions: Closed book. Closed notes. Calculator allowed. Double-sided exam. NO CELL PHONES. Multiple Choice (3pts each). Circle
Observational study is a poor way to gauge the effect of an intervention. When looking for cause effect relationships you MUST have an experiment.
Chapter 5 Producing data Observational study Observes individuals and measures variables of interest but does not attempt to influence the responses. Experiment Deliberately imposes some treatment on individuals
04/12/2014. Research Methods in Psychology. Chapter 6: Independent Groups Designs. What is your ideas? Testing
Research Methods in Psychology Chapter 6: Independent Groups Designs 1 Why Psychologists Conduct Experiments? What is your ideas? 2 Why Psychologists Conduct Experiments? Testing Hypotheses derived from
11 questions to help you make sense of a case control study
Critical Appraisal Skills Programme (CASP) making sense of evidence 11 questions to help you make sense of a case control study How to use this appraisal tool Three broad issues need to be considered when
STATISTICS & PROBABILITY
STATISTICS & PROBABILITY LAWRENCE HIGH SCHOOL STATISTICS & PROBABILITY CURRICULUM MAP 2015-2016 Quarter 1 Unit 1 Collecting Data and Drawing Conclusions Unit 2 Summarizing Data Quarter 2 Unit 3 Randomness
Section 6.1 Sampling. Population each element (or person) from the set of observations that can be made (entire group)
Section 6.1 Sampling Population each element (or person) from the set of observations that can be made (entire group) Sample a subset of the population Census systematically getting information about an
Chapter 3. Producing Data
Chapter 3. Producing Data Introduction Mostly data are collected for a specific purpose of answering certain questions. For example, Is smoking related to lung cancer? Is use of hand-held cell phones associated
1.4 - Linear Regression and MS Excel
1.4 - Linear Regression and MS Excel Regression is an analytic technique for determining the relationship between a dependent variable and an independent variable. When the two variables have a linear
I. Introduction and Data Collection B. Sampling. 1. Bias. In this section Bias Random Sampling Sampling Error
I. Introduction and Data Collection B. Sampling In this section Bias Random Sampling Sampling Error 1. Bias Bias a prejudice in one direction (this occurs when the sample is selected in such a way that
CRITICAL APPRAISAL SKILLS PROGRAMME Making sense of evidence about clinical effectiveness. 11 questions to help you make sense of case control study
CRITICAL APPRAISAL SKILLS PROGRAMME Making sense of evidence about clinical effectiveness 11 questions to help you make sense of case control study General comments Three broad issues need to be considered
2.75: 84% 2.5: 80% 2.25: 78% 2: 74% 1.75: 70% 1.5: 66% 1.25: 64% 1.0: 60% 0.5: 50% 0.25: 25% 0: 0%
Capstone Test (will consist of FOUR quizzes and the FINAL test grade will be an average of the four quizzes). Capstone #1: Review of Chapters 1-3 Capstone #2: Review of Chapter 4 Capstone #3: Review of
DO NOT OPEN THIS BOOKLET UNTIL YOU ARE TOLD TO DO SO
NATS 1500 Mid-term test A1 Page 1 of 8 Name (PRINT) Student Number Signature Instructions: York University DIVISION OF NATURAL SCIENCE NATS 1500 3.0 Statistics and Reasoning in Modern Society Mid-Term
Biostatistics for Med Students. Lecture 1
Biostatistics for Med Students Lecture 1 John J. Chen, Ph.D. Professor & Director of Biostatistics Core UH JABSOM JABSOM MD7 February 14, 2018 Lecture note: http://biostat.jabsom.hawaii.edu/education/training.html
Homework #3. SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.
