Standard deviation of x symbol

Statistical Symbols and Formulas1Taken from: http://www2.uta.edu/ssw/Basham/Statistical Symbols and Formulas.docStatistical SymbolsMean = MBeta weight or beta coefficient = Chi square = 2Coefficient of variation = VDegrees of freedom = dFrequency =Gamma (also G) = Kendall’s tau-b = bLambda ( also called the Guttman coefficient of predictability) = Level of significance = Pearson’s correlation coefficient = rPopulation mean score = Population size = NPopulation variance = 2Rho = Sample size = nSample variance = s2Standard deviation or standard error of sample = sStandard Deviation = SDStandard Error of the mean = SEThe summation sign = tdistribution for rejecting or accepting the null hypothesis = tZ Score = zStandardized scores,and Z distribution = ZCorrelation = rPoint Biserial Correlation = rpbStatistical significance = pStatistical significance = Sig.The 95% Confidence Interval = 95%CIT-test = tOne Way ANOVA or Comparison Test of Between Group Differences = FCorrelation Coefficient for ANOVA (3+ categories) = etaANOVA test of significance of difference among means= Tukey-b procedureMultiple correlation coefficient symbol ( 2 or more I.V.). = RIn SPSS ProgramBeta= (Standardized regression slope). Slope based on standard scores = average change in D.V. in S.D. units, associated with 1 S.D. increase in I.V. (1 point increase in I.V. = 1 S.D.)B= (Unstandardized regression slope). Slope based on raw scores = Indicates
Statistical Symbols and Formulas2average change in D.V. for 1 point increase in I.V.= Beta weight or beta coefficientR2change = tells whether or not variables entered at that point add anything over and above variables thathave been added previously.Variance = 2XCovariance (of x and y) = XYStatistical FormulasMeasures of Central Tendency(Simple Distribution)Mean = = NPopulation Mean = 11nXiiXXn(Frequency Distribution)Mean = = f NMdn = simple distribution= center scoreodd populationMdn = simple distribution= Even population2 center scores divided by 2Mdn = frequency distribution =LRL –(PN-CFL .h)FIMode = Most Frequent ScoreVariance Measures in a Population(Simple Distribution and Frequency Distribution)Population Standard Deviation___= 2 , or2XX(Simple Distribution)Population Variance2 = 1( X2–( X)2N –1(Frequency Distribution)Population Variance2 = 1( fX2–( fX)2N N –1Variance = Sum of squared distributions from the mean for all cases(number of cases –1) or,(X-M)2N –1Note:col:[XMX-M(X-M)2] (X-M)2N –1or,221111nnXiiiiXXnn