Chapter 2 Methods of Psychology Flashcards
Bias
&
Random variation
👽BIAS
(= nonrandom effect caused by factor/s extraneous to research hypothesis)
- > researchers might think that hypothesis is supported but
- > factor/s irrelevant to hypothesis (BIAS) cause observed results
SERIOUS PROBLEM
-> statistical techniques cannot identify/correct it
-> NOT correctable by averaging
⚡-> results are ✔️NOT statistically significant
👽Random variation / error
-> average can correct it
⚡-> the higher variability of data the less likely results are to be statistically significant
But they ✅😊ARE statistically significant (oppsed to when results are biased)
- > RANDOMLY ASSIGN PEOPLE
- differences only due to error/random variation
Biased sample
Biased sample NOT representative of larger population
-> can’t draw general conclusions from the sample for the population
PROBLEM
-human subjects that are easily available to be studied (like psychology students) may not be representative of population
Reliability
of measurement procedure
If we do the same study with the same measurement procedure again, how likely are we to get the same results?
How reliable is our measurement (procedure)?
🔥⚡LOW RELIABILITY =
SOURCE OF ERROR / RANDOM VARIABILITY
F. Ex. Measurement procedure: psychological test
- > greatly affected by mood of subjects
- > observed results subject to random variation (because of random variation in mood)
Interobserver / interrater reliability
Is the same behaviour seen by one observer also seen by other?
Need to carefully define which behaviour we wanna observe
Operational definition
Specifying exactly what observable behaviour (which we measure) should look like
(-> so we can observe it and know if we’re observing the behaviour we wanna observe)
F. Ex. Operational definition of aggression
- Child hits others
- questionnaire to measure aggression
Validity
Are we measuring what we want to measure?
-> is our measurement (procedure) valid?
(-> then it has “face validity”
F. Ex. Test that assesses degree of shyness (measurement procedure) has face validity for measure of personality)
⚡🔥LACK OF VALIDITY = SOURCE OF BIAS
F. Ex. Biased group: people who are motivated to better their depression are all in one group
-> now we’re not measuring what we want to
- > we’re not measuring if people with depression respond well to psychotherapy in general
- > we’re measuring if people who are motivated to better their depression respond well to psychotherapy
- > we’re not testing if Hypothesis is true
Measurement procedure
Can be RELIABLE (same results when study reproduced)
But NOT VALID (measuring sth else than we want to)
Within-Subject Experiment
Each subject each tested in each condition of independent variable
(subjects repeatedly tested)
OR
just 1 subject tested under varying conditions of independent variable
F. Ex. Clever Hans
Between-Groups Experiment
Different groups tested under varying conditions of independent variable /
Manipulations of independent variable applied to different groups of subjects
observer-expectancy effects
=> Biases
Observer has certain wishes/expectations that affect how they behave and what they observe
F. Ex. Clever Hans
Researcher wants/expects horse to respond in particular way and unintentionally communicates this expectation & influences subjects behaviour
blind observer
How does blind observer prevent 2 biases of observer-expectancy effect?
observer blind (uninformed) about aspects of study that could lead him/her to form biasing expectations
F. Ex.
Observer doesn’t know which group gets treatment
-> Doesn’t have expectations regarding the behaviour of the groups
1.
-> no confirmation bias (f. Ex. expects them to smile more, interprets more facial expressions as smiling)
2.
-> doesn’t influence their behaviour through behaving differently with each group
Subject-expectancy effect
=bias
Expectation of subject leads to effect and not treatment itself
F. Ex. Believe that psychotherapy treatment will work -> improve because of that (placebo)
Placebo effect = Subject-expectancy effect
Hawthorne effect
Workers got more productive because they believed they were receiving special treatment (& bc they knew they were being watched)
Double-blind experiment
Subjects and observers blind to / uninformed about treatment
To prevent BIASES
F. Ex.
Some subjects receive drug, some placebo (inactive substance that looks like drug)
- double-blind experiment - NO BIASES
- all subjects take sth - all subjects have PLACEBO EFFECT (belief that it will work causes it to work) /Hawthorne effect
=> any observed difference between subjects who did and didn’t get the drug due to drug’s chemical qualities
Theory
idea / conceptual model / explanation
explains existing observations
makes predictions about new observations (hypothesis)
Observation -> Theory -> Hypothesis
Hypothesis
Prediction about new observations made from a theory
Then: testable prediction
F. Ex.
Theory: Horses have humanlike intelligence
Hypothesis: Hans can give correct answers to verbally stated problems/questions
Variable
Anything that can change / assume different values
(Anything that’s observed in a study)
F. Ex. Temperature, amount of noise, score on test, eye colour
