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| Total size: |
687,335,602 |
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|
| Archived
files |
|
01 Introduction\002 Using the exercise files.mp4
[3aa6edda0024b128]
|
1,857,227 |
1554A734 |
|
01 Introduction\001 Model data with R.mp4
[2a7ca11e7960ccef]
|
13,772,856 |
0FDB2DA1 |
|
02 R for Data Science\001 Data science with R_ A case study.mp4
[8ffd1211eb46ca7c]
|
57,577,729 |
53A0CE0B |
|
03 Exploring Data\003 Computing correlations.mp4
[cc507f6d20d70aa8]
|
17,401,328 |
8FF5E812 |
|
03 Exploring Data\006 Conducting an item analysis.mp4
[d28b7efeefb5686]
|
51,313,019 |
47CEEA8A |
|
03 Exploring Data\004 Creating contingency tables.mp4
[e0924f1be4048714]
|
15,978,943 |
C07BD293 |
|
03 Exploring Data\002 Computing descriptive statistics.mp4
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|
26,060,925 |
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|
03 Exploring Data\005 Conducting a principal component analysis.mp4
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|
37,848,955 |
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|
03 Exploring Data\001 Computing frequencies.mp4
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|
14,106,669 |
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|
03 Exploring Data\007 Conducting a confirmatory factor analysis.mp4
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|
17,065,579 |
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|
04 Analyzing Data\002 Comparing one mean to a population_ One-sample t-test.mp4
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|
16,381,995 |
36ED3BE2 |
|
04 Analyzing Data\003 Comparing paired means_ Paired samples t-test.mp4
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|
25,059,810 |
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|
04 Analyzing Data\006 Comparing means with multiple categorical predictors_ Factorial analysis of variance.mp4
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|
23,304,090 |
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|
04 Analyzing Data\005 Comparing multiple means_ One-factor analysis of variance.mp4
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|
30,958,134 |
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|
04 Analyzing Data\004 Comparing two means_ Independent samples t-test.mp4
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|
21,993,741 |
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|
04 Analyzing Data\001 Comparing proportions.mp4
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|
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|
05 Predicting Outcomes\004 Predicting outcomes with logistic regression.mp4
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|
33,848,841 |
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|
05 Predicting Outcomes\005 Predicting outcomes with Poisson or log-linear regression.mp4
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|
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|
05 Predicting Outcomes\006 Assessing predictions with blocked-entry models.mp4
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|
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|
05 Predicting Outcomes\002 Predicting outcomes with lasso regression.mp4
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|
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|
05 Predicting Outcomes\003 Predicting outcomes with quantile regression.mp4
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|
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|
05 Predicting Outcomes\001 Predicting outcomes with linear regression.mp4
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|
28,459,933 |
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|
06 Clustering and Classifying Cases\003 Classifying cases with k-nearest neighbors.mp4
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|
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|
06 Clustering and Classifying Cases\004 Classifying cases with decision tree analysis.mp4
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|
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|
06 Clustering and Classifying Cases\002 Grouping cases with k-means clustering.mp4
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|
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|
06 Clustering and Classifying Cases\005 Creating ensemble models with random forest classification.mp4
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|
25,137,268 |
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|
06 Clustering and Classifying Cases\001 Grouping cases with hierarchical clustering.mp4
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|
30,501,683 |
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|
07 Conclusion\001 Next steps.mp4
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|
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|
Ex_Files_R_EssT_Modeling_Data.zip |
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01 Introduction |
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02 R for Data Science |
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03 Exploring Data |
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04 Analyzing Data |
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05 Predicting Outcomes |
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06 Clustering and Classifying Cases |
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07 Conclusion |
0 |
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| Total size: |
687,327,362 |
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