D OES SCHOOL MAKE YOU SMARTER ? Stuart Ritchie Tim Bates Differential Club 03/02/12.

Slides:

Advertisements

Similar presentations

IQ: Refuting Popular Myths Michael Hoerger. Introduction Intelligence (IQ): ones overall cognitive ability, including knowledge, memory, mental quickness,

Advertisements

Aging and Intelligence

Comparing Two Means: One-sample & Paired-sample t-tests Lesson 12.

Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 ~ Curve Fitting ~ Least Squares Regression Chapter.

Class 4: Tues., Sept. 21 External/Internal Reliability Clarification Regression Analysis Examples: –Appropriate Dating Ages –Father’s and son’s heights.

Chapter 9: Intelligence and Psychological Testing

Unit 1: Science of Psychology

Scottish Mental Survey 1932 Deary et al. (2004) Journal of Personality and Social Psychology, 86,

Streissguth et al.(1994) Seattle Longitudinal study started in 1974 to examined long term effects of PAE At this point there was little evidence that alcohol.

3.2 Sampling Design. Sample vs. Population Recall our discussion about sample vs. population. The entire group of individuals that we are interested in.

Development of Empirical Models From Process Data

Standard Deviation A measure of variability

Data Mining: A Closer Look Chapter Data Mining Strategies (p35) Moh!

AP Psychology Unit 11: Testing and Individual Differences © 2010 by Worth Publishers David G. Myers.

Data observation and Descriptive Statistics

Cognitive Psychology, 2 nd Ed. Chapter 15 Intelligence.

Stanford-Binet IV Description: –Point-scale (contrast with age-scale of previous editions) –Test composite (M=100, SD=16) –4 areas & scores (M=100, SD=16)

Data Collection Mean, Mode, Median, & Range Standard Deviation

Mary Ganguli’s Slides March 13 th Meeting. Mild Cognitive Impairment A View from the Trenches.

Coupled change in brain white matter integrity and fluid intelligence in later life Stuart J. Ritchie Centre for Cognitive Ageing and Cognitive Epidemiology.

Chapter 9 Quiz Intelligence.

Introductory Statistical Concepts. Disclaimer – I am not an expert SAS programmer. – Nothing that I say is confirmed or denied by Texas A&M University.

Wechsler Adult Intelligence Scales

PSYCHOMETRICIANS: develop tests -try to make constructs measurable and quantifiable -purpose is to differentiate between test- takers 3 Qualities of Tests:

Stimulus Control of Operant Behavior Discrimination Generalization Generalization Gradients Peak Shift Concepts Overview of stimulus control of operant.

Unit 6: Testing & Individual Differences

 Problems of ________ structure  Series completion and analogy problems  Problems of ____________  String problem and Anagrams  Often solved through.

The Charter Oak Group, LLC1 Challenges To Managing To Wage- Record Based Outcomes Time lag –To find out that an outcome actually occurred, you have to.

Chapter 9: Intelligence and Psychological Testing

1 rules of engagement no computer or no power → no lesson no SPSS → no lesson no homework done → no lesson GE 5 Tutorial 5.

2-6 Measures of Spread. Remember from yesterday, the mean, median, and mode are valuable to us in a couple of ways 1 They help us get a sense for the.

Defining Success Understanding Statistical Vocabulary.

Lecture 8 Simple Linear Regression (cont.). Section Objectives: Statistical model for linear regression Data for simple linear regression Estimation.

Chapter 9 Intelligence and Psychological Testing.

Chapter 9 Intelligence and Psychological Testing.

BPS - 3rd Ed. Chapter 131 Confidence Intervals: The Basics.

Intelligence & Testing

Relative Values. Statistical Terms n Mean:  the average of the data  sensitive to outlying data n Median:  the middle of the data  not sensitive to.

Intelligence CHAPTER 16 LESSONS 16.1 Measuring Intelligence

Intelligence and Psychological Testing

Tables & Graphs Outline 1. Tables as representations of data 2. Graphs *Definition *Components 3. Types of graph *Bar *Line *Frequency distribution *Scattergram.

28. Multiple regression The Practice of Statistics in the Life Sciences Second Edition.

Outline 1. Tables as representations of data 2. Graphs * Definition * Components 3. Types of graph * Bar * Line * Frequency distribution * Scattergram.

Assessing Intelligence

Multivariate Analysis and Data Reduction. Multivariate Analysis Multivariate analysis tries to find patterns and relationships among multiple dependent.

Direct Variation We say that two positive quantities x and y vary directly if an increase in one causes a proportional increase in the other. In this case,

Chapter 9 Intelligence & Psychological Testing. Principle Types of Tests Standardized measure of a sample of a persons behavior Represent a sample of.

Intelligence Christine Bui Bennet Engelhardt Jai Dahyabhai.

