Course Slides for Quantitative Research Methods Using Risk Simulator and ROV BizStats Software: Applying Econometrics, Multivariate Regression, Parame
Reseña del libro "Course Slides for Quantitative Research Methods Using Risk Simulator and ROV BizStats Software: Applying Econometrics, Multivariate Regression, Parame"
FIFTH EDITION (2022) COURSE SLIDESINTRODUCTIONResearch Philosophy, Ontology, EpistemologyTheory, Constructs, Propositions, Logic, Attributes of a Good Theory, Theory BuildingQualitative Research: Case Study, Phenomenology, Field Research, Ethnographic Research, Grounded TheoryProbabilistic & Nonprobabilistic SamplingReliability & Threats to ValidityTrue/Quasi Experimental Design THE BASICSCentral Tendency, Spread, Skew, KurtosisProbability, Bayes' Theorem, Trees, Combination, PermutationPDF, CDF, ICDF, Binomial, Hypergeometric, Poisson, Bernoulli, Discrete Uniform, Geometric, Negative Binomial, Pascal, Arcsine, Beta, Cauchy Lorentzian, Breit Wigner, Chi-Square, Cosine, Double Log, Erlang, Exponential, Extreme Value Gumbel, F Fisher Snedecor, Gamma Erlang, Laplace, Logistic, Lognormal, Normal, Parabolic, Pareto, Pearson V/VI, PERT, Power, Student's T, Triangular, Uniform, Weibull/Rayleigh Classical, Standard, P-Value, CICentral Limit TheoremType I-IV Errors, Sampling BiasesData Types & Collection Design ANALYTICAL METHODST-Tests: Equal/Unequal/Paired Variance, F-Test, Z-TestANOVA, Blocked, Two-Way, ANCOVA, MANOVALinear/Nonlinear CorrelationNormality & Distributional Fitting: Kolmogorov-Smirnov, Chi-Square, Akaike Information Criterion, Anderson-Darling, Kuiper's, Schwarz/Bayes, Box-CoxNonparametrics: Runs, Wilcoxon, Mann-Whitney, Lilliefors, Q-Q, D'Agostino-Pearson, Shapiro-Wilk-Royston, Kruskal-Wallis, Mood's, Cochran's Q, Friedman'sInter/Intra-Rater Reliability, Consistency, Diversity, Internal/External Validity, PredictabilityCohen's Kappa, Cronbach's Alpha, Guttman's Lambda, Inter-Class Correlation, Kendall's W, Shannon-Brillouin-Simpson Diversity, Homogeneity, Grubbs Outlier, Mahalanobis, Linear & Quadratic Discriminant, Hannan-Quinn, Diebold-Mariano, Pesaran-Timmermann, Precision, Error ControlLinear/Nonlinear Multivariate RegressionMulticollinearity, HeteroskedasticityStructural Equation Modeling (SEM), Partial Least Squares (PLS)Endogeneity, Simultaneous Equations Methods, Two-Stage Least SquaresGranger Causality, Engle-GrangerAdvanced Regressions: Poisson, Deming, Ordinal Logistic, Ridge, Weighted, Bootstrap ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (DATA SCIENCE)Bagging Linear BootstrapBagging Nonlinear BootstrapClassification and Regression Trees CARTCustom FitDimension Reduction Principal Component AnalysisDimension Reduction Factor AnalysisEnsemble Common FitEnsemble Complex FitEnsemble Time-SeriesGaussian Mix & K-Means SegmentationK-Nearest NeighborsLinear Fit ModelMultivariate Discriminant Analysis (Linear)Multivariate Discriminant Analysis (Quadratic)Neural Network (Cosine, Tangent, Hyperbolic)Logistic Binary ClassificationNormit-Probit Binary ClassificationPhylogenetic Trees & Hierarchical ClusteringRandom ForestSegmentation ClusteringSupport Vector Machines SVM FORECASTING AND PREDICTIVE MODELINGForecasting TechniquesTime-Series AnalysisStepwise RegressionStochastic ForecastingNonlinear ExtrapolationBox Jenkins ARIMAJ-Curve, S-CurveGARCHMarkov ChainGLM/MLE: Logit, Probit, TobitCubic Spline, Neural Network, Combinatorial Fuzzy LogicTrendlines, RMSE, MSE, MAD, MAPE, Theil's UOutliers, Nonlinearity, Multicollinearity, Heteroskedasticity, Autocorrelation, Structural BreaksFunctional FormsForecast Intervals, OLS, Detect/Fix Autocorrelation MONTE CARLO SIMULATIONConfidence Intervals, Correlations, Precision, Tornado, Sensitivity, Fitting, Percentile Fit, Bootstrapping, Distributional Analysis, Scenarios, Structural Break, Detrending, Deseasonalizing OPTIMIZATIONAlgorithms: Continuous & Discrete OptimizationEfficient Frontier & Stochastic O
