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The larger the value of the standard deviation, the more spread out data points are. Some of the statistical tests and procedures used in predictive analytics are: • Analysis of variance (ANOVA): ANOVA models are used to analyze the differences between group means and the variation among and between the groups. • Chi-squared test: This is a hypothesis in where when the null hypothesis is true when the sampling distribution of the test statistic is a chi-squared distribution. • Correlation: Correlation means the dependence between the statistical relationship between two random variables or two sets of data. • Factor analysis: This describe the variability among observed and correlated variables with reference to factors which are unobserved variables. • Mann–Whitney U: This a hypothesis that a particular population tends to have larger values than the other. • Mean square weighted deviation (MSWD): Measures of goodness of fit. • Pearson product-moment correlation coefficient: This is a measure of the degree of linear dependence between two variables. • Regression analysis: Estimating the relationships among variables. • Spearman’s rank correlation coefficient: Measure of statistical dependence between two variables. • Student’s t-test: This is used to determine if two sets of data are significantly different from each other. • Time series analysis: This is a sequence of data points, measured at successive points in time. • k-nearest neighbor algorithm (k-NN)is a non-parametric method for classification and regression, which predicts the objects values or class memberships based on the k closest training examples in the feature space. • Majority classifier takes non anomalous data and incorporates it within its calculations.

Pages: 168

Publisher: Springer; 2011 edition (September 16, 2011)

ISBN: 3642228976

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