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Confirmation Bias
the tendency to look for or notice info that supports what you already believe while ignoring info that disagrees
Hindsight bias-The tendency to believe, after something happens, that you knew it would happen all along
Overconfidence
The tendency to be more confident in your knowledge or abilities than is justified by the evidence
Independent vs. Dependent Variable
IV; The variable that is changed or controlled in an experiment. DV; The variable that is measured to see whether it was affected by the independent variable
Random Assignment
Placing participants into different experimental groups by chance, helping make the groups similar
Case Study
An in-depth investigation of one person, group, or situation
Correlation
A relationship between two variables in which changes in one variable are associated with changes in another; doesn't = causation
Meta
- A study that combines the results of many previous studies to find an overall pattern or conclusion
Naturalistic Observation
Observing and recording behavior in a person's or animal's normal environment without interfering
Hypothesis
A testable prediction about the relationship between variables
Falsifiable Hypothesis
A hypothesis that can be tested and possibly proven false
Operational Definitions
Specific, measurable descriptions of how a researcher will define and measure a variable
Confounding Variables / Third Variable Problem
An outside variable that affects the results and can make it difficult to determine whether one variable actually caused a change in another
Histogram
A graph that shows how numerical data was distributed across intervals or ranges
Scatterplot (Correlational Coefficient)
A graph that uses dots to show the relationship between two numerical variables
Central Tendency
A way of describing the typical or center value of a set of data, usually using the mean, median, or mode
Variation
The amount by which data values differ from one another
Percentile Rank
The percentage of scores that fall at or below a particular score
Range
The difference between the highest and lowest values in data
Population
The entire group of people or subjects that a researcher wants to study
Representative Sample
A smaller group that closely reflects the important characteristics of the population being studied
Random Sample
A sample chosen so that every member of the population has an equal or known chance of being selected
Convenience Sampling
Choosing participants because they are easy for the researcher to reach
Sampling Bias
A problem that occurs when the sample does not accurately represent the population
Generalization
Applying the results of a study to a larger population beyond the participants who were studied
Experimental Group
The group in an experiment that receives the treatment or independent variable being tested
Control Group
The group that does not receive the experimental treatment and is used for comparison
Placebo
An inactive treatment that looks like real treatment and is used as a comparison
Single Blind
A study in which the participants do not know which group they are in, but researchers do
Double Blind
A study in which neither the participants nor the researchers directly interacting with them know who is receiving the treatment
Experimenter Bias
When a researcher's expectation unintentionally influence how a study is conducted or interpreted
Social Desirability Bias
When people give answers they think will make them look better or more socially acceptable
Qualitative (Structured Interviews)
Research that collects non-numerical info, such as people's experiences, opinions, or descriptions
Quantitative Measures (Likert Scales)
Measures that collect numerical data that can be counted or statistically analyzed
Peer Review
When other experts evaluate a research study before it's published
Replication
Repeating a study to see whether similar results can be obtained again
Statistical Significance
A statistical indication that a result is unlikely to have occurred simply because of random chance, based on a chosen significance level
Size of Sample and Statistical Significance
Larger samples generally provide more precise estimates and can make it easier to detect statistically significant effects, although a large sample doesn't automatically make an effect meaningful
Self Report Bias
Errors that occur when people report info about themselves inaccurately, intentionally or unintentionally
Social Desirability Bias
When someone gives an answer they think will make them look better or more socially acceptable