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文档列表
11. Hypothesis Testing/1. Distributions.mp4
112.1 MB
11. Hypothesis Testing/3. Hypothesis testing.mp4
86.2 MB
11. Hypothesis Testing/2. Standard Error and Confidence Intervals.mp4
68.9 MB
11. Hypothesis Testing/7. The P-value.mp4
63.6 MB
11. Hypothesis Testing/5. Test for the mean - population variance known.mp4
61.5 MB
12. Linear Regression Analysis/1. The linear regression model.mp4
60.3 MB
11. Hypothesis Testing/8. Test for the mean - Population variance unknown.mp4
57.4 MB
6. Fundamentals of programming with R/16. Building a function in R 2.0 - Scoping.mp4
54.3 MB
12. Linear Regression Analysis/5. How to interpret the regression table.mp4
52.7 MB
5. Matrices/18. Lists in R.mp4
52.7 MB
11. Hypothesis Testing/10. Comparing two means - Dependent samples.mp4
51.6 MB
12. Linear Regression Analysis/7. Decomposition of variability SST, SSR, SSE.mp4
51.6 MB
1. Introduction/1. Ten Things You Will Learn in This Course.mp4
51.3 MB
11. Hypothesis Testing/12. Comparing two means - Independent samples.mp4
46.5 MB
3. The building blocks of R/1. Creating an object in R.mp4
46.1 MB
11. Hypothesis Testing/4. Type I and Type II errors.mp4
43.7 MB
12. Linear Regression Analysis/4. First regression in R.mp4
39.8 MB
12. Linear Regression Analysis/8. R-squared.mp4
36.1 MB
6. Fundamentals of programming with R/15. Building a function in R 2.0.mp4
33.3 MB
5. Matrices/14. Categorical data.mp4
32.3 MB
2. Getting started/6. Installing packages in R and using the library.mp4
29.1 MB
4. Vectors and vector operations/8. Getting help with R.mp4
26.0 MB
3. The building blocks of R/13. Building a function in R (basics).mp4
25.8 MB
9. Visualizing data/3. Intro to ggplot2.mp4
25.5 MB
9. Visualizing data/5. Building a histogram with ggplot2.mp4
23.7 MB
5. Matrices/15. Creating a factor in R.mp4
21.8 MB
9. Visualizing data/9. Building a box and whiskers plot with ggplot2.mp4
21.3 MB
4. Vectors and vector operations/10. Slicing and indexing a vector in R.mp4
20.0 MB
7. Data frames/2. Creating a data frame in R.mp4
19.9 MB
8. Manipulating data/8. Tidying data in R - gather() and separate().mp4
19.6 MB
8. Manipulating data/2. Data transformation with R - the Dplyr package - Part I.mp4
19.1 MB
9. Visualizing data/11. Building a scatterplot with ggplot2.mp4
17.6 MB
12. Linear Regression Analysis/2. Correlation vs regression.mp4
16.2 MB
8. Manipulating data/1. Intro.mp4
16.2 MB
5. Matrices/6. Indexing an element from a matrix.mp4
15.9 MB
7. Data frames/4. The Tidyverse package.mp4
15.9 MB
2. Getting started/3. Quick guide to the RStudio user interface.mp4
15.6 MB
5. Matrices/9. Matrix arithmetic.mp4
15.0 MB
10. Exploratory data analysis/6. Covariance and correlation.mp4
14.8 MB
2. Getting started/2. Downloading and installing R & RStudio.mp4
14.8 MB
4. Vectors and vector operations/1. Intro.mp4
12.8 MB
9. Visualizing data/7. Building a bar chart with ggplot2.mp4
12.8 MB
10. Exploratory data analysis/1. Population vs. sample.mp4
12.8 MB
5. Matrices/1. Creating a matrix in R.mp4
12.2 MB
6. Fundamentals of programming with R/9. For loops in R.mp4
12.1 MB
10. Exploratory data analysis/5. Variance, standard deviation, and coefficient of variability.mp4
11.9 MB
7. Data frames/15. Dealing with missing data in R.mp4
11.2 MB
5. Matrices/11. Matrix operations in R.mp4
11.0 MB
