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[] Udemy - R Programming for Statistics and Data Science 2020

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  • 文件大小:2GB
  • 下载次数:28
  • 最近下载:2021-01-09 03:55:56
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文件列表

  1. 11. Hypothesis Testing/1. Distributions.mp4 107MB
  2. 11. Hypothesis Testing/3. Hypothesis testing.mp4 82MB
  3. 11. Hypothesis Testing/2. Standard Error and Confidence Intervals.mp4 66MB
  4. 11. Hypothesis Testing/7. The P-value.mp4 61MB
  5. 11. Hypothesis Testing/5. Test for the mean - population variance known.mp4 59MB
  6. 12. Linear Regression Analysis/1. The linear regression model.mp4 58MB
  7. 11. Hypothesis Testing/8. Test for the mean - Population variance unknown.mp4 55MB
  8. 6. Fundamentals of programming with R/16. Building a function in R 2.0 - Scoping.mp4 52MB
  9. 12. Linear Regression Analysis/5. How to interpret the regression table.mp4 50MB
  10. 5. Matrices/18. Lists in R.mp4 50MB
  11. 11. Hypothesis Testing/10. Comparing two means - Dependent samples.mp4 49MB
  12. 12. Linear Regression Analysis/7. Decomposition of variability SST, SSR, SSE.mp4 49MB
  13. 1. Introduction/1. Ten Things You Will Learn in This Course.mp4 49MB
  14. 11. Hypothesis Testing/12. Comparing two means - Independent samples.mp4 44MB
  15. 3. The building blocks of R/1. Creating an object in R.mp4 44MB
  16. 11. Hypothesis Testing/4. Type I and Type II errors.mp4 42MB
  17. 12. Linear Regression Analysis/4. First regression in R.mp4 38MB
  18. 12. Linear Regression Analysis/8. R-squared.mp4 34MB
  19. 6. Fundamentals of programming with R/15. Building a function in R 2.0.mp4 32MB
  20. 5. Matrices/14. Categorical data.mp4 31MB
  21. 2. Getting started/6. Installing packages in R and using the library.mp4 28MB
  22. 4. Vectors and vector operations/8. Getting help with R.mp4 25MB
  23. 3. The building blocks of R/13. Building a function in R (basics).mp4 25MB
  24. 9. Visualizing data/3. Intro to ggplot2.mp4 24MB
  25. 9. Visualizing data/5. Building a histogram with ggplot2.mp4 23MB
  26. 5. Matrices/15. Creating a factor in R.mp4 21MB
  27. 9. Visualizing data/9. Building a box and whiskers plot with ggplot2.mp4 20MB
  28. 4. Vectors and vector operations/10. Slicing and indexing a vector in R.mp4 19MB
  29. 7. Data frames/2. Creating a data frame in R.mp4 19MB
  30. 8. Manipulating data/8. Tidying data in R - gather() and separate().mp4 19MB
  31. 8. Manipulating data/2. Data transformation with R - the Dplyr package - Part I.mp4 18MB
  32. 9. Visualizing data/11. Building a scatterplot with ggplot2.mp4 17MB
  33. 12. Linear Regression Analysis/2. Correlation vs regression.mp4 15MB
  34. 8. Manipulating data/1. Intro.mp4 15MB
  35. 5. Matrices/6. Indexing an element from a matrix.mp4 15MB
  36. 7. Data frames/4. The Tidyverse package.mp4 15MB
  37. 2. Getting started/3. Quick guide to the RStudio user interface.mp4 15MB
  38. 5. Matrices/9. Matrix arithmetic.mp4 14MB
  39. 10. Exploratory data analysis/6. Covariance and correlation.mp4 14MB
  40. 2. Getting started/2. Downloading and installing R & RStudio.mp4 14MB
  41. 4. Vectors and vector operations/1. Intro.mp4 12MB
  42. 9. Visualizing data/7. Building a bar chart with ggplot2.mp4 12MB
  43. 10. Exploratory data analysis/1. Population vs. sample.mp4 12MB
  44. 5. Matrices/1. Creating a matrix in R.mp4 12MB
  45. 6. Fundamentals of programming with R/9. For loops in R.mp4 12MB
  46. 10. Exploratory data analysis/5. Variance, standard deviation, and coefficient of variability.mp4 11MB
  47. 7. Data frames/15. Dealing with missing data in R.mp4 11MB
  48. 5. Matrices/11. Matrix operations in R.mp4 11MB