Homework #3 Name Due Due on on February Tuesday, Due on February 17th, Sept Friday 28th 17th, Friday SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Fill
GATHERING DATA. Chapter 4
GATHERING DATA Chapter 4 4.3 What are Good and Poor Ways to Experiment? Elements of an Experiment Experimental units: Subjects Treatment: Conditions imposed on subjects Explanatory variable: Defines groups
Sta 309 (Statistics And Probability for Engineers)
Instructor: Prof. Mike Nasab Sta 309 (Statistics And Probability for Engineers) Chapter (1) 1. Statistics: The science of collecting, organizing, summarizing, analyzing numerical information called data
AP Statistics. Semester One Review Part 1 Chapters 1-5
AP Statistics Semester One Review Part 1 Chapters 1-5 AP Statistics Topics Describing Data Producing Data Probability Statistical Inference Describing Data Ch 1: Describing Data: Graphically and Numerically
Math 140 Introductory Statistics
Math 140 Introductory Statistics Professor Silvia Fernández Sample surveys and experiments Most of what we ve done so far is data exploration ways to uncover, display, and describe patterns in data. Unfortunately,
Pre-Calculus Multiple Choice Questions - Chapter S4
1 Which of the following represents the dependent variable in experimental design? a Treatment b Factor 2 Which of the following represents the independent variable in experimental design? a Treatment
Section 1.1 What is Statistics?
Chapter 1 Getting Started Name Section 1.1 What is Statistics? Objective: In this lesson you learned how to identify variables in a statistical study, distinguish between quantitative and qualitative variables,
MAT 155. Chapter 1 Introduction to Statistics. Key Concept. Basics of Collecting Data. August 20, S1.5_3 Collecting Sample Data
MAT 155 Dr. Claude Moore Cape Fear Community College Chapter 1 Introduction to Statistics 1 1 Review and Preview 1 2 Statistical Thinking 1 3 Types of Data 1 4 Critical Thinking 1 5 Collecting Sample Data
Villarreal Rm. 170 Handout (4.3)/(4.4) - 1 Designing Experiments I
Statistics and Probability B Ch. 4 Sample Surveys and Experiments Villarreal Rm. 170 Handout (4.3)/(4.4) - 1 Designing Experiments I Suppose we wanted to investigate if caffeine truly affects ones pulse
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Statistics Final Review Semeter I Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Provide an appropriate response. 1) The Centers for Disease
Chapter 1 Data Collection
Chapter 1 Data Collection OUTLINE 1.1 Introduction to the Practice of Statistics 1.2 Observational Studies versus Designed Experiments 1.3 Simple Random Sampling 1.4 Other Effective Sampling Methods 1.5
1. What is the difference between positive and negative correlations?
1. What is the difference between positive and negative correlations? 2. Can correlations make predictions? 3. Can correlations prove causation? 4. What are illusory correlations? We can take data from
Chapter 1: Data Collection Pearson Prentice Hall. All rights reserved
Chapter 1: Data Collection 2010 Pearson Prentice Hall. All rights reserved 1-1 Statistics is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer
Unit 1 History and Methods Chapter 1 Thinking Critically with Psychological Science
Myers PSYCHOLOGY (7th Ed) Unit 1 History and Methods Chapter 1 Thinking Critically with James A. McCubbin, PhD Clemson University Worth Publishers Fact vs. Falsehood 1. Human intuition is remarkably accurate
Chapter 2. The Data Analysis Process and Collecting Data Sensibly. Copyright 2005 Brooks/Cole, a division of Thomson Learning, Inc.
Chapter 2 The Data Analysis Process and Collecting Data Sensibly Important Terms Variable A variable is any characteristic whose value may change from one individual to another Examples: Brand of television
Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making effective decisions
Readings: OpenStax Textbook - Chapters 1 5 (online) Appendix D & E (online) Plous - Chapters 1, 5, 6, 13 (online) Introductory comments Describe how familiarity with statistical methods can - be associated
Chapter 4: More about Relationships between Two-Variables
1. Which of the following scatterplots corresponds to a monotonic decreasing function f(t)? A) B) C) D) G Chapter 4: More about Relationships between Two-Variables E) 2. Which of the following transformations
Chapter 4 Review. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.
