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| Four principles of science |
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| Determinism, empiricism, parsimony, testability |
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| Events have logical causes |
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| Observation is the key to learning |
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| When there are competing explanations, the simplest is better, i.e. Occam's Razor |
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| How well can a hypothesis be tested? How well can it be falsified? |
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| Popper's idea that knowledge must be based on what we can observe with complete certainty. Empirical. |
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| What are the three purposes of studies/types of studies? |
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Describe -> Descriptive studies
Predict -> Correlational studies
Explain relationship -> Experimental study |
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| The general idea/construct of interest in a study |
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| The specific variable that measures a conceptual variable. Hopefully, if there are multiple, they converge. |
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| Describe the uses of et al. |
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Definition
1-2 authors: Don't use it
3-5 authors: Don't use it the first time, use it after that
6 or more authors: use it every time except for the references section |
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| Intuition (pros and cons) |
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Definition
Def: a gut feeling
Pros: easy to figure out
Cons: often wrong |
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Def: reason.
Pro: calculable, provable
Cons: Assumptions change over time. |
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Def: relying on the wisdom of experts
Pro: Experts can have some good stuff to say
Cons: Do we pick good experts? How do they get their info? We tend to follow them blindly |
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Def: knowledge through empirical tests
Pro: Repeatable, less subject to bias
Con: Some questions are difficult to test |
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Definition
Universal statements about the nature of something.
Not really used in psychology |
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| A statement about the relationship between variables. Like a law but with boundary conditions |
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| A specific prediction derived from a theory. A testable example of a theory. |
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Drawing general conclusions from specific observations.
Ex: I've seen ten guys named Tom eat a lot of pickles. Therefore, everyone named Tom eats hella pickles.
Specific->General |
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Going from a general law to a specific prediction.
Ex:
Tom has an iron deficiency.
The only way to live with an iron deficiency is to eat a pickle every hour.
Tom is alive.
Therefore Tom eats a pickle every hour |
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| The hypothesis that states that there is no relationship between the variables/groups in question |
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| The prediction that your theory states is supported |
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The probability that the findings result from random error, i.e. the probability that the null hypothesis is right.
Considers strength of relationship and # of participants |
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| The standard p-value at which one rejects the null hypothesis (usually .05, sometimes .01) |
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| Incorrectly rejecting the null hypothesis. Aka incorrectly confirming a hypothesis |
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| Failing to reject an incorrect null hypothesis. I.e. incorrectly denying your hypothesis |
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| How big is the effect? It's not related to statistical reliability, but it's practically important. |
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Describes the nature of a variable/condition.
Used in the beginning stages of research. There is no hypothesis. |
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| A type of descriptive research. Observing the experiences of a particular person or group, usually for interesting and rare phenomena. Good for grounding hypotheses but too small of a group to be reliable itself. |
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| Using a group of participants to reach a conclusion about a population. E.g. the census |
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| A descriptive study in which everyone in a population has an equal chance of being selected |
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| A descriptive study in which the are multiple groups of people meant to represent a population and people are randomly selected from those groups. |
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| A descriptive study in which participants are randomly sampled from a specific group. |
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| A descriptive study in which the participants are selected for convenience |
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| When a sample doesn't reflect a population |
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| If someone thinks that they can tell when you're telling the truth, they will tell the truth now. |
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| A measurement in a correlational study that says the strength and direction of a relationship. It's -1 to 1. |
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| For any two variables, there are at least three causal possibilities. What are they? |
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Definition
X causes Y
Y causes X
Z causes both X and Y |
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| A third variable that effects a correlational study |
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Personal confound
Environmental confound
Operational confound |
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| Something about a person's personality is a third variable |
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| Something in the setting is the third variable |
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| Your operational definition doesn't measure the concept you are trying to measure. |
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Def: Getting data from records
Pros: Can't be influenced, has external validity
Cons: limited data you can collect, not collected by scientists |
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| Two correlational caveats |
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Definition
Linearity: there aren't always linear relationships between variables (e.g. Yerkes Dodson)
Restriction of Ranger: responses might not cover the full range of a variable.
Eg: if you're doing a test on whether # of Dums Dums eaten per year correlates with suicide attempts, you might not have someone who's never had a Dum Dum or attempted suicide twenty times. |
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Definition
| Does a variable measure what it is supposed to? |
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| Are the results consistent? |
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| Does the variable measure the construct of interest? No operational confounds? |
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Definition
| Does the variable measure the construct of interest? No operational confounds? |
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| Does the variable measure the construct of interest? No operational confounds? |
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| Four types of construct validity |
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Definition
Face validity
Content validity
Convergent validity
Discriminant validity |
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| Does a variable seem to measure what we want it to? |
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| Does a variable cover the entire range of the construct? |
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| Does the variable correlate with other variables measuring the same construct? |
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| Is the variable unrelated to other variables measuring similar constructs? |
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The extent to which a study tells us about causality.
For experiments only |
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| How generalizable is a study? Across participants, situations, and stimuli? |
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| A measure of internal reliability |
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| Consistency across judges/coders |
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| Consistency across time on the same measure |
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| Equivalent-form reliability |
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| Does the subject do the same on an equal test? |
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| Four types of reliability |
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Definition
Internal reliability
Interrater reliability
Test-Retest reliability
Equivalent-fore reliability |
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Definition
| Chance fluctuations in measurement. They cancel out over time. They're a small threat to validity but a bigger threat to reliability |
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| Nonrandom fluctuations in measurement. They don't effect reliability but they are a major threat to validity |
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| Nominal, ordinal, interval, ratio |
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Categorical data in which number assignments are arbitrary.
Ex: gender, species of plant |
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The order is meaningful but the exact values aren't/
Ex: class year, army ranks |
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Tells about the order but there is no absolute zero
Ex: SAT, IQ |
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Ordered, standardized differences. There is an absolute zero.
Ex: length, money, age. |
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| How much do you agree with the following? |
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