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| [CourseClub.Me].url |
48B |
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| [CourseClub.Me].url |
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| [CourseClub.Me].url |
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| [CourseClub.Me].url |
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| [DesireCourse.Net].url |
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| [DesireCourse.Net].url |
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| [DesireCourse.Net].url |
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| 1. Creating a matrix in R.mp4 |
11.66MB |
| 1. Creating a matrix in R.srt |
7.69KB |
| 1. Creating an object in R.mp4 |
43.96MB |
| 1. Creating an object in R.srt |
7.44KB |
| 1. Distributions.mp4 |
106.94MB |
| 1. Distributions.srt |
8.68KB |
| 1. Intro.mp4 |
6.77MB |
| 1. Intro.mp4 |
12.25MB |
| 1. Intro.mp4 |
6.64MB |
| 1. Intro.mp4 |
15.47MB |
| 1. Intro.mp4 |
6.66MB |
| 1. Intro.srt |
1.47KB |
| 1. Intro.srt |
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| 1. Intro.srt |
1.27KB |
| 1. Intro.srt |
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| 1. Intro.srt |
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| 1. Population vs. sample.mp4 |
12.20MB |
| 1. Population vs. sample.srt |
5.46KB |
| 1. Relational operators in R.mp4 |
7.55MB |
| 1. Relational operators in R.srt |
6.44KB |
| 1. Ten Things You Will Learn in This Course.mp4 |
48.91MB |
| 1. Ten Things You Will Learn in This Course.srt |
4.16KB |
| 1. The linear regression model.mp4 |
57.54MB |
| 1. The linear regression model.srt |
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| 10.1 Building a boxplot with ggplot2 - solution.html |
158B |
| 10.1 dependent-samples.csv |
102B |
| 10.1 For Loops in R Exercise Solution.html |
130B |
| 10.1 Matrix arithmetic - solution.html |
138B |
| 10.1 pokRdex-comma.csv |
50.46KB |
| 10.1 Using functions in R - solution.html |
145B |
| 10. Comparing two means - Dependent samples.mp4 |
49.26MB |
| 10. Comparing two means - Dependent samples.srt |
9.55KB |
| 10. Exercise 13 Matrix arithmetic.html |
1.28KB |
| 10. Exercise 23 Building a box plot with ggplot2.html |
1.12KB |
| 10. Exercise 4 Using functions in R.html |
1.30KB |
| 10. Exercise For Loops in R.html |
132B |
| 10. Getting a sense of your data frame.mp4 |
8.93MB |
| 10. Getting a sense of your data frame.srt |
5.18KB |
| 10. Slicing and indexing a vector in R.mp4 |
19.04MB |
| 10. Slicing and indexing a vector in R.srt |
8.07KB |
| 10. Tidying data.html |
156B |
| 11.1 Data tidying with Tidyr - solution.html |
148B |
| 11.1 weight_data_exercise_kg.csv |
264B |
| 11.2 Comparing two means - dependent samples - exercise solution.html |
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| 11.2 weather_untidy.csv |
2.81KB |
| 11.3 tb_untidy.csv |
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| 11.3 weight_data_exercise_lbs.csv |
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| 11. Building a scatterplot with ggplot2.mp4 |
16.84MB |
| 11. Building a scatterplot with ggplot2.srt |
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| 11. Exercise 20 Data tidying with Tidyr.html |
696B |
| 11. Exercise Comparing two means - Dependent samples.html |
692B |
| 11. Extracting elements from a vector.html |
156B |
| 11. Functions and arguments.mp4 |
4.52MB |
| 11. Functions and arguments.srt |
3.55KB |
| 11. Indexing and slicing a data frame in R.mp4 |
10.09MB |
| 11. Indexing and slicing a data frame in R.srt |
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| 11. Matrix operations in R.mp4 |
10.52MB |
| 11. Matrix operations in R.srt |
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| 11. While loops in R.mp4 |
7.94MB |
| 11. While loops in R.srt |
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| 12.1 independent-samples.csv |
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| 12.1 Indexing and slicing a vector - solution.html |
156B |
| 12.1 The arguments of a function - solution.html |
154B |
| 12.1 While Loops in R Exercise Solution.html |
132B |
| 12. Comparing two means - Independent samples.mp4 |
44.36MB |
| 12. Comparing two means - Independent samples.srt |
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| 12. Data frame operations.html |
156B |
| 12. Exercise 5 The arguments of a function.html |
727B |
| 12. Exercise 9 Indexing and slicing a vector.html |
432B |
| 12. Exercise While loops in R.html |
134B |
| 12. Matrix operations.html |
156B |
| 13.1 Course notes - Section II, III, IV.pdf |
630.05KB |