10. Exploratory data analysis/2. Mean, median, mode.mp4
11.0 MB
9. Visualizing data/4. Variables revisited.mp4
10.8 MB
7. Data frames/11. Indexing and slicing a data frame in R.mp4
10.6 MB
7. Data frames/13. Extending a data frame in R.mp4
10.5 MB
6. Fundamentals of programming with R/6. If, else, else if statements in R.mp4
10.1 MB
3. The building blocks of R/16. Using the script vs. using the console.mp4
9.8 MB
4. Vectors and vector operations/5. Naming a vector in R.mp4
9.6 MB
4. Vectors and vector operations/13. Changing the dimensions of an object in R.mp4
9.4 MB
7. Data frames/10. Getting a sense of your data frame.mp4
9.4 MB
3. The building blocks of R/3. Data types in R - Integers and doubles.mp4
8.8 MB
7. Data frames/6. Importing a CSV in R.mp4
8.6 MB
6. Fundamentals of programming with R/11. While loops in R.mp4
8.3 MB
6. Fundamentals of programming with R/1. Relational operators in R.mp4
7.9 MB
10. Exploratory data analysis/3. Skewness.mp4
7.9 MB
9. Visualizing data/2. Intro to data visualization.mp4
7.8 MB
5. Matrices/7. Slicing a matrix in R.mp4
7.7 MB
8. Manipulating data/3. Data transformation with R - the Dplyr package - Part II.mp4
7.7 MB
8. Manipulating data/5. Using the pipe operator in R.mp4
7.7 MB
4. Vectors and vector operations/2. Introduction to vectors.mp4
7.3 MB
2. Getting started/1. Intro.mp4
7.1 MB
12. Linear Regression Analysis/3. Geometrical representation.mp4
7.1 MB
9. Visualizing data/1. Intro.mp4
7.0 MB
7. Data frames/1. Intro.mp4
7.0 MB
6. Fundamentals of programming with R/13. Repeat loops in R.mp4
6.8 MB
7. Data frames/5. Data import in R.mp4
6.8 MB
6. Fundamentals of programming with R/8. If, else, else if statements - Keep-In-Mind's.mp4
6.8 MB
3. The building blocks of R/4. Data types in R - Characters and logicals.mp4
6.7 MB
7. Data frames/7. Data export in R.mp4
6.6 MB
3. The building blocks of R/9. Functions in R.mp4
6.5 MB
8. Manipulating data/9. Tidying data in R - unite() and spread().mp4
6.3 MB
5. Matrices/2. Faster code creating a matrix in a single line of code.mp4
6.0 MB
3. The building blocks of R/7. Coercion rules in R.mp4
5.7 MB
4. Vectors and vector operations/3. Vector recycling.mp4
5.4 MB
6. Fundamentals of programming with R/2. Logical operators in R.mp4
5.3 MB
3. The building blocks of R/11. Functions and arguments.mp4
4.7 MB
2. Getting started/5. Changing the appearance in RStudio.mp4
4.4 MB
8. Manipulating data/4. Sampling data with the Dplyr package.mp4
4.2 MB
6. Fundamentals of programming with R/3. Vectors and logicals operators.mp4
4.1 MB
5. Matrices/5. Do matrices recycle.mp4
3.5 MB
11. Hypothesis Testing/3.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf
717.0 kB
11. Hypothesis Testing/4.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf
717.0 kB
11. Hypothesis Testing/7.1 R Programming for Statistics and Data Science - Course notes - Hypothesis testing.pdf
717.0 kB
5. Matrices/15.1 Course notes - Section II, III, IV, V.pdf
709.6 kB
2. Getting started/3.1 RStudio shortcuts.pdf
701.9 kB
4. Vectors and vector operations/13.1 Course notes - Section II, III, IV.pdf
645.2 kB
10. Exploratory data analysis/6.1 landdata-states.csv
474.7 kB
7. Data frames/5.2 pokRdex_tab.txt
114.2 kB
8. Manipulating data/8.2 billboard.csv
97.6 kB
7. Data frames/8.1 employee_data.csv
76.2 kB
9. Visualizing data/6.1 employee-data.csv
76.2 kB
