Lynda R Essential Training Part 2 Modeling Data-APoLLo

  RELEASE  Lynda.R.Essential.Training.Part.2.Modeling.Data-APoLLo
      URL  https://www.lynda.com/R-tutorials/R-Essential-Training-Part-2-Modeling-Data/2824299-2.html
   SOURCE  Lynda
  UPDATED  5/12/2020
     DATE  
 ex.FiLES  Yes
                GROUP  NOTES  
                                             xS2k19

15M	01 Introduction
14M	01 Introduction/001 Model data with R.mp4
1.8M	01 Introduction/002 Using the exercise files.mp4
55M	02 R for Data Science
55M	02 R for Data Science/001 Data science with R_ A case study.mp4
172M	03 Exploring Data
14M	03 Exploring Data/001 Computing frequencies.mp4
25M	03 Exploring Data/002 Computing descriptive statistics.mp4
17M	03 Exploring Data/003 Computing correlations.mp4
16M	03 Exploring Data/004 Creating contingency tables.mp4
37M	03 Exploring Data/005 Conducting a principal component analysis.mp4
49M	03 Exploring Data/006 Conducting an item analysis.mp4
17M	03 Exploring Data/007 Conducting a confirmatory factor analysis.mp4
135M	04 Analyzing Data
22M	04 Analyzing Data/001 Comparing proportions.mp4
16M	04 Analyzing Data/002 Comparing one mean to a population_ One-sample t-test.mp4
24M	04 Analyzing Data/003 Comparing paired means_ Paired samples t-test.mp4
21M	04 Analyzing Data/004 Comparing two means_ Independent samples t-test.mp4
30M	04 Analyzing Data/005 Comparing multiple means_ One-factor analysis of variance.mp4
23M	04 Analyzing Data/006 Comparing means with multiple categorical predictors_ Factorial analysis of variance.mp4
141M	05 Predicting Outcomes
28M	05 Predicting Outcomes/001 Predicting outcomes with linear regression.mp4
24M	05 Predicting Outcomes/002 Predicting outcomes with lasso regression.mp4
19M	05 Predicting Outcomes/003 Predicting outcomes with quantile regression.mp4
33M	05 Predicting Outcomes/004 Predicting outcomes with logistic regression.mp4
9.4M	05 Predicting Outcomes/005 Predicting outcomes with Poisson or log-linear regression.mp4
31M	05 Predicting Outcomes/006 Assessing predictions with blocked-entry models.mp4
129M	06 Clustering and Classifying Cases
30M	06 Clustering and Classifying Cases/001 Grouping cases with hierarchical clustering.mp4
22M	06 Clustering and Classifying Cases/002 Grouping cases with k-means clustering.mp4
30M	06 Clustering and Classifying Cases/003 Classifying cases with k-nearest neighbors.mp4
25M	06 Clustering and Classifying Cases/004 Classifying cases with decision tree analysis.mp4
24M	06 Clustering and Classifying Cases/005 Creating ensemble models with random forest classification.mp4
7.4M	07 Conclusion
7.4M	07 Conclusion/001 Next steps.mp4
3.5M	Ex_Files_R_EssT_Modeling_Data.zip
656M	total