| 13.1 Matrix operations - solution.html |
138B |
| 13. Building a function in R (basics).mp4 |
24.60MB |
| 13. Building a function in R (basics).srt |
12.18KB |
| 13. Changing the dimensions of an object in R.mp4 |
8.93MB |
| 13. Changing the dimensions of an object in R.srt |
5.53KB |
| 13. Exercise 14 Matrix operations.html |
895B |
| 13. Extending a data frame in R.mp4 |
9.99MB |
| 13. Extending a data frame in R.srt |
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| 13. Repeat loops in R.mp4 |
6.45MB |
| 13. Repeat loops in R.srt |
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| 14.1 Changing dimensions in R - solution.html |
149B |
| 14.1 Data frames operations - solution.html |
144B |
| 14. Categorical data.mp4 |
30.85MB |
| 14. Categorical data.srt |
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| 14. Exercise 10 Vector attributes - dimensions.html |
785B |
| 14. Exercise 18 Data frame operations.html |
1.20KB |
| 14. Loops in R.html |
156B |
| 14. Objects and Functions.html |
156B |
| 15.1 Building a function in R - solution.html |
151B |
| 15.1 Course notes - Section II, III, IV, V.pdf |
693.00KB |
| 15.1 Generate the data we used in the previous lessons.html |
136B |
| 15. Building a function in R 2.0.mp4 |
31.78MB |
| 15. Building a function in R 2.0.srt |
6.67KB |
| 15. Creating a factor in R.mp4 |
20.78MB |
| 15. Creating a factor in R.srt |
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| 15. Dealing with missing data in R.mp4 |
10.70MB |
| 15. Dealing with missing data in R.srt |
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| 15. Exercise 6 Building a function in R.html |
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| 16. Building a function in R 2.0 - Scoping.mp4 |
51.75MB |
| 16. Building a function in R 2.0 - Scoping.srt |
6.71KB |
| 16. Factors in R.html |
156B |
| 16. Using the script vs. using the console.mp4 |
9.33MB |
| 16. Using the script vs. using the console.srt |
3.97KB |
| 17.1 Creating a factor in R - solution.html |
149B |
| 17.1 Scoping Exercise Solution.html |
126B |
| 17. Exercise 15 Creating a factor in R.html |
415B |
| 17. Exercise Scoping.html |
350B |
| 18. Completed 50% of the course.html |
1.13KB |
| 18. Lists in R.mp4 |
50.23MB |
| 18. Lists in R.srt |
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| 19.1 Lists in R - Exercise Solution.html |
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| 19. Exercise Lists in R.html |
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| 2.1 Creating an object in R - solution.html |
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| 2. Correlation vs regression.mp4 |
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| 2. Correlation vs regression.srt |
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| 2. Creating a data frame in R.mp4 |
18.98MB |
| 2. Creating a data frame in R.srt |
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| 2. Data transformation with R - the Dplyr package - Part I.mp4 |
18.17MB |
| 2. Data transformation with R - the Dplyr package - Part I.srt |
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| 2. Downloading and installing R & RStudio.mp4 |
14.09MB |
| 2. Downloading and installing R & RStudio.srt |
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| 2. Exercise 1 Creating an object in R.html |
817B |
| 2. Faster code creating a matrix in a single line of code.mp4 |
5.71MB |
| 2. Faster code creating a matrix in a single line of code.srt |
3.34KB |
| 2. Introduction to vectors.mp4 |
6.92MB |
| 2. Introduction to vectors.srt |
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| 2. Intro to data visualization.mp4 |
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| 2. Intro to data visualization.srt |
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| 2. Logical operators in R.mp4 |
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| 2. Logical operators in R.srt |
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| 2. Mean, median, mode.mp4 |
10.49MB |
| 2. Mean, median, mode.srt |
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| 2. Standard Error and Confidence Intervals.mp4 |
65.65MB |
| 2. Standard Error and Confidence Intervals.srt |
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| 20. Completed 33% of the course.html |
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| 3.1 Creating a data frame in R - solution.html |
146B |
| 3.1 hdi-cpi.csv |
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| 3.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf |
700.23KB |
| 3.1 RStudio shortcuts.pdf |
685.40KB |
