Essentials of Statistics for the Behavioural Science Assignment

Essays on Essentials of Statistics for the Behavioural Science Assignment The paper "Essentials of Statistics for the Behavioural Science" is a worthy example of an essay on statistics.  Significance of having at least interval level dataThe interval level of data is desirable because of its equidistance property that facilitates analysis. It is particularly important in inferential analysis in which the difference between data values is the center of focus (Gravetter and Wallnau, 2011).   Reasons for preference of the mean as a measure for central tendencyOne of the reasons for which the mean is preferred as a measure of central tendency is its incorporation of all data to be represented that meets the need for a central measure. This is contrary to other measures of central tendency that do not consider magnitudes of every data in a data set. The mean is also preferred because of its close relation to measures of dispersion such as standard deviation (Gravetter and Wallnau, 2011). Reasons for instability of the range as a measure of variabilityThe range is an unstable measure of variability because it only considers the minimum and maximum values. This defines its suitability to measure the variability of the extremes but not the other values in between (Wood and Haber, 2013; Gravetter and Wallnau, 2011). Intended descriptions of measures of variabilityMeasures of dispersion are intended for describing variation in a data set, describing the reliability of the mean, and describing the difference in trend between two or more data sets through the exploration of variability in the distribution of data (Wood and Haber, 2013; Gravetter and Wallnau, 2011). Factors to consider when determining the level of significance in hypothesis testingImportant factors to consider when determining level of significance is the standard error, sample size, variance, and the nature of the test, whether it is a one-tailed test or a two-tailed test, because the factors have direct effects on significance of a test (Wood and Haber, 2013; Gravetter and Wallnau, 2011).