Download Psych Stats Midterm: Descriptive & Inferential Stats, Samples & Populations, Measures and more Exams Psychology in PDF only on Docsity! Psychological Statistics Midterm Descriptive Statistics - Techniques for summarizing the numeric properties of groups Inferential Statistics - The use of estimates to test hypotheses about parameters which cannot be measured directly Sample - Small group to represent the larger group of interest Population - The entire group of interest Estimates - Properties of samples Parameters - Properties of populations Nominal variables - Values are labels with no order (ex: faculty) Ordinal variables - Values are labels with order (ex: letter grades) Interval variables - Values are numbers with an arbitrary zero (ex: temperature) Ratio variables - Values are numbers with a real zero (zero really means zero) (ex: age, height, etc.) Discrete information - limited number of values possible within the range of values Continuous information - all "in between" values are possible (ex: age, height, etc.) Cumulative frequency - sum of frequencies up to and including a given category Central location/Averages - A typical response (mean, median, mode) Variation - Spread of distribution - very spread out or condensed Sometimes around a measure of central location 4 measures of variation: range, mean deviation, variance, standard deviation Zero skew - Symmetric distribution Positive skew - many low values, few high values Negative skew - many high values, few low values Biased estimate - An approximation for a parameter that contains systematic error so that it always over or under-estimates the parameter Standard score - "z" A transformation of a raw score into distance from the mean in units of standard deviation z = (X - mean) / s Causality - The assumption that a change in one variable directly brings about a change in another variable Correlation - "r" An indicator of bivariate linear relationship that gives the direction and strength of the relationship Covariance - An indicator of bivariate relationship that gives the direction of the relationship Coefficient of determination - "r²" Measures the proportion of the variation in one variable that can be accounted for by variation in another variable Dependent variable - The variable that is observed to assess the result of manipulating the independent variable Independent variable - The variable that is manipulated to study the effect on the dependent variable Residual - (Y-Y') The error of estimation; The differencebetween the value of the dependent variable and its estimate Standard error of estimation - The standard deviation around the regression line or the standard deviation of residuals Simple probability - The likelihood of occurence of an event Joint probability - The likelihood of co-occurence of two or more events Denoted as P(A and B) or P(A∩B) Independent events - Event in which the outcome of the first does not influence the outcome of the second So P(A|B) = P(A) and P(B|A) = P(A) Mutually exclusive events - Their joint probability is zero and the disjunctive probability is the sum of the individual probabilities If A and B are mutually exclusive, P(A∪B) = P(A) + P(B) Conditional probability - The likelihood of event B occuring given that event A has already occurred Denoted as P(B given A) or P(B|A) Disjunctive probability - The likelihood of either event A or event B both occuring Denoted as P(A or B) or P(A∪B) Permutations - The total number of orderings of a set or subset