Forecasting Demand. Forecasting Methods Qualitative – Judgmental, Executive Opinion - Internal Opinions - Delphi Method - Surveys Quantitative - Causal,

Chapter 9: Intelligence Slides prepared by Randall E. Osborne, Texas State University-San Marcos, adapted by Dr Mark Forshaw, Staffordshire University,

How to investigate Perception & Cognition n Ask your subjects (Introspectionism) n Look at S-R patterns (Behaviorism) n Infer mental processes (Cognitive.

Dominion Training Survey BADM 621 October 19,2005 Shawn Miller Kylee Fink Soumya Prasad Thomas O’Neill Casey Brown.

Forecasting Demand. Problems with Forecasts Forecasts are Usually Wrong. Every Forecast Should Include an Estimate of Error. Forecasts are More Accurate.

The accuracy of averages We learned how to make inference from the sample to the population: Counting the percentages. Here we begin to learn how to make.

TOPIC - Page 1 Representativity Indicators for Survey Quality R-indicators and fieldwork monitoring Koen Beullens & Geert Loosveldt K.U.Leuven.

VALIDITY What is validity? What are the types of validity? How do you assess validity? How do you improve validity?

Test construction and assessment

Exploring Group Differences

Statistical Inference

Testing an Individual Differences

History: defining & measuring intelligence

Regression Computer Print Out

Width vs. Area for Sample Squares

Reaction time زمن الرجع.

Homework 4a: Trend Forecasting and Future Uncertainties

Which Test Should I Use?.

History: defining & measuring intelligence

Presentation transcript:

D OES SCHOOL MAKE YOU SMARTER ? Stuart Ritchie Tim Bates Differential Club 03/02/12

W HAT CAN WE DO TO RAISE IQ? Jensen (1969): Gloomy about reducing gaps… Ceci (1991): Review – school works. Herrnstein & Murray (1994) NLSY indicates minor effects: ~1 IQ point/year. Winship & Korenman (1997) NLSY reanalysis: ~2.5 pts/year Other studies similarly-sized: Cascio & Lewis, 2006; Falch & Massih, 2011; Hansen, Heckman, & Mullen, 2004 Renewed interest in trainability of g itself E.g. Improving fluid intelligence with training on working memory (e.g. Jaeggi, Buschkeuhl, Jonides, & Perrig, 2008) But see Moody, 2009; Shipstead, Redick, & Engle, 2010.

B RINCH & G ALLOWAY (2012), PNAS Norway – compulsory education reform - increases by 2 years But not in all municipalities Education reform leads to increase in average IQ of.6 points Measured by IQ test on entry to armed forces at age 19 Modeled using Instrumental Variables/2-Stage Least Squares analysis – this increase translates to an increase of 3.69 IQ points per year Similar to previous studies, but with a better design But what is being tested here? Arithmetic, word similarities, figures

IQ CHANGE WITH E DUCATION C HANGE

N ETTELBECK & W ILSON (2004), I NTELLIGENCE ‘The Flynn effect: Smarter not faster’ 2 samples of schoolchildren, separated by 20 years, both tested on vocab and inspection time As expected, Flynn effect occurs on VIQ (sig. increase)… …but not on IT (no sig. difference). So secular IQ gains – due to unknown causes – are not speed gains But what about IQ gains due to known causes (education)?

L OTHIAN B IRTH C OHORT 1921: LBC21 Scottish Mental Survey, 1932 IQ = Moray House Test (MHT) 87,498 tested Those in Edinburgh area followed up , , … Age 79 MHT; Asked about Education ( n = 550) At age 83 Reaction Time & Inspection Time ( n = 341) Jensen Box - RT IT stimulus

C ORRELATION MATRIX IQ11IQ79Edu Simple RT Simple RT SD 4-Choice RT 4-Choice RT SD IQ79.66*** Edu.44***.42*** Simple RT-.16**-.26***-.10 Simple RT SD-.16**-.29*** *** 4-Choice RT-.14*-.29***-.14*.53***.40*** 4-Choice RT SD-.13*-.28*** ***.37***.60*** IT.18**.30*** ***-.30***-.33*** Note: Edu = years of education; * = p <.05; ** = p <.01; *** = p <.001. Residualized variables, controlling for sex and age in days at time of testing/report

R ESULTS : EDUCATION DOES NOT IMPROVE S PEED Education predicts late-life IQ, controlling for early IQ lm(IQ79 ~ Education + IQ11 + Sex) F (1,479) = 10.65, p = year education =.78 IQ points (95% CI = ) Education effect on RT? lm(simpleRT ~ Education + IQ11 + Sex) F (1,286) =.03, p =.86 Effect of education on CRT? lm(choiceRT ~ Education + IQ11 + Sex) F (1,286) = 1.15, p =.28 Effect of education on IT? lm(IT ~ Education + IQ11 + Sex) No education effect, F (1,284) =.0004, p =.98

D ISCUSSION So does education make you smarter? Yes... in an IQ-score sense Q: Why the smaller IQ gains in our sample? Training vs. processing speed ‘transfer’ seems not to have occurred Limits “School” before age 11 may improve speed Or may not Replication in other samples?