  49. 10. Exploratory data analysis/2. Mean, median, mode.mp4 10MB
  50. 9. Visualizing data/4. Variables revisited.mp4 10MB
  51. 7. Data frames/11. Indexing and slicing a data frame in R.mp4 10MB
  52. 7. Data frames/13. Extending a data frame in R.mp4 10MB
  53. 6. Fundamentals of programming with R/6. If, else, else if statements in R.mp4 10MB
  54. 3. The building blocks of R/16. Using the script vs. using the console.mp4 9MB
  55. 4. Vectors and vector operations/5. Naming a vector in R.mp4 9MB
  56. 7. Data frames/10. Getting a sense of your data frame.mp4 9MB
  57. 4. Vectors and vector operations/13. Changing the dimensions of an object in R.mp4 9MB
  58. 3. The building blocks of R/3. Data types in R - Integers and doubles.mp4 8MB
  59. 7. Data frames/6. Importing a CSV in R.mp4 8MB
  60. 6. Fundamentals of programming with R/11. While loops in R.mp4 8MB
  61. 6. Fundamentals of programming with R/1. Relational operators in R.mp4 8MB
  62. 10. Exploratory data analysis/3. Skewness.mp4 8MB
  63. 9. Visualizing data/2. Intro to data visualization.mp4 7MB
  64. 5. Matrices/7. Slicing a matrix in R.mp4 7MB
  65. 8. Manipulating data/3. Data transformation with R - the Dplyr package - Part II.mp4 7MB
  66. 8. Manipulating data/5. Using the pipe operator in R.mp4 7MB
  67. 4. Vectors and vector operations/2. Introduction to vectors.mp4 7MB
  68. 2. Getting started/1. Intro.mp4 7MB
  69. 12. Linear Regression Analysis/3. Geometrical representation.mp4 7MB
  70. 9. Visualizing data/1. Intro.mp4 7MB
  71. 7. Data frames/1. Intro.mp4 7MB
  72. 7. Data frames/5. Data import in R.mp4 6MB
  73. 6. Fundamentals of programming with R/8. If, else, else if statements - Keep-In-Mind's.mp4 6MB
  74. 6. Fundamentals of programming with R/13. Repeat loops in R.mp4 6MB
  75. 3. The building blocks of R/4. Data types in R - Characters and logicals.mp4 6MB
  76. 7. Data frames/7. Data export in R.mp4 6MB
  77. 3. The building blocks of R/9. Functions in R.mp4 6MB
  78. 8. Manipulating data/9. Tidying data in R - unite() and spread().mp4 6MB
  79. 5. Matrices/2. Faster code creating a matrix in a single line of code.mp4 6MB
  80. 3. The building blocks of R/7. Coercion rules in R.mp4 5MB
  81. 4. Vectors and vector operations/3. Vector recycling.mp4 5MB
  82. 6. Fundamentals of programming with R/2. Logical operators in R.mp4 5MB
  83. 3. The building blocks of R/11. Functions and arguments.mp4 5MB
  84. 2. Getting started/5. Changing the appearance in RStudio.mp4 4MB
  85. 8. Manipulating data/4. Sampling data with the Dplyr package.mp4 4MB
  86. 6. Fundamentals of programming with R/3. Vectors and logicals operators.mp4 4MB
  87. 5. Matrices/5. Do matrices recycle.mp4 3MB
  88. 11. Hypothesis Testing/3.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf 700KB
  89. 11. Hypothesis Testing/4.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf 700KB
  90. 11. Hypothesis Testing/7.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf 700KB
  91. 5. Matrices/15.1 Course notes - Section II, III, IV, V.pdf 693KB
  92. 2. Getting started/3.1 RStudio shortcuts.pdf 685KB
  93. 4. Vectors and vector operations/13.1 Course notes - Section II, III, IV.pdf 630KB
  94. 10. Exploratory data analysis/6.1 landdata-states.csv 464KB
  95. 8. Manipulating data/8.1 billboard.csv 95KB
  96. 7. Data frames/8.1 employee_data.csv 74KB
  97. 8. Manipulating data/7.1 employee_data.csv 74KB
  98. 9. Visualizing data/6.1 employee-data.csv 74KB
  99. 7. Data frames/5.1 pokRdex_comma.csv 60KB
  100. 9. Visualizing data/5.1 titanic.csv 60KB
  101. 7. Data frames/10.1 pokRdex-comma.csv 50KB
  102. 7. Data frames/5.2 pokRdex_tab.txt 32KB
  103. 10. Exploratory data analysis/7.1 practical_customer.csv 16KB
