{"product_id":"course-slides-for-quantitative-research-methods-using-risk-simulator-and-rov-bizstats-software-applying-econometrics-multivariate-regression-parame-paperback","title":"Course Slides for Quantitative Research Methods Using Risk Simulator and ROV BizStats Software: Applying Econometrics, Multivariate Regression, Parame - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eJohnathan Mun\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFIFTH EDITION (2022) COURSE SLIDES\u003c\/b\u003e\u003c\/p\u003e\u003cb\u003eINTRODUCTION\u003c\/b\u003e\u003cbr\u003eResearch Philosophy, Ontology, Epistemology\u003cbr\u003eTheory, Constructs, Propositions, Logic, Attributes of a Good Theory, Theory Building\u003cbr\u003eQualitative Research: Case Study, Phenomenology, Field Research, Ethnographic Research, Grounded Theory\u003cbr\u003eProbabilistic \u0026amp; Nonprobabilistic Sampling\u003cbr\u003eReliability \u0026amp; Threats to Validity\u003cbr\u003eTrue\/Quasi Experimental Design \u003cp\u003e\u003c\/p\u003e\u003cb\u003eTHE BASICS\u003c\/b\u003e\u003cbr\u003eCentral Tendency, Spread, Skew, Kurtosis\u003cbr\u003eProbability, Bayes' Theorem, Trees, Combination, Permutation\u003cbr\u003ePDF, 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 \u003cp\u003e\u003c\/p\u003eClassical, Standard, P-Value, CI\u003cbr\u003eCentral Limit Theorem\u003cbr\u003eType I-IV Errors, Sampling Biases\u003cbr\u003eData Types \u0026amp; Collection Design \u003cp\u003e\u003c\/p\u003e\u003cb\u003eANALYTICAL METHODS\u003c\/b\u003e\u003cbr\u003eT-Tests: Equal\/Unequal\/Paired Variance, F-Test, Z-Test\u003cbr\u003eANOVA, Blocked, Two-Way, ANCOVA, MANOVA\u003cbr\u003eLinear\/Nonlinear Correlation\u003cbr\u003eNormality \u0026amp; Distributional Fitting: Kolmogorov-Smirnov, Chi-Square, Akaike Information Criterion, Anderson-Darling, Kuiper's, Schwarz\/Bayes, Box-Cox\u003cbr\u003eNonparametrics: Runs, Wilcoxon, Mann-Whitney, Lilliefors, Q-Q, D'Agostino-Pearson, Shapiro-Wilk-Royston, Kruskal-Wallis, Mood's, Cochran's Q, Friedman's\u003cbr\u003eInter\/Intra-Rater Reliability, Consistency, Diversity, Internal\/External Validity, Predictability\u003cbr\u003eCohen's Kappa, Cronbach's Alpha, Guttman's Lambda, Inter-Class Correlation, Kendall's W, Shannon-Brillouin-Simpson Diversity, Homogeneity, Grubbs Outlier, Mahalanobis, Linear \u0026amp; Quadratic Discriminant, Hannan-Quinn, Diebold-Mariano, Pesaran-Timmermann, Precision, Error Control\u003cbr\u003eLinear\/Nonlinear Multivariate Regression\u003cbr\u003eMulticollinearity, Heteroskedasticity\u003cbr\u003eStructural Equation Modeling (SEM), Partial Least Squares (PLS)\u003cbr\u003eEndogeneity, Simultaneous Equations Methods, Two-Stage Least Squares\u003cbr\u003eGranger Causality, Engle-Granger\u003cbr\u003eAdvanced Regressions: Poisson, Deming, Ordinal Logistic, Ridge, Weighted, Bootstrap \u003cp\u003e\u003c\/p\u003e\u003cb\u003eARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (DATA SCIENCE)\u003c\/b\u003e\u003cbr\u003eBagging Linear Bootstrap\u003cbr\u003eBagging Nonlinear Bootstrap\u003cbr\u003eClassification and Regression Trees CART\u003cbr\u003eCustom Fit\u003cbr\u003eDimension Reduction Principal Component Analysis\u003cbr\u003eDimension Reduction Factor Analysis\u003cbr\u003eEnsemble Common Fit\u003cbr\u003eEnsemble Complex Fit\u003cbr\u003eEnsemble Time-Series\u003cbr\u003eGaussian Mix \u0026amp; K-Means Segmentation\u003cbr\u003eK-Nearest Neighbors\u003cbr\u003eLinear Fit Model\u003cbr\u003eMultivariate Discriminant Analysis (Linear)\u003cbr\u003eMultivariate Discriminant Analysis (Quadratic)\u003cbr\u003eNeural Network (Cosine, Tangent, Hyperbolic)\u003cbr\u003eLogistic Binary Classification\u003cbr\u003eNormit-Probit Binary Classification\u003cbr\u003ePhylogenetic Trees \u0026amp; Hierarchical Clustering\u003cbr\u003eRandom Forest\u003cbr\u003eSegmentation Clustering\u003cbr\u003eSupport Vector Machines SVM \u003cp\u003e\u003c\/p\u003e\u003cb\u003eFORECASTING AND PREDICTIVE MODELING\u003c\/b\u003e\u003cbr\u003eForecasting Techniques\u003cbr\u003eTime-Series Analysis\u003cbr\u003eStepwise Regression\u003cbr\u003eStochastic Forecasting\u003cbr\u003eNonlinear Extrapolation\u003cbr\u003eBox Jenkins ARIMA\u003cbr\u003eJ-Curve, S-Curve\u003cbr\u003eGARCH\u003cbr\u003eMarkov Chain\u003cbr\u003eGLM\/MLE: Logit, Probit, Tobit\u003cbr\u003eCubic Spline, Neural Network, Combinatorial Fuzzy Logic\u003cbr\u003eTrendlines, RMSE, MSE, MAD, MAPE, Theil's U\u003cbr\u003eOutliers, Nonlinearity, Multicollinearity, Heteroskedasticity, Autocorrelation, Structural Breaks\u003cbr\u003eFunctional Forms\u003cbr\u003eForecast Intervals, OLS, Detect\/Fix Autocorrelation \u003cp\u003e\u003c\/p\u003e\u003cb\u003eMONTE CARLO SIMULATION\u003c\/b\u003e\u003cbr\u003eConfidence Intervals, Correlations, Precision, Tornado, Sensitivity, Fitting, Percentile Fit, Bootstrapping, Distributional Analysis, Scenarios, Structural Break, Detrending, Deseasonalizing \u003cp\u003e\u003c\/p\u003e\u003cb\u003eOPTIMIZATION\u003c\/b\u003e\u003cbr\u003eAlgorithms: Continuous \u0026amp; Discrete Optimization\u003cbr\u003eEfficient Frontier \u0026amp; Stochastic O\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 462\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.93 x 11 x 8.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 25, 2017\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":52482889613619,"sku":"9781734497342","price":74.5,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/Y0pndUVPV1hjdm5lWDNUM0RZS2Rjdz09.webp?v=1759744657","url":"https:\/\/www.vysn.com\/en-ca\/products\/course-slides-for-quantitative-research-methods-using-risk-simulator-and-rov-bizstats-software-applying-econometrics-multivariate-regression-parame-paperback","provider":"VYSN","version":"1.0","type":"link"}