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Linkedin - Complete Guide to R Wrangling Visualizing and Modeling Data

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文件列表

  1. 8. An R for Data Science Case Study/1. Data science with R- A case study.mp4 57MB
  2. 9. Exploring Data/6. Conducting an item analysis.mp4 52MB
  3. 9. Exploring Data/5. Conducting a principal component analysis.mp4 38MB
  4. 6. Wrangling Data/1. Creating tidy data.mp4 34MB
  5. 11. Predicting Outcomes/4. Predicting outcomes with logistic regression.mp4 31MB
  6. 11. Predicting Outcomes/6. Assessing predictions with blocked-entry models.mp4 31MB
  7. 12. Clustering and Classifying Cases/3. Classifying cases with k-nearest neighbors.mp4 31MB
  8. 2. What Is R/2. Data science with R- A case study.mp4 31MB
  9. 10. Analyzing Data/5. Comparing multiple means- One-factor analysis of variance.mp4 30MB
  10. 12. Clustering and Classifying Cases/1. Grouping cases with hierarchical clustering.mp4 29MB
  11. 3. Getting Started/6. Data types and structures.mp4 29MB
  12. 11. Predicting Outcomes/1. Predicting outcomes with linear regression.mp4 28MB
  13. 5. Visualizing Data with ggplot2/3. Using color palettes.mp4 27MB
  14. 9. Exploring Data/2. Computing descriptive statistics.mp4 25MB
  15. 5. Visualizing Data with ggplot2/9. Creating cluster charts.mp4 25MB
  16. 11. Predicting Outcomes/2. Predicting outcomes with lasso regression.mp4 25MB
  17. 12. Clustering and Classifying Cases/4. Classifying cases with decision tree analysis.mp4 24MB
  18. 10. Analyzing Data/1. Comparing proportions.mp4 24MB
  19. 5. Visualizing Data with ggplot2/4. Creating bar charts.mp4 24MB
  20. 12. Clustering and Classifying Cases/5. Creating ensemble models with random forest classification.mp4 24MB
  21. 7. Recoding Data/1. Recoding categorical data.mp4 24MB
  22. 10. Analyzing Data/3. Comparing paired means- Paired samples t-test.mp4 23MB
  23. 12. Clustering and Classifying Cases/2. Grouping cases with k-means clustering.mp4 23MB
  24. 7. Recoding Data/2. Recoding quantitative data.mp4 22MB
  25. 6. Wrangling Data/10. Filtering cases and subgroups.mp4 22MB
  26. 10. Analyzing Data/6. Comparing means with multiple categorical predictors- Factorial analysis of variance.mp4 22MB
  27. 7. Recoding Data/3. Transforming outliers.mp4 21MB
  28. 4. Importing Data/2. Exploring sample datasets with pacman.mp4 21MB
  29. 4. Importing Data/5. Importing JSON data.mp4 21MB
  30. 10. Analyzing Data/4. Comparing two means- Independent samples t-test.mp4 21MB
  31. 4. Importing Data/6. Saving data in native R formats.mp4 20MB
  32. 4. Importing Data/4. Importing XML data.mp4 19MB
  33. 6. Wrangling Data/6. Working with dates and times.mp4 19MB
  34. 11. Predicting Outcomes/3. Predicting outcomes with quantile regression.mp4 18MB
  35. 9. Exploring Data/7. Conducting a confirmatory factor analysis.mp4 18MB
  36. 4. Importing Data/3. Importing data from a spreadsheet.mp4 18MB
  37. 3. Getting Started/4. Navigating the RStudio environment.mp4 17MB
  38. 6. Wrangling Data/8. Working with XML data.mp4 17MB
  39. 3. Getting Started/8. Packages for R.mp4 17MB
  40. 3. Getting Started/5. Entering data.mp4 17MB
  41. 9. Exploring Data/4. Creating contingency tables.mp4 17MB
  42. 9. Exploring Data/3. Computing correlations.mp4 17MB
  43. 4. Importing Data/1. Rs built-in datasets.mp4 16MB
  44. 10. Analyzing Data/2. Comparing one mean to a population- One-sample t-test.mp4 16MB
  45. 5. Visualizing Data with ggplot2/2. Using colors in R.mp4 16MB
  46. 6. Wrangling Data/3. Using data.table.mp4 16MB
  47. 6. Wrangling Data/9. Working with categorical variables.mp4 15MB
  48. 6. Wrangling Data/5. Converting data from tables to rows.mp4 15MB
  49. 6. Wrangling Data/7. Working with list data.mp4 15MB
  50. 5. Visualizing Data with ggplot2/1. Introduction to ggplot2.mp4 15MB
  51. 7. Recoding Data/4. Creating scale scores by counting.mp4 14MB
  52. 9. Exploring Data/1. Computing frequencies.mp4 14MB
  53. 5. Visualizing Data with ggplot2/7. Creating scatterplots.mp4 14MB
  54. 2. What Is R/1. R in context.mp4 13MB
  55. 6. Wrangling Data/2. Using tibbles.mp4 13MB
  56. 5. Visualizing Data with ggplot2/5. Creating histograms.mp4 13MB
  57. 3. Getting Started/7. Comments and headers.mp4 13MB
  58. 5. Visualizing Data with ggplot2/6. Creating box plots.mp4 12MB
  59. 6. Wrangling Data/4. Converting data from wide to tall and from tall to wide.mp4 11MB
  60. 3. Getting Started/2. Environments for R.mp4 11MB
  61. 5. Visualizing Data with ggplot2/8. Creating multiple graphs.mp4 10MB
  62. 11. Predicting Outcomes/5. Predicting outcomes with Poisson or log-linear regression.mp4 9MB
  63. 3. Getting Started/9. The tidyverse.mp4 9MB
  64. 7. Recoding Data/5. Creating scale scores by averaging.mp4 9MB
  65. 3. Getting Started/10. Piping commands with %%.mp4 8MB
  66. Ex_Files_Complete_Guide_to_R.zip 6MB
  67. 13. Conclusion/1. Next steps.mp4 6MB
  68. 3. Getting Started/1. Installing R.mp4 5MB
  69. 1. Introduction/1. Make your data make sense.mp4 4MB
  70. 3. Getting Started/3. Installing RStudio.mp4 3MB
  71. 1. Introduction/2. Using the exercise files.mp4 2MB