Name: Class: Date: Chapter 4 Review Multiple Choice Identify the choice that best completes the statement or answers the question. 1. Use Scenario 4-1. The newspaper asks you to comment on their survey
Subject index. bootstrap...94 National Maternal and Infant Health Study (NMIHS) example
Subject index A AAPOR... see American Association of Public Opinion Research American Association of Public Opinion Research margins of error in nonprobability samples... 132 reports on nonprobability
Section 6.1 Sampling. Population each element (or person) from the set of observations that can be made (entire group)
Section 6.1 Sampling Population each element (or person) from the set of observations that can be made (entire group) Sample a subset of the population Census systematically getting information about an
q3_2 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
q3_2 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Provide an appropriate response. 1) The relationship between the number of games won by a minor
Design of Experiments & Introduction to Research
Design of Experiments & Introduction to Research 1 Design of Experiments Introduction to Research Definition and Purpose Scientific Method Research Project Paradigm Structure of a Research Project Types
Critical Appraisal Series
Definition for therapeutic study Terms Definitions Study design section Observational descriptive studies Observational analytical studies Experimental studies Pragmatic trial Cluster trial Researcher
AP Statistics Unit 4.2 Day 3 Notes: Experimental Design. Expt1:
AP Statistics Unit 4.2 Day 3 Notes: Experimental Design OBSERVATION -observe outcomes without imposing any treatment EXPERIMENT -actively impose some treatment in order to observe the response I ve developed
Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making effective decisions
Readings: OpenStax Textbook - Chapters 1 5 (online) Appendix D & E (online) Plous - Chapters 1, 5, 6, 13 (online) Introductory comments Describe how familiarity with statistical methods can - be associated
Ch 4 Practice Test. Multiple Choice Identify the choice that best completes the statement or answers the question. Scenario 4-1
Ch 4 Practice Test Multiple Choice Identify the choice that best completes the statement or answers the question. Scenario 4-1 A sportswriter wants to know how strongly Lafayette residents support the
WDHS Curriculum Map Probability and Statistics. What is Statistics and how does it relate to you?
WDHS Curriculum Map Probability and Statistics Time Interval/ Unit 1: Introduction to Statistics 1.1-1.3 2 weeks S-IC-1: Understand statistics as a process for making inferences about population parameters
General Biostatistics Concepts
General Biostatistics Concepts Dongmei Li Department of Public Health Sciences Office of Public Health Studies University of Hawai i at Mānoa Outline 1. What is Biostatistics? 2. Types of Measurements
Define the population Determine appropriate sample size Choose a sampling design Choose an appropriate research design
Numbers! Observation Study: observing individuals and measuring variables of interest without attempting to influence the responses Correlational Research: examining the relationship between two variables
CHAPTER 5: PRODUCING DATA
CHAPTER 5: PRODUCING DATA 5.1: Designing Samples Exploratory data analysis seeks to what data say by using: These conclusions apply only to the we examine. To answer questions about some of individuals
Lecture Slides. Elementary Statistics Eleventh Edition. by Mario F. Triola. and the Triola Statistics Series 1.1-1
Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by Mario F. Triola 1.1-1 Chapter 1 Introduction to Statistics 1-1 Review and Preview 1-2 Statistical Thinking 1-3
What you should know before you collect data. BAE 815 (Fall 2017) Dr. Zifei Liu
What you should know before you collect data BAE 815 (Fall 2017) Dr. Zifei Liu Zifeiliu@ksu.edu Types and levels of study Descriptive statistics Inferential statistics How to choose a statistical test
Variable Data univariate data set bivariate data set multivariate data set categorical qualitative numerical quantitative
The Data Analysis Process and Collecting Data Sensibly Important Terms Variable A variable is any characteristic whose value may change from one individual to another Examples: Brand of television Height
P. 266 #9, 11. p. 289 # 4, 6 11, 14, 17
P. 266 #9, 11 9. Election. a) Answers will vary. A component is one voter voting. An outcome is a vote for our candidate. Using two random digits, 00-99, let 01-55 represent a vote for your candidate,
Chapter 13 Summary Experiments and Observational Studies
Chapter 13 Summary Experiments and Observational Studies What have we learned? We can recognize sample surveys, observational studies, and randomized comparative experiments. o These methods collect data
Section Experiments
Section 4.2 - Experiments There are two different ways to produce/gather data in order to answer specific questions: 1. Observational Studies Observes individuals and measures variables of interest but
You can t fix by analysis what you bungled by design. Fancy analysis can t fix a poorly designed study.
