Chapter 4 & 5 Flashcards
Central tendency
descriptive statistic that best represents the center of a dataset, which is the “typical” score or value that the rest of the data is clustered around
Statistics
numbers based on samples taken from a population
Parameters
numbers based on whole populations
Unimodal
when a distribution of scores has one mode
Bimodal
when a distribution of scores has two modes
Multimodal
when a distribution has more than two modes
Variability
numerical way of describing how much spread there is in a distribution
Variance
average of squared deviations from the mean
Deviation
amount that a score in a sample differs from the mean of a sample
Sum of squares
sum of each score’s squared deviation from the mean
Standard deviation
square root of the variance; typical amount that each score varies from the mean
Random sample
every member of the population has an equal chance of being selected into the study
Convenience sampling
uses participants who are readily available
Generalizability or external validity
researcher’s ability to apply findings from one sample or in one context to other samples or contexts
Replication
duplication of scientific results, ideally in a different context or with sample that has different characteristics (aka reproducibility)
Volunteer or self-selected sample
convenience sample in which participants actively choose to participate in a study
Crowdsourcing
when a research team solicits input from a very large group of people, usually online
Constraints on generality (COG) statement
a statement of the target population to which the study results should generalize which should be included in papers
Confirmation bias
unintentional tendency to pay attention to evidence that confirms our beliefs rather than those that disconfirm
Illusory correlation
phenomenon of believing one sees an association between variables when it doesn’t exist
Personal or subjective probability
a person’s own judgement about the likelihood that an event will occur
Expected relative-frequency probability
likelihood of an event occuring based on the actual outcome of many, many trials; only works in the long-run
Outcome
result of a trial
Success
outcome for which we’re trying to determine the probability
Probability vs. proportion
probability is what we would expect in the long-run while proportions are what we observe
Control group
level of IV that does not receive the treatment of interest in the study
Experimental group
level of IV that receives treatment or intervention of interest
Type 1 error
when we reject the null hypothesis but it is correct
Type 2 error
when we fail to reject the null hypothesis but it is false
