Chapter 3 Lecture Flashcards
Indigenous Ways of Knowing
- There is an overlap between western european science
- Experential & holistic (how do things connect)
- Stories get passed on
- Relations & Context (why?)
- Multiple correct answers (always acknowledge different views & nothing is right)
- Similar measurements
3 Claims
- Frequency
- Association
- Causal
Frequency Claim
- One Variable measured
- Descriptive Study
- Percentage/ numbers/ amount
- Not relational
Association Claim
- Two Measured Variables
- Correlational Study
- Looking at a link between two things
Causal Claim
- Two Variables (1 manipulated (causal) and 1 measured (outcome))
- Experimental study
- Causal variable causes outcome variable
- Need 2 levels for variable otherwise it is a constant
4 Big Validities
- Construct
- Statistical
- External
- Internal
Construct Validity
How well does/do the variable(s) predict what we are interested in? How well were they measured/manipulated?
Statistical
- Does the data support the conclusions?
- Strength
- Statistical Significance
- Amount of error
External Validity
Do the results generalize to some larger populations, and to other times or situations?
Internal Validity
Can we say that variable A, rather than some other variable (such as C), is responsible for the effect on B? (no third variable)
3 Rules for Causation
- Covariance
- Temporal Precedence
- Internal Validity
Covariance
Both variables must be associated/covary; alterations with variable A must change variable B
Temporal Precedence
- A comes before B
- In an experiment, manipulating the causal variable ensures that it comes first
Internal Validity
- No 3rd (outside) variable, A 100% caused B
- In an experiment, manipulating a variable controls for alternative explanations
Random Sampling
- Random population sample
- Drawing a sample using some random method
- Ensures members have an equal chance of being in the sample
- External validity
- Representative of population outside of study
Random assignment
- Using of a random method to assign participants into different groups
- Ensures groups have the same kinds of people in them
- Internal validity (any differences are due to chance)
- Randomly assigning people to different random conditions/groups
Frequency Claim and Validities
- Construct
- External
- Statistical
- Population studied must be representative of similar population outside
Association Claim and Validities
- Construct
- External
- Statistical (Strong/ Satistical Significant Relation)
Causal Claim and Validities
- Causal
- External
- Statistical
- Internal (no other outcomes)