| 3. Creating a matrix.html |
156B |
| 3. Data transformation with R - the Dplyr package - Part II.mp4 |
7.36MB |
| 3. Data transformation with R - the Dplyr package - Part II.srt |
4.15KB |
| 3. Data types in R - Integers and doubles.mp4 |
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| 3. Data types in R - Integers and doubles.srt |
6.46KB |
| 3. Exercise 16 Creating a data frame in R.html |
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| 3. Geometrical representation.mp4 |
6.74MB |
| 3. Geometrical representation.srt |
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| 3. Hypothesis testing.mp4 |
82.20MB |
| 3. Hypothesis testing.srt |
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| 3. Intro to ggplot2.mp4 |
24.34MB |
| 3. Intro to ggplot2.srt |
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| 3. Quick guide to the RStudio user interface.mp4 |
14.89MB |
| 3. Quick guide to the RStudio user interface.srt |
11.04KB |
| 3. Skewness.mp4 |
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| 3. Skewness.srt |
4.05KB |
| 3. Vector recycling.mp4 |
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| 3. Vector recycling.srt |
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| 3. Vectors and logicals operators.mp4 |
3.92MB |
| 3. Vectors and logicals operators.srt |
3.01KB |
| 4.1 Creating a matrix in R - solution.html |
149B |
| 4.1 regression_example.csv |
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| 4.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf |
700.23KB |
| 4.1 skew_2.csv |
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| 4.1 Vector recycling - solution.html |
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| 4.2 Determining the skew - solution.html |
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| 4.3 skew_1.csv |
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| 4. Data types in R - Characters and logicals.mp4 |
6.36MB |
| 4. Data types in R - Characters and logicals.srt |
4.57KB |
| 4. Exercise 11 Creating a matrix in R.html |
682B |
| 4. Exercise 25 Determining Skewness.html |
197B |
| 4. Exercise 7 Vector recycling.html |
1.16KB |
| 4. First regression in R.mp4 |
37.93MB |
| 4. First regression in R.srt |
5.69KB |
| 4. Relational and Logical operators in R.html |
156B |
| 4. RStudio's GUI.html |
156B |
| 4. Sampling data with the Dplyr package.mp4 |
3.99MB |
| 4. Sampling data with the Dplyr package.srt |
2.11KB |
| 4. The Tidyverse package.mp4 |
15.18MB |
| 4. The Tidyverse package.srt |
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| 4. Type I and Type II errors.mp4 |
41.66MB |
| 4. Type I and Type II errors.srt |
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| 4. Variables revisited.mp4 |
10.33MB |
| 4. Variables revisited.srt |
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| 5.1 Logical operators exercise solution.html |
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| 5.1 pokRdex_comma.csv |
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| 5.1 titanic.csv |
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| 5.1 ztest-a.csv |
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| 5.2 pokRdex_tab.txt |
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| 5. Building a histogram with ggplot2.mp4 |
22.58MB |
| 5. Building a histogram with ggplot2.srt |
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| 5. Changing the appearance in RStudio.mp4 |
4.18MB |
| 5. Changing the appearance in RStudio.srt |
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| 5. Data import in R.mp4 |
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| 5. Data import in R.srt |
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| 5. Do matrices recycle.mp4 |
3.39MB |
| 5. Do matrices recycle.srt |
1.91KB |
| 5. Exercise Logical operators.html |
67B |
| 5. How to interpret the regression table.mp4 |
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| 5. How to interpret the regression table.srt |
5.74KB |
| 5. Naming a vector in R.mp4 |
9.11MB |
| 5. Naming a vector in R.srt |
3.86KB |
| 5. Objects and Data Types.html |
156B |
| 5. Test for the mean - population variance known.mp4 |
58.64MB |
| 5. Test for the mean - population variance known.srt |
9.53KB |
| 5. Using the pipe operator in R.mp4 |
7.32MB |
| 5. Using the pipe operator in R.srt |
3.66KB |
| 5. Variance, standard deviation, and coefficient of variability.mp4 |
11.35MB |
| 5. Variance, standard deviation, and coefficient of variability.srt |
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| 6.1 Data types in R - solution.html |