9. Visualizing data/5.1 titanic.csv
61.2 kB
7. Data frames/10.1 pokRdex-comma.csv
51.7 kB
7. Data frames/5.1 pokRdex_comma.csv
51.7 kB
10. Exploratory data analysis/7.3 practical_customer.csv
16.8 kB
8. Manipulating data/11.2 tb_untidy.csv
14.8 kB
10. Exploratory data analysis/7.1 practical_product.csv
13.7 kB
3. The building blocks of R/13. Building a function in R (basics).srt
12.5 kB
11. Hypothesis Testing/2. Standard Error and Confidence Intervals.srt
11.8 kB
2. Getting started/3. Quick guide to the RStudio user interface.srt
11.3 kB
8. Manipulating data/8.1 tb.csv
11.2 kB
11. Hypothesis Testing/3. Hypothesis testing.srt
10.5 kB
11. Hypothesis Testing/10. Comparing two means - Dependent samples.srt
9.8 kB
11. Hypothesis Testing/5. Test for the mean - population variance known.srt
9.8 kB
8. Manipulating data/8. Tidying data in R - gather() and separate().srt
9.2 kB
10. Exploratory data analysis/6. Covariance and correlation.srt
9.1 kB
9. Visualizing data/5. Building a histogram with ggplot2.srt
9.0 kB
6. Fundamentals of programming with R/9. For loops in R.srt
9.0 kB
9. Visualizing data/7. Building a bar chart with ggplot2.srt
8.9 kB
11. Hypothesis Testing/1. Distributions.srt
8.9 kB
9. Visualizing data/3. Intro to ggplot2.srt
8.8 kB
4. Vectors and vector operations/8. Getting help with R.srt
8.7 kB
10. Exploratory data analysis/5. Variance, standard deviation, and coefficient of variability.srt
8.6 kB
9. Visualizing data/9. Building a box and whiskers plot with ggplot2.srt
8.3 kB
5. Matrices/18. Lists in R.srt
8.3 kB
4. Vectors and vector operations/10. Slicing and indexing a vector in R.srt
8.3 kB
5. Matrices/1. Creating a matrix in R.srt
7.9 kB
11. Hypothesis Testing/12. Comparing two means - Independent samples.srt
7.8 kB
3. The building blocks of R/1. Creating an object in R.srt
7.6 kB
9. Visualizing data/11. Building a scatterplot with ggplot2.srt
7.6 kB
5. Matrices/9. Matrix arithmetic.srt
7.5 kB
2. Getting started/6. Installing packages in R and using the library.srt
7.4 kB
12. Linear Regression Analysis/1. The linear regression model.srt
7.3 kB
11. Hypothesis Testing/8. Test for the mean - Population variance unknown.srt
7.3 kB
10. Exploratory data analysis/2. Mean, median, mode.srt
7.1 kB
9. Visualizing data/4. Variables revisited.srt
7.1 kB
8. Manipulating data/2. Data transformation with R - the Dplyr package - Part I.srt
7.0 kB
6. Fundamentals of programming with R/6. If, else, else if statements in R.srt
7.0 kB
5. Matrices/15. Creating a factor in R.srt
7.0 kB
6. Fundamentals of programming with R/16. Building a function in R 2.0 - Scoping.srt
6.9 kB
6. Fundamentals of programming with R/15. Building a function in R 2.0.srt
6.8 kB
7. Data frames/2. Creating a data frame in R.srt
6.8 kB
12. Linear Regression Analysis/8. R-squared.srt
6.7 kB
11. Hypothesis Testing/7. The P-value.srt
6.6 kB
3. The building blocks of R/3. Data types in R - Integers and doubles.srt
6.6 kB
6. Fundamentals of programming with R/1. Relational operators in R.srt
6.6 kB
9. Visualizing data/3.1 hdi-cpi.csv
6.5 kB
7. Data frames/15. Dealing with missing data in R.srt
6.4 kB
12. Linear Regression Analysis/5. How to interpret the regression table.srt
5.9 kB
12. Linear Regression Analysis/4. First regression in R.srt
5.8 kB
7. Data frames/11. Indexing and slicing a data frame in R.srt
5.7 kB
