PSYC209 Lecture Notes - Lecture 5: Standard Deviation, Random Variable, Statistical Inference
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=(cid:3033)(cid:3045)(cid:3032)(cid:3044)(cid:3048)(cid:3032)(cid:3041)(cid:3030)(cid:3052) (cid:3042)(cid:3033) (cid:3047)(cid:3040)(cid:3032)(cid:3046) (cid:3028)(cid:3041) (cid:3042)(cid:3048)(cid:3047)(cid:3030)(cid:3042)(cid:3040)(cid:3032) (cid:3042)(cid:3030)(cid:3030)(cid:3048)(cid:3045)(cid:3046) (cid:3047) (cid:3032) (cid:3047)(cid:3042)(cid:3047)(cid:3028)(cid:3039) (cid:3041)(cid:3048)(cid:3040)(cid:3029)(cid:3032)(cid:3045) (cid:3042)(cid:3033) (cid:3043)(cid:3042)(cid:3046)(cid:3046)(cid:3029)(cid:3039)(cid:3032) (cid:3042)(cid:3048)(cid:3047)(cid:3030)(cid:3042)(cid:3040)(cid:3032)(cid:3046) The total number of outcomes is called the sample space. The probability, p, of an outcome, x, is represented as p(x) The frequency, f, of times an outcome, x, occurs is represented as f(x) Used to describe the likelihood that an outcome will occur. Can be used to predict an outcome that is not fixed. Used to identify the likelihood of a random event (an event in which the outcomes. Relationships between samples and populations are defined in terms of probability. Step 1: identifying the types of samples that probably would be obtained from the population (probability) Step 2: use the data collected from the sample to answer about the population (inferential statistics) Each individual in the population has an equal chance of being selected. Probabilities must stay constant from one selection to the next if more than one individual is selected.