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| 6.1 employee-data.csv |
74.40KB |
| 6.1 landdata-states.csv |
463.53KB |
| 6.1 Linear regression in R - solution.html |
147B |
| 6.1 Test for the mean - population variance known exercise solution.html |
178B |
| 6.1 Vector attributes - names - solution.html |
150B |
| 6.2 Building a histogram with ggplot2 - solution.html |
160B |
| 6.2 real_estate_price_size_year_view.csv |
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| 6.2 ztest-a.csv |
234B |
| 6. Covariance and correlation.mp4 |
14.10MB |
| 6. Covariance and correlation.srt |
8.93KB |
| 6. Exercise 21 Building a histogram with ggplot2.html |
631B |
| 6. Exercise 2 Data types in R.html |
1.22KB |
| 6. Exercise 8 Vector attributes - names.html |
585B |
| 6. Exercise Doing a regression in R.html |
866B |
| 6. Exercise Test for the mean - population variance known.html |
380B |
| 6. If, else, else if statements in R.mp4 |
9.67MB |
| 6. If, else, else if statements in R.srt |
6.86KB |
| 6. Importing a CSV in R.mp4 |
8.18MB |
| 6. Importing a CSV in R.srt |
4.04KB |
| 6. Indexing an element from a matrix.mp4 |
15.20MB |
| 6. Indexing an element from a matrix.srt |
4.60KB |
| 6. Installing packages in R and using the library.mp4 |
27.70MB |
| 6. Installing packages in R and using the library.srt |
7.22KB |
| 6. Manipulating data.html |
156B |
| 7.1 employee_data.csv |
74.40KB |
| 7.1 If, else, else if - exercise solution.html |
140B |
| 7.1 practical_customer.csv |
16.40KB |
| 7.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf |
700.23KB |
| 7.2 Data transformation with Dplyr - solution.html |
155B |
| 7.2 Practical Example RE Data - Solution.html |
136B |
| 7.3 practical_product.csv |
13.41KB |
| 7. Building a bar chart with ggplot2.mp4 |
12.21MB |
| 7. Building a bar chart with ggplot2.srt |
8.74KB |
| 7. Coercion rules in R.mp4 |
5.44MB |
| 7. Coercion rules in R.srt |
3.66KB |
| 7. Data export in R.mp4 |
6.32MB |
| 7. Data export in R.srt |
3.52KB |
| 7. Decomposition of variability SST, SSR, SSE.mp4 |
49.19MB |
| 7. Decomposition of variability SST, SSR, SSE.srt |
4.33KB |
| 7. Exercise 19 Data transformation with Dplyr.html |
935B |
| 7. Exercise 26 Practical example with real estate data.html |
1.05KB |
| 7. Exercise If, else, else if statements in R.html |
1.32KB |
| 7. Introduction to vectors.html |
156B |
| 7. Slicing a matrix in R.mp4 |
7.37MB |
| 7. Slicing a matrix in R.srt |
3.73KB |
| 7. The P-value.mp4 |
60.63MB |
| 7. The P-value.srt |
6.48KB |
| 8.1 billboard.csv |
95.34KB |
| 8.1 Building a bar chart with ggplot2 - solution.html |
162B |
| 8.1 Coercion Rules in R - Solution.html |
144B |
| 8.1 employee_data.csv |
74.40KB |
| 8.1 Indexing and slicing a matrix - solution.html |
156B |
| 8.1 ttest-a.csv |
70B |
| 8.2 Importing and exporting data in R - solution.html |
162B |
| 8.2 tb.csv |
10.89KB |
| 8. Exercise 12 Indexing and slicing a matrix.html |
914B |
| 8. Exercise 17 Importing and exporting data in R.html |
744B |
| 8. Exercise 22 Building a bar chart with ggplot2.html |
771B |
| 8. Exercise 3 Coercion rules in R.html |
644B |
| 8. Getting help with R.mp4 |
24.77MB |
| 8. Getting help with R.srt |
8.47KB |
| 8. If, else, else if statements - Keep-In-Mind's.mp4 |
6.45MB |
| 8. If, else, else if statements - Keep-In-Mind's.srt |
4.82KB |
| 8. R-squared.mp4 |
34.41MB |
| 8. R-squared.srt |
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| 8. Test for the mean - Population variance unknown.mp4 |
54.76MB |
| 8. Test for the mean - Population variance unknown.srt |
7.12KB |
| 8. Tidying data in R - gather() and separate().mp4 |
18.70MB |
| 8. Tidying data in R - gather() and separate().srt |
9.00KB |
| 9.1 ttest-a.csv |
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| 9.1 weather.csv |
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| 9.2 Test for the mean - population variance unknown exercise solution.html |
180B |
| 9. Building a box and whiskers plot with ggplot2.mp4 |
20.28MB |
| 9. Building a box and whiskers plot with ggplot2.srt |
8.13KB |
| 9. Completed 100% of the course.html |
1.19KB |
| 9. Creating data frames.html |
156B |
| 9. Exercise Test for the mean - population variance unknown.html |
548B |
| 9. For loops in R.mp4 |
11.55MB |
| 9. For loops in R.srt |
8.76KB |
| 9. Functions in R.mp4 |
6.18MB |
| 9. Functions in R.srt |
4.31KB |
| 9. Getting Help with R.html |
156B |
| 9. Matrix arithmetic.mp4 |
14.32MB |
| 9. Matrix arithmetic.srt |
7.34KB |
| 9. Tidying data in R - unite() and spread().mp4 |
6.01MB |
| 9. Tidying data in R - unite() and spread().srt |
3.34KB |