You can t fix by analysis what you bungled by design. Light, Singer and Willett Or, not as catchy but perhaps more accurate: Fancy analysis can t fix a poorly designed study. Producing Data The Role of
Observation Studies, Sampling Designs and Bias
Observation Studies, Sampling Designs and Bias Study / memorize this Observation Study: is a study wherein the researcher passively observes individuals or objects and measures / records some characteristic
Observational Study Designs. Review. Today. Measures of disease occurrence. Cohort Studies
Observational Study Designs Denise Boudreau, PhD Center for Health Studies Group Health Cooperative Today Review cohort studies Case-control studies Design Identifying cases and controls Measuring exposure
Chapter 13. Experiments and Observational Studies. Copyright 2012, 2008, 2005 Pearson Education, Inc.
Chapter 13 Experiments and Observational Studies Copyright 2012, 2008, 2005 Pearson Education, Inc. Observational Studies In an observational study, researchers don t assign choices; they simply observe
3.2A Least-Squares Regression
3.2A Least-Squares Regression Linear (straight-line) relationships between two quantitative variables are pretty common and easy to understand. Our instinct when looking at a scatterplot of data is to
Theory. = an explanation using an integrated set of principles that organizes observations and predicts behaviors or events.
Definition Slides Hindsight Bias = the tendency to believe, after learning an outcome, that one would have foreseen it. Also known as the I knew it all along phenomenon. Critical Thinking = thinking that
Chapter 5: Producing Data Review Sheet
Review Sheet 1. In order to assess the effects of exercise on reducing cholesterol, a researcher sampled 50 people from a local gym who exercised regularly and 50 people from the surrounding community
STA 291 Lecture 4 Jan 26, 2010
STA 291 Lecture 4 Jan 26, 2010 Methods of Collecting Data Survey Experiment STA 291 - Lecture 4 1 Review: Methods of Collecting Data Observational Study vs. Experiment An observational study (survey) passively
Multiple Regression Analysis
Multiple Regression Analysis Basic Concept: Extend the simple regression model to include additional explanatory variables: Y = β 0 + β1x1 + β2x2 +... + βp-1xp + ε p = (number of independent variables
Epidemiologic Methods I & II Epidem 201AB Winter & Spring 2002
DETAILED COURSE OUTLINE Epidemiologic Methods I & II Epidem 201AB Winter & Spring 2002 Hal Morgenstern, Ph.D. Department of Epidemiology UCLA School of Public Health Page 1 I. THE NATURE OF EPIDEMIOLOGIC
Methodological skills
Methodological skills rma linguistics, week 3 Tamás Biró ACLC University of Amsterdam t.s.biro@uva.nl Tamás Biró, UvA 1 Topics today Parameter of the population. Statistic of the sample. Re: descriptive
Conducting Research. Research Methods Chapter 1. Descriptive Research Methods. Conducting Research. Case Study
Research Methods Chapter 1 Conducting Research Goals of Psychology Describe Explain Predict Control Pitfalls of intuition and common sense explanations: Hindsight bias, overconfidence Remember psychology
Multi-Stage Stratified Sampling for the Design of Large Scale Biometric Systems
Multi-Stage Stratified Sampling for the Design of Large Scale Biometric Systems Jad Ramadan, Mark Culp, Ken Ryan, Bojan Cukic West Virginia University 1 Problem How to create a set of biometric samples
Design, Sampling, and Probability
STAT 269 Design, Sampling, and Probability Three ways to classify data Quantitative vs. Qualitative Quantitative Data: data that represents counts or measurements, answers the questions how much? or how
Strategies for data analysis: I. Observational studies
Strategies for data analysis: I. Observational studies Gilda Piaggio UNDP/UNFPA/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction World Health Organization
Chapter 1: Review of Basic Concepts
Chapter 1: Review of Basic Concepts Multiple Choice 1. A researcher uses a six-sided dice to determine group membership. The sampling method being used is: a. random sample. b. stratified sample. c. convenience
Intervention vs. Observational Trials:
Intervention vs. Observational Trials: A Brief Introduction Introduction Just like an architect translates a vision for a building into blueprints, so an investigator translates their research idea into
Statistical analysis of comparative data on composition and agronomic characteristics: new software tool and recurring issues identified
Statistical analysis of comparative data on composition and agronomic characteristics: new software tool and recurring issues identified C. Paoletti*, J. Perry and H. Broll* * EFSA GMO Unit; EFSA GMO Panel
Chapter 1 Thinking Critically with Psychological Science
Myers PSYCHOLOGY (7th Ed) Chapter 1 Thinking Critically with James A. McCubbin, PhD Clemson University Worth Publishers The Need for Psychologists, like all scientists, use the scientific method to construct
Chapter 5 Review. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.
