# PSY571_Ch3-4_Glossary

 .remove_background_ad { border: 1px solid #555555; padding: .75em; margin: .75em; background-color: #e7e7e7; } .rmbg_image { max-height: 80px; } Central Tendency a typical or representative score value Mean the numerical average. Obtained by summing all of the measurements in the distribution and dividing by the number of measurements in the distribution Population Mean µ (∑X)/N Sample Mean M (∑X)/n Population Parameter a quantity computed from the scores in a population. Sample Statistic a quantity computed from the scores in a sample. Unbiased Estimator a quantity which when all possible random samples of the same size are collected from a population and a mean is computed from each of the samples, then the mean of means equals the population parameter being estimated. Median the 50th percentile, the score value that has below it half of the measurements in the distribution and half the measurements above it. Mode the score value (or class interval) with the greatest frequency. Variability the extent to which the measurements in a distribution differ from one another. Range the largest score minus the smallest score. Population Variance the average of the squared deviations of each score from the population mean (µ). The symbol for the population variance is the Greek lowercase letter sigma to the power of two,σ². Sum of Squares (SS) the sum of the squared deviations of each score. SS Sum of Squares Σ(X-μ)² or ΣX² - ((ΣX)²)/N σ² Population Variance (∑(X- μ)²)/N or (∑X²-Nµ²)/N Sample Variance the sum of squared deviations of each score from M divided by n – 1. The symbol of the sample variance is s². s² Sample Variance SS/(n-1) or (∑X²-nM²)/(n-1) Standard Score (z score) a score that has been standardized by subtracting µ and dividing the difference by σ. This score indicates the number of standard deviations the observation is above or below the mean of the distribution. z score formula (X- μ)/σ Raw Score from a zscore formula X= μ+zσ Normal Distribution A unimodal and symmetrical distribution with both tails extending to infinity. Standard Normal Distribution a normal distribution with µ = 0 and σ = 0. .remove_background_ad { border: 1px solid #555555; padding: .75em; margin: .75em; background-color: #e7e7e7; } .rmbg_image { max-height: 80px; } Authordarwinguevarra ID64351 Card SetPSY571_Ch3-4_Glossary DescriptionCh. 2: Central Tendency and Variability Ch. 4: z Scores and Normal Distributions Updated2011-02-22T18:28:21Z Show Answers