  104. 8. Manipulating data/11.3 tb_untidy.csv 14KB
  105. 10. Exploratory data analysis/7.3 practical_product.csv 13KB
  106. 3. The building blocks of R/13. Building a function in R (basics).srt 12KB
  107. 11. Hypothesis Testing/2. Standard Error and Confidence Intervals.srt 12KB
  108. 2. Getting started/3. Quick guide to the RStudio user interface.srt 11KB
  109. 8. Manipulating data/8.2 tb.csv 11KB
  110. 11. Hypothesis Testing/3. Hypothesis testing.srt 10KB
  111. 11. Hypothesis Testing/10. Comparing two means - Dependent samples.srt 10KB
  112. 11. Hypothesis Testing/5. Test for the mean - population variance known.srt 10KB
  113. 8. Manipulating data/8. Tidying data in R - gather() and separate().srt 9KB
  114. 10. Exploratory data analysis/6. Covariance and correlation.srt 9KB
  115. 9. Visualizing data/5. Building a histogram with ggplot2.srt 9KB
  116. 6. Fundamentals of programming with R/9. For loops in R.srt 9KB
  117. 9. Visualizing data/7. Building a bar chart with ggplot2.srt 9KB
  118. 11. Hypothesis Testing/1. Distributions.srt 9KB
  119. 9. Visualizing data/3. Intro to ggplot2.srt 9KB
  120. 4. Vectors and vector operations/8. Getting help with R.srt 8KB
  121. 10. Exploratory data analysis/5. Variance, standard deviation, and coefficient of variability.srt 8KB
  122. 9. Visualizing data/9. Building a box and whiskers plot with ggplot2.srt 8KB
  123. 5. Matrices/18. Lists in R.srt 8KB
  124. 4. Vectors and vector operations/10. Slicing and indexing a vector in R.srt 8KB
  125. 5. Matrices/1. Creating a matrix in R.srt 8KB
  126. 11. Hypothesis Testing/12. Comparing two means - Independent samples.srt 8KB
  127. 3. The building blocks of R/1. Creating an object in R.srt 7KB
  128. 9. Visualizing data/11. Building a scatterplot with ggplot2.srt 7KB
  129. 5. Matrices/9. Matrix arithmetic.srt 7KB
  130. 2. Getting started/6. Installing packages in R and using the library.srt 7KB
  131. 12. Linear Regression Analysis/1. The linear regression model.srt 7KB
  132. 11. Hypothesis Testing/8. Test for the mean - Population variance unknown.srt 7KB
  133. 10. Exploratory data analysis/2. Mean, median, mode.srt 7KB
  134. 9. Visualizing data/4. Variables revisited.srt 7KB
  135. 8. Manipulating data/2. Data transformation with R - the Dplyr package - Part I.srt 7KB
  136. 6. Fundamentals of programming with R/6. If, else, else if statements in R.srt 7KB
  137. 5. Matrices/15. Creating a factor in R.srt 7KB
  138. 6. Fundamentals of programming with R/16. Building a function in R 2.0 - Scoping.srt 7KB
  139. 6. Fundamentals of programming with R/15. Building a function in R 2.0.srt 7KB
  140. 7. Data frames/2. Creating a data frame in R.srt 7KB
  141. 12. Linear Regression Analysis/8. R-squared.srt 7KB
  142. 11. Hypothesis Testing/7. The P-value.srt 6KB
  143. 3. The building blocks of R/3. Data types in R - Integers and doubles.srt 6KB
  144. 6. Fundamentals of programming with R/1. Relational operators in R.srt 6KB
  145. 9. Visualizing data/3.1 hdi-cpi.csv 6KB
  146. 7. Data frames/15. Dealing with missing data in R.srt 6KB
  147. 12. Linear Regression Analysis/5. How to interpret the regression table.srt 6KB
  148. 12. Linear Regression Analysis/4. First regression in R.srt 6KB
  149. 7. Data frames/11. Indexing and slicing a data frame in R.srt 6KB
  150. 6. Fundamentals of programming with R/11. While loops in R.srt 6KB
  151. 4. Vectors and vector operations/13. Changing the dimensions of an object in R.srt 6KB
  152. 10. Exploratory data analysis/1. Population vs. sample.srt 5KB
  153. 5. Matrices/11. Matrix operations in R.srt 5KB
  154. 7. Data frames/10. Getting a sense of your data frame.srt 5KB
  155. 7. Data frames/13. Extending a data frame in R.srt 5KB