6. Fundamentals of programming with R/11. While loops in R.srt
5.7 kB
4. Vectors and vector operations/13. Changing the dimensions of an object in R.srt
5.7 kB
10. Exploratory data analysis/1. Population vs. sample.srt
5.6 kB
5. Matrices/11. Matrix operations in R.srt
5.4 kB
7. Data frames/10. Getting a sense of your data frame.srt
5.3 kB
7. Data frames/13. Extending a data frame in R.srt
5.3 kB
6. Fundamentals of programming with R/8. If, else, else if statements - Keep-In-Mind's.srt
4.9 kB
9. Visualizing data/2. Intro to data visualization.srt
4.9 kB
7. Data frames/5. Data import in R.srt
4.9 kB
5. Matrices/6. Indexing an element from a matrix.srt
4.7 kB
3. The building blocks of R/4. Data types in R - Characters and logicals.srt
4.7 kB
2. Getting started/2. Downloading and installing R & RStudio.srt
4.6 kB
11. Hypothesis Testing/4. Type I and Type II errors.srt
4.6 kB
4. Vectors and vector operations/2. Introduction to vectors.srt
4.5 kB
12. Linear Regression Analysis/7. Decomposition of variability SST, SSR, SSE.srt
4.4 kB
3. The building blocks of R/9. Functions in R.srt
4.4 kB
5. Matrices/14. Categorical data.srt
4.4 kB
1. Introduction/1. Ten Things You Will Learn in This Course.srt
4.3 kB
8. Manipulating data/3. Data transformation with R - the Dplyr package - Part II.srt
4.2 kB
6. Fundamentals of programming with R/13. Repeat loops in R.srt
4.2 kB
10. Exploratory data analysis/3. Skewness.srt
4.1 kB
7. Data frames/6. Importing a CSV in R.srt
4.1 kB
7. Data frames/4. The Tidyverse package.srt
4.1 kB
6. Fundamentals of programming with R/2. Logical operators in R.srt
4.1 kB
3. The building blocks of R/16. Using the script vs. using the console.srt
4.1 kB
4. Vectors and vector operations/5. Naming a vector in R.srt
4.0 kB
5. Matrices/7. Slicing a matrix in R.srt
3.8 kB
8. Manipulating data/5. Using the pipe operator in R.srt
3.8 kB
3. The building blocks of R/7. Coercion rules in R.srt
3.7 kB
3. The building blocks of R/11. Functions and arguments.srt
3.6 kB
7. Data frames/7. Data export in R.srt
3.6 kB
12. Linear Regression Analysis/6.1 real_estate_price_size_year_view.csv
3.5 kB
8. Manipulating data/9. Tidying data in R - unite() and spread().srt
3.4 kB
5. Matrices/2. Faster code creating a matrix in a single line of code.srt
3.4 kB
6. Fundamentals of programming with R/3. Vectors and logicals operators.srt
3.1 kB
8. Manipulating data/11.3 weather_untidy.csv
2.9 kB
2. Getting started/5. Changing the appearance in RStudio.srt
2.8 kB
4. Vectors and vector operations/3. Vector recycling.srt
2.3 kB
12. Linear Regression Analysis/3. Geometrical representation.srt
2.2 kB
12. Linear Regression Analysis/2. Correlation vs regression.srt
2.2 kB
8. Manipulating data/4. Sampling data with the Dplyr package.srt
2.2 kB
5. Matrices/5. Do matrices recycle.srt
2.0 kB
8. Manipulating data/9.1 weather.csv
1.9 kB
4. Vectors and vector operations/1. Intro.srt
1.8 kB
8. Manipulating data/1. Intro.srt
1.6 kB
5. Matrices/19. Exercise Lists in R.html
1.5 kB
2. Getting started/1. Intro.srt
1.5 kB
9. Visualizing data/1. Intro.srt
1.5 kB
6. Fundamentals of programming with R/7. Exercise If, else, else if statements in R.html
1.4 kB
3. The building blocks of R/10. Exercise 4 Using functions in R.html
1.3 kB
5. Matrices/10. Exercise 13 Matrix arithmetic.html
1.3 kB
7. Data frames/1. Intro.srt
1.3 kB
