PSYCH 100A Lecture Notes - Lecture 1: Gambling, Toothpaste, Conditional Probability
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Inductive statements: statement whose truth is assessed by observing a series of examples, ex. ) Population = complete set of things we are interested in (any size) Sample = subset of population: data fluctuations, probability, p(e) = # successful outcomes/# total possible outcomes, conditional probability, given x what is the likelihood of y happening, ex. ) 13/26: gambler"s fallacy, mistaken notion that the probability of a particular event changes with a long string of same event, ex. ) Reaction time in stroop task: time to say colors compared to time to say word, we have a hard time inhibiting our reading of the world creates cognitive competition, measurement scales, nominal: category or name (ex. Interval & ratio: numbers are equally spaced: ratio examples = height or depression level. Interval examples = temperature: classification of variables, discrete = variable that can only take on a specific value, ex. ) whole numbers, how many letters are in ur name, ex. )