  156. 6. Fundamentals of programming with R/8. If, else, else if statements - Keep-In-Mind's.srt 5KB
  157. 9. Visualizing data/2. Intro to data visualization.srt 5KB
  158. 7. Data frames/5. Data import in R.srt 5KB
  159. 5. Matrices/6. Indexing an element from a matrix.srt 5KB
  160. 3. The building blocks of R/4. Data types in R - Characters and logicals.srt 5KB
  161. 2. Getting started/2. Downloading and installing R & RStudio.srt 5KB
  162. 11. Hypothesis Testing/4. Type I and Type II errors.srt 4KB
  163. 4. Vectors and vector operations/2. Introduction to vectors.srt 4KB
  164. 12. Linear Regression Analysis/7. Decomposition of variability SST, SSR, SSE.srt 4KB
  165. 3. The building blocks of R/9. Functions in R.srt 4KB
  166. 5. Matrices/14. Categorical data.srt 4KB
  167. 1. Introduction/1. Ten Things You Will Learn in This Course.srt 4KB
  168. 8. Manipulating data/3. Data transformation with R - the Dplyr package - Part II.srt 4KB
  169. 6. Fundamentals of programming with R/13. Repeat loops in R.srt 4KB
  170. 10. Exploratory data analysis/3. Skewness.srt 4KB
  171. 7. Data frames/6. Importing a CSV in R.srt 4KB
  172. 7. Data frames/4. The Tidyverse package.srt 4KB
  173. 6. Fundamentals of programming with R/2. Logical operators in R.srt 4KB
  174. 3. The building blocks of R/16. Using the script vs. using the console.srt 4KB
  175. 4. Vectors and vector operations/5. Naming a vector in R.srt 4KB
  176. 5. Matrices/7. Slicing a matrix in R.srt 4KB
  177. 8. Manipulating data/5. Using the pipe operator in R.srt 4KB
  178. 3. The building blocks of R/7. Coercion rules in R.srt 4KB
  179. 3. The building blocks of R/11. Functions and arguments.srt 4KB
  180. 7. Data frames/7. Data export in R.srt 4KB
  181. 12. Linear Regression Analysis/6.2 real_estate_price_size_year_view.csv 3KB
  182. 8. Manipulating data/9. Tidying data in R - unite() and spread().srt 3KB
  183. 5. Matrices/2. Faster code creating a matrix in a single line of code.srt 3KB
  184. 6. Fundamentals of programming with R/3. Vectors and logicals operators.srt 3KB
  185. 8. Manipulating data/11.2 weather_untidy.csv 3KB
  186. 2. Getting started/5. Changing the appearance in RStudio.srt 3KB
  187. 4. Vectors and vector operations/3. Vector recycling.srt 2KB
  188. 12. Linear Regression Analysis/3. Geometrical representation.srt 2KB
  189. 12. Linear Regression Analysis/2. Correlation vs regression.srt 2KB
  190. 8. Manipulating data/4. Sampling data with the Dplyr package.srt 2KB
  191. 5. Matrices/5. Do matrices recycle.srt 2KB
  192. 8. Manipulating data/9.1 weather.csv 2KB
  193. 4. Vectors and vector operations/1. Intro.srt 2KB
  194. 8. Manipulating data/1. Intro.srt 2KB
  195. 5. Matrices/19. Exercise Lists in R.html 1KB
  196. 2. Getting started/1. Intro.srt 1KB
  197. 9. Visualizing data/1. Intro.srt 1KB
  198. 6. Fundamentals of programming with R/7. Exercise If, else, else if statements in R.html 1KB
  199. 3. The building blocks of R/10. Exercise 4 Using functions in R.html 1KB
  200. 5. Matrices/10. Exercise 13 Matrix arithmetic.html 1KB
  201. 7. Data frames/1. Intro.srt 1KB
  202. 3. The building blocks of R/6. Exercise 2 Data types in R.html 1KB
  203. 7. Data frames/14. Exercise 18 Data frame operations.html 1KB
  204. 12. Linear Regression Analysis/9. Completed 100% of the course.html 1KB
  205. 4. Vectors and vector operations/4. Exercise 7 Vector recycling.html 1KB
  206. 6. Fundamentals of programming with R/18. Completed 50% of the course.html 1KB
  207. 9. Visualizing data/10. Exercise 23 Building a box plot with ggplot2.html 1KB
  208. 10. Exploratory data analysis/7. Exercise 26 Practical example with real estate data.html 1KB
  209. 5. Matrices/20. Completed 33% of the course.html 1KB
