chapter 8/9 Gauss/ Applied/ learning

Question 1

Quetelet/ The Gaussian Distribution

Answer 1

Depicted the errors obtained from multiple measurements; measuring errors.
- m = average, but also the most frequent score
“true value”
- he saw the curve and was like their is something systamic in the curve.
instruments & observers
- all traits in a population were distributed in the gaussian distribution.
- same curve kept coming up
- talked about average score as a true value, idealized type
- the deviation were accidental causes; error.
- accidental variation; random
- constant; act the same way in every measure, continuous
- variable; chnge over time, continuous/ continual forces
- Population = a group of individuals who share a common trait
The larger the population, the smaller the variation

Question 2

variation

Answer 2

**Ven (Ven diagram) (infleunced by darwin) **
- (human) difference is not an error; the differences are common
- variation is normative.
- we’re all different/ there is not real error, its human differences such as variation.
**- Gauss (Natural State Model) **
- law of errors; measurements may include errors that create variation
- any variation was a mistake,because if there is a true value then the statistical noise; interferring forces, he said it was a mistake of measurement.
**- Galton **
- lawful properties of bvariation can lead to an understanding about change
- variation is meaningful
- variation is not an error; it can tell us a lot about change/ differences.
- regression toward the mean; extreme scores graviate back towards the average number,
- extreme score have some measure of variance
- Occurs as a result of aggregating variance from multiple sources
There is a systematic proportion in which the extreme scores will regress
Accidental factors “cancel each other out”
Problem: RTTM should make a more narrow distribution
Accidental factors cancel out RTTM

Question 3

Eugenics

Answer 3

RTTM posed a “social problem”; desirable traits would occur only by chance!
-only wanted to breed desirable people/ tall, rich, smart people, so people were encouraged to breed wth other smart people.
- galton; RTTM; social problem
- RTTM should occur but there are all these accidental forces – these accidental forces were all variation and mistakes, and these mistakes were constantly changing what that average true value was, so if we just let it happen, then all of our desirable traits would happen accidentally.
- 1. evolution occurred by discontinuos steps, not incremental steps– evolution leaps forward in one bound.
- 2. reversion displaces accidental but not constant variation
- using a scatter could still result in separate sub-populations
- selective breeding is required.
- reversion would get rid of all the accidental stuff but not the constant variation i.e., you can’t actually select for a certain trait during process of reversion.

Question 4

eugenics; galton; mental capacity

Answer 4

what traits should we be selecting for? mental capacity; mental capacity was related to neural efficiency
- breed only smart people, no one else.
- neural efficiency; can tell if someone is smart by checkingt their neural activity.
- smart people; can lift heavier things; so only for men and well nourished people (rich)

Question 5

relate between gauss, galton & Quetelet; their ideas about stat noise & true value.. how did this relate back to aristotles hylpmorphism

Answer 5

hylomorphism; accidental change aristotle, similar to galtons - accidental change will regress the mean in the longterm.
- final goal; aristotle, intent behind changes, galtons believe evolution happens for a reason, survival of the fittest.
- substansive change; development (aristotle)
- Galton; the true value represented the highest, best value and everything else represented statistical noise.
- galton; had some idea that error was not meaningul
- quetelet; some error was not meaningful.

Question 6

Alfred Binet; Learning Potential

Answer 6

Complex higher mental processes were different from low-level sensorimotor abilities
- “adapting, judging, understanding and reason.”
- functional measures to test for differences
- Caveats
1) Intelligence was multifaceted; forced to reduce to one score
2) mental levels could increase with training
3) Test was only appropriate for determining weak students
- i.e. not generalizable!!
Aptitude Test: the probability of achievement given a specific operationalized goal; competency.
- predict performance based on their age, if they’re above the average, then bump them up to a higher grade.
❑Predictive

Question 7

learning potential; binet-simon scales

Answer 7

❖Binet-Simon Scales; Standardized- administered and scored in a consistent manner
- Normed; Estimates (reflects) the population with respect to the ability
Helps to eliminate systematic bias inherent in testing goals; baed on content and nothing else, testing knowledge.
- Diagnostic (i.e. predictive); Correlated with impairment/achievement; had to let you know something about outcomes, relate to some functional idea.
- Quantifiable result
Mental age: operationalized by successful completion of diagnostic tasks; measure of psychological ability

Question 8

Lewis Terman: Intelligence

Answer 8

Racially biased;
1. Cross-cultural (American) results yielded differing (non-flattering) results; revised items to reflect culture
Problem: marketed later as universal.
❑Comparative debate
2. Institutionalizing measures; determine a hierarchy
Problem: Generalizability
❑External validity of measures (adults, goal of test)
3. William Stern: relate mental ability to age
4. Changing “mental age” to “intelligence”
– Problem: conceptualizing cognition as a trait

Question 9

WAIS; Wechsler Adult Intelligence Scale

Answer 9

this checks for avergae; not meaning you’re a genious, you’re normal.
use this to measure average.
Compares cognitive performance with typically developing (TD) norms
1. Clinical tool looking at impairment
Looks at the average
means to test for the disorder
Intelligence doesn’t refer to smart, refers to the cognitive aptitude
Clinical tool used for diagnostics
Measure of impairment
❑“intelligence” means “cognitive,” not “smart”!
2. Point-scale
Sensitive to individual differences in task performance
Pass-fail- all or none
Underscore or overscore the test
0-3 have no distinct meaning
Just because you pass doesn’t mean you really pass
❑ compiling sub-tasks allows for a more accurate representation
❑More informative than “pass/fail.”
3. Non-verbal performance
Overcome cultural, linguistic, and education biases
❑Tapped into higher-order cognitive abilities such as attention, problem-solving, etc