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The original SPSS manual (Nie, Bent & Hull, 1970) [11] has been described as one of "sociology's most influential books" for allowing ordinary researchers to do their own statistical analysis. [12] In addition to statistical analysis, data management (case selection, file reshaping and creating derived data) and data documentation (a metadata ...
IBM SPSS Modeler is a data mining and text analytics software application from IBM. It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.
Partial least squares (PLS) regression is a statistical method that bears some relation to principal components regression and is a reduced rank regression; [1] instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space of maximum ...
DOS For Dummies became popular due to the rarity of beginner-friendly materials for using DOS. The Windows title written by Andy Rathbone was soon released. While initially the series focused solely on software and technology topics, it later branched out to more general-interest titles, with topics as diverse as Acne For Dummies , Chess For ...
For Dummies – a similar series of how-to books from John Wiley & Sons, Inc. Découvertes Gallimard, a similar series in French of introductory books, noted for its fine illustration. Some titles are translated in other languages. FabJob – a similar series of how-to-books for starting a business or dream career
Quantile regression is a type of regression analysis used in statistics and econometrics. Whereas the method of least squares estimates the conditional mean of the response variable across values of the predictor variables, quantile regression estimates the conditional median (or other quantiles) of the response variable.
A great advantage of bootstrap is its simplicity. It is a straightforward way to derive estimates of standard errors and confidence intervals for complex estimators of the distribution, such as percentile points, proportions, Odds ratio, and correlation coefficients.
Correspondence analysis (CA) is a multivariate statistical technique proposed [1] by Herman Otto Hartley (Hirschfeld) [2] and later developed by Jean-Paul Benzécri. [3] It is conceptually similar to principal component analysis, but applies to categorical rather than continuous data.