Exploring Inferential Statistics and Their Discontents

2123 WordsJul 16, 20189 Pages
What are degrees of freedom? The degrees of freedom (df) of an estimate is the number or function of sample size of information on which the estimate is based and are free to vary relating to the sample size (Jackson, 2012; Trochim & Donnelly, 2008). How are the calculated? The degrees of freedom for an estimate equals the number of values minus the number of factors expected en route to the approximation in question. Therefore, the degrees of freedom of an estimate of variance is equal to N - 1, where N is the number of observations (Jackson, 2012). Given a single set of six numbers (N) the df = 6 – 1 = 5. What do inferential statistics allow you to infer? Inferential statistics establish the methods for the analyses used for…show more content…
What are your options if your dependent variable scores are not normally distributed? Transformation of data using a logarithm, square root, reciprocal, or some other function assists in normalizing the data and correcting for heteroscedasiticy, nonlinearity, and outliers when one or more variables are not normally distributed (Abrams, 1999; Bland & Altman, 1996). The extent of the deviations from normality determines the specific transformation used. A moderate difference in normality uses a square root transformation, more substantially non-normal uses a log transformation, and severely non-normal would use an inverse transformation (Abrams, 1999). The aim of data transformation allows for changing the non-normal distributed population data into more useful variable and is not uncommon as the basic statistical summaries such as the sample mean, variance, z-scores, histograms, etc., are all transformed data and require the data follow a particular distribution (Bland & Altman, 1996; Trochim & Donnelly, 2008). Part II What does p = .05 mean? P = .05, or p-value, is a probability measurement that the confidence of the research questions or null hypothesis is correct and has a less than 5 percent observed outcome on a normal distribution curve thus having statistically significant. The p-value is the prospect that null hypothesis is actually correct; however, criticisms of various scholars believe in science that nearly everything is impossible to

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