  210. 8. Manipulating data/7. Exercise 19 Data transformation with Dplyr.html 935B
  211. 12. Linear Regression Analysis/4.1 regression_example.csv 933B
  212. 5. Matrices/8. Exercise 12 Indexing and slicing a matrix.html 914B
  213. 5. Matrices/13. Exercise 14 Matrix operations.html 895B
  214. 12. Linear Regression Analysis/6. Exercise Doing a regression in R.html 866B
  215. 3. The building blocks of R/15. Exercise 6 Building a function in R.html 831B
  216. 3. The building blocks of R/2. Exercise 1 Creating an object in R.html 817B
  217. 4. Vectors and vector operations/14. Exercise 10 Vector attributes - dimensions.html 785B
  218. 9. Visualizing data/8. Exercise 22 Building a bar chart with ggplot2.html 771B
  219. 7. Data frames/8. Exercise 17 Importing and exporting data in R.html 744B
  220. 3. The building blocks of R/12. Exercise 5 The arguments of a function.html 727B
  221. 8. Manipulating data/11. Exercise 20 Data tidying with Tidyr.html 696B
  222. 11. Hypothesis Testing/11. Exercise Comparing two means - Dependent samples.html 692B
  223. 5. Matrices/4. Exercise 11 Creating a matrix in R.html 682B
  224. 11. Hypothesis Testing/12.1 independent-samples.csv 664B
  225. 3. The building blocks of R/8. Exercise 3 Coercion rules in R.html 644B
  226. 9. Visualizing data/6. Exercise 21 Building a histogram with ggplot2.html 631B
  227. 4. Vectors and vector operations/6. Exercise 8 Vector attributes - names.html 585B
  228. 7. Data frames/3. Exercise 16 Creating a data frame in R.html 566B
  229. 11. Hypothesis Testing/9. Exercise Test for the mean - population variance unknown.html 548B
  230. 4. Vectors and vector operations/12. Exercise 9 Indexing and slicing a vector.html 432B
  231. 5. Matrices/17. Exercise 15 Creating a factor in R.html 415B
  232. 11. Hypothesis Testing/6. Exercise Test for the mean - population variance known.html 380B
  233. 6. Fundamentals of programming with R/17. Exercise Scoping.html 350B
  234. 11. Hypothesis Testing/11.1 weight_data_exercise_kg.csv 264B
  235. 11. Hypothesis Testing/11.3 weight_data_exercise_lbs.csv 237B
  236. 11. Hypothesis Testing/5.1 ztest-a.csv 234B
  237. 11. Hypothesis Testing/6.2 ztest-a.csv 234B
  238. 10. Exploratory data analysis/4. Exercise 25 Determining Skewness.html 197B
  239. 11. Hypothesis Testing/9.2 Test for the mean - population variance unknown exercise solution.html 180B
  240. 11. Hypothesis Testing/6.1 Test for the mean - population variance known exercise solution.html 178B
  241. 11. Hypothesis Testing/11.2 Comparing two means - dependent samples - exercise solution.html 168B
  242. 7. Data frames/8.2 Importing and exporting data in R - solution.html 162B
  243. 9. Visualizing data/8.1 Building a bar chart with ggplot2 - solution.html 162B
  244. 10. Exploratory data analysis/4.1 skew_2.csv 161B
  245. 9. Visualizing data/6.2 Building a histogram with ggplot2 - solution.html 160B
  246. 9. Visualizing data/10.1 Building a boxplot with ggplot2 - solution.html 158B
  247. 10. Exploratory data analysis/4.3 skew_1.csv 156B
  248. 2. Getting started/4. RStudio's GUI.html 156B
  249. 3. The building blocks of R/14. Objects and Functions.html 156B
  250. 3. The building blocks of R/5. Objects and Data Types.html 156B
  251. 4. Vectors and vector operations/11. Extracting elements from a vector.html 156B
  252. 4. Vectors and vector operations/12.1 Indexing and slicing a vector - solution.html 156B
  253. 4. Vectors and vector operations/7. Introduction to vectors.html 156B
  254. 4. Vectors and vector operations/9. Getting Help with R.html 156B
  255. 5. Matrices/12. Matrix operations.html 156B
  256. 5. Matrices/16. Factors in R.html 156B
  257. 5. Matrices/3. Creating a matrix.html 156B