Class: Date: Chapter 5 Review Multiple Choice Identify the choice that best completes the statement or answers the question. 1. The Women s Health Study randomly assigned nearly 40,000 women over the age
YSU Students. STATS 3743 Dr. Huang-Hwa Andy Chang Term Project 2 May 2002
YSU Students STATS 3743 Dr. Huang-Hwa Andy Chang Term Project May 00 Anthony Koulianos, Chemical Engineer Kyle Unger, Chemical Engineer Vasilia Vamvakis, Chemical Engineer I. Executive Summary It is common
The degree to which a measure is free from error. (See page 65) Accuracy
Accuracy The degree to which a measure is free from error. (See page 65) Case studies A descriptive research method that involves the intensive examination of unusual people or organizations. (See page
The Impact of Melamine Spiking on the Gel Strength and Viscosity of Gelatin
The Impact of Melamine Spiking on the and of atin Introduction The primary purpose of this research was to assess the impact of melamine spiking on the gel strength and viscosity of gelatin. A secondary
Thursday, April 25, 13. Intervention Studies
Intervention Studies Outline Introduction Advantages and disadvantages Avoidance of bias Parallel group studies Cross-over studies 2 Introduction Intervention study, or clinical trial, is an experiment
Data = collections of observations, measurements, gender, survey responses etc. Sample = collection of some members (a subset) of the population
Chapter 1: Basic Ideas 1.1 Sampling Statistics = the Science of Data By collecting a limited amount of data, we want to say something about the whole group that we want to study, i.e. we want to say something
Sample Exam Questions Psychology 3201 Exam 1
Scientific Method Scientific Researcher Scientific Practitioner Authority External Explanations (Metaphysical Systems) Unreliable Senses Determinism Lawfulness Discoverability Empiricism Control Objectivity
Mathacle. PSet Stats, Concepts In Statistics Level Number Name: Date:
II. DESIGN OF STUDIES Observational studies and experiments are two types of studies that aim to describe or explain the variation of responses under the hypothesized factors, without or with manipulation.
Psych 1Chapter 2 Overview
Psych 1Chapter 2 Overview After studying this chapter, you should be able to answer the following questions: 1) What are five characteristics of an ideal scientist? 2) What are the defining elements of
PTHP 7101 Research 1 Chapter Assignments
PTHP 7101 Research 1 Chapter Assignments INSTRUCTIONS: Go over the questions/pointers pertaining to the chapters and turn in a hard copy of your answers at the beginning of class (on the day that it is
BIOSTATISTICAL METHODS
BIOSTATISTICAL METHODS FOR TRANSLATIONAL & CLINICAL RESEARCH PROPENSITY SCORE Confounding Definition: A situation in which the effect or association between an exposure (a predictor or risk factor) and
Review and Wrap-up! ESP 178 Applied Research Methods Calvin Thigpen 3/14/17 Adapted from presentation by Prof. Susan Handy
Review and Wrap-up! ESP 178 Applied Research Methods Calvin Thigpen 3/14/17 Adapted from presentation by Prof. Susan Handy Final Proposals Read instructions carefully! Check Canvas for our comments on