Ken Plummer

inferential vs. descriptive range select - run - interpret nature of the data independent variable difference relationship goodness of fit (2) distribution moments symmetry spread central tendency inferential descriptive difference relationship goodness of fit dichotomous or scaled skewed less than 30 (ties) skewed sample size less than 30 ordinal (ties) ordinal and nominal relationship covariates relationship nature of data number of variables (predictive) levels of the iv independent variables ( dependent variable predictive or arbitrary nature of the data (descriptive) interpret select independent samples t test - run iq range select - run - interpret interquartile range select - run - interpret standard deviation select - run - interpret mean select - run - interpret iqr standard deviation range normal or skewed distributions (descriptive both2) normal or skewed distributions (descriptive one central spread - symmetry central tendency - spread - symmetry infernetial vs desctiptive (jejit + indepth) normal or skewed distributions (inferential) normal or skewed distributions (descriptive two normal versus skewed distributions types of data data types differentiating statistical methods when to use descriptive statistics inferential statistics nature of the data (spread) mean median and mode mode categorizing stats questions diferencia entre anova e prueba de t niveles de la variable explicativa variables independientes variables explicativas datos ordinales y escalados variable dependient variables de interes bondad de ajuste relacion diferencia inferencial descriptiva t test and anova anova vs t-test levels variables of interest inferential versus descriptive romanticism spirituality anova t-test levels of iv independent variables scaled ordinal nominal dependent variables classify stat problems c distributions normal non normal practice decision based learning describing inferring descriptive inferential quick reminder arbitrary or causal relationship single sample t factorial anova