  258. 5. Matrices/8.1 Indexing and slicing a matrix - solution.html 156B
  259. 6. Fundamentals of programming with R/14. Loops in R.html 156B
  260. 6. Fundamentals of programming with R/4. Relational and Logical operators in R.html 156B
  261. 7. Data frames/12. Data frame operations.html 156B
  262. 7. Data frames/9. Creating data frames.html 156B
  263. 8. Manipulating data/10. Tidying data.html 156B
  264. 8. Manipulating data/6. Manipulating data.html 156B
  265. 8. Manipulating data/7.2 Data transformation with Dplyr - solution.html 155B
  266. 3. The building blocks of R/12.1 The arguments of a function - solution.html 154B
  267. 3. The building blocks of R/15.1 Building a function in R - solution.html 151B
  268. 3. The building blocks of R/2.1 Creating an object in R - solution.html 150B
  269. 4. Vectors and vector operations/6.1 Vector attributes - names - solution.html 150B
  270. 4. Vectors and vector operations/14.1 Changing dimensions in R - solution.html 149B
  271. 5. Matrices/17.1 Creating a factor in R - solution.html 149B
  272. 5. Matrices/4.1 Creating a matrix in R - solution.html 149B
  273. 8. Manipulating data/11.1 Data tidying with Tidyr - solution.html 148B
  274. 12. Linear Regression Analysis/6.1 Linear regression in R - solution.html 147B
  275. 7. Data frames/3.1 Creating a data frame in R - solution.html 146B
  276. 3. The building blocks of R/10.1 Using functions in R - solution.html 145B
  277. 3. The building blocks of R/8.1 Coercion Rules in R - Solution.html 144B
  278. 7. Data frames/14.1 Data frames operations - solution.html 144B
  279. 3. The building blocks of R/6.1 Data types in R - solution.html 140B
  280. 6. Fundamentals of programming with R/7.1 If, else, else if - exercise solution.html 140B
  281. 5. Matrices/10.1 Matrix arithmetic - solution.html 138B
  282. 5. Matrices/13.1 Matrix operations - solution.html 138B
  283. 6. Fundamentals of programming with R/5.1 Logical operators exercise solution.html 138B
  284. 4. Vectors and vector operations/4.1 Vector recycling - solution.html 137B
  285. 10. Exploratory data analysis/7.2 Practical Example RE Data - Solution.html 136B
  286. 6. Fundamentals of programming with R/15.1 Generate the data we used in the previous lessons.html 136B
  287. 6. Fundamentals of programming with R/12. Exercise While loops in R.html 134B
  288. 5. Matrices/19.1 Lists in R - Exercise Solution.html 133B
  289. 6. Fundamentals of programming with R/10. Exercise For Loops in R.html 132B
  290. 6. Fundamentals of programming with R/12.1 While Loops in R Exercise Solution.html 132B
  291. 6. Fundamentals of programming with R/10.1 For Loops in R Exercise Solution.html 130B
  292. 6. Fundamentals of programming with R/17.1 Scoping Exercise Solution.html 126B
  293. 10. Exploratory data analysis/4.2 Determining the skew - solution.html 123B
  294. 11. Hypothesis Testing/10.1 dependent-samples.csv 102B
  295. 11. Hypothesis Testing/8.1 ttest-a.csv 70B
  296. 11. Hypothesis Testing/9.1 ttest-a.csv 70B
  297. 6. Fundamentals of programming with R/5. Exercise Logical operators.html 67B
  298. 0. Websites you may like/[DesireCourse.Net].url 51B
  299. 1. Introduction/[DesireCourse.Net].url 51B
  300. 12. Linear Regression Analysis/[DesireCourse.Net].url 51B
  301. 5. Matrices/[DesireCourse.Net].url 51B
  302. 9. Visualizing data/[DesireCourse.Net].url 51B
  303. [DesireCourse.Net].url 51B
  304. 0. Websites you may like/[CourseClub.Me].url 48B
  305. 1. Introduction/[CourseClub.Me].url 48B
  306. 12. Linear Regression Analysis/[CourseClub.Me].url 48B
  307. 5. Matrices/[CourseClub.Me].url 48B
  308. 9. Visualizing data/[CourseClub.Me].url 48B
  309. [CourseClub.Me].url 48B