PSYC 210 Lecture Notes - Lecture 1: Data Matrix, Statistical Inference
Document Summary
Random variable: a property that can take on different (at least 2) values (in it varies). These values have associated probabilities and we can this talk about their associated probability distributions. Discrete random variables are those that can only take on particular values that are made up of disjointed categories. E. g. , random variables cannot be something like 3. 1. Continuous random variables can take on values along an entire interval of the number line and these values are not disjointed. E. g. random variable y that can take on values between 2 and 5 and everything in between (such as 4. 14) Data: numerical (or sometimes non-numerical) information collected by the researcher - these are usually the observed values on random variables. Data matrix: organizes data in an array of columns/rows with order n x p. N = number of rows of the matrix (usually # of observations) P = number of columns of the matrix (usually # of variables)