3. The building blocks of R/6. Exercise 2 Data types in R.html
1.2 kB
7. Data frames/14. Exercise 18 Data frame operations.html
1.2 kB
12. Linear Regression Analysis/9. Completed 100% of the course.html
1.2 kB
4. Vectors and vector operations/4. Exercise 7 Vector recycling.html
1.2 kB
6. Fundamentals of programming with R/18. Completed 50% of the course.html
1.2 kB
9. Visualizing data/10. Exercise 23 Building a box plot with ggplot2.html
1.2 kB
10. Exploratory data analysis/7. Exercise 26 Practical example with real estate data.html
1.1 kB
5. Matrices/20. Completed 33% of the course.html
1.0 kB
8. Manipulating data/7. Exercise 19 Data transformation with Dplyr.html
935 Bytes
12. Linear Regression Analysis/4.1 regression_example.csv
933 Bytes
5. Matrices/8. Exercise 12 Indexing and slicing a matrix.html
914 Bytes
5. Matrices/13. Exercise 14 Matrix operations.html
895 Bytes
12. Linear Regression Analysis/6. Exercise Doing a regression in R.html
866 Bytes
3. The building blocks of R/15. Exercise 6 Building a function in R.html
831 Bytes
3. The building blocks of R/2. Exercise 1 Creating an object in R.html
817 Bytes
4. Vectors and vector operations/14. Exercise 10 Vector attributes - dimensions.html
785 Bytes
9. Visualizing data/8. Exercise 22 Building a bar chart with ggplot2.html
771 Bytes
7. Data frames/8. Exercise 17 Importing and exporting data in R.html
744 Bytes
3. The building blocks of R/12. Exercise 5 The arguments of a function.html
727 Bytes
8. Manipulating data/11. Exercise 20 Data tidying with Tidyr.html
696 Bytes
11. Hypothesis Testing/11. Exercise Comparing two means - Dependent samples.html
692 Bytes
5. Matrices/4. Exercise 11 Creating a matrix in R.html
682 Bytes
11. Hypothesis Testing/12.1 independent-samples.csv
664 Bytes
3. The building blocks of R/8. Exercise 3 Coercion rules in R.html
644 Bytes
9. Visualizing data/6. Exercise 21 Building a histogram with ggplot2.html
631 Bytes
4. Vectors and vector operations/6. Exercise 8 Vector attributes - names.html
585 Bytes
7. Data frames/3. Exercise 16 Creating a data frame in R.html
566 Bytes
11. Hypothesis Testing/9. Exercise Test for the mean - population variance unknown.html
548 Bytes
4. Vectors and vector operations/12. Exercise 9 Indexing and slicing a vector.html
432 Bytes
5. Matrices/17. Exercise 15 Creating a factor in R.html
415 Bytes
11. Hypothesis Testing/6. Exercise Test for the mean - population variance known.html
380 Bytes
6. Fundamentals of programming with R/17. Exercise Scoping.html
350 Bytes
11. Hypothesis Testing/11.3 weight_data_exercise_kg.csv
264 Bytes
11. Hypothesis Testing/11.1 weight_data_exercise_lbs.csv
237 Bytes
11. Hypothesis Testing/5.1 ztest-a.csv
234 Bytes
11. Hypothesis Testing/6.1 ztest-a.csv
234 Bytes
10. Exploratory data analysis/4. Exercise 25 Determining Skewness.html
197 Bytes
11. Hypothesis Testing/9.1 Test for the mean - population variance unknown exercise solution.html
180 Bytes
11. Hypothesis Testing/6.2 Test for the mean - population variance known exercise solution.html
178 Bytes
11. Hypothesis Testing/11.2 Comparing two means - dependent samples - exercise solution.html
168 Bytes
7. Data frames/8.2 Importing and exporting data in R - solution.html
162 Bytes
9. Visualizing data/8.1 Building a bar chart with ggplot2 - solution.html
162 Bytes
10. Exploratory data analysis/4.3 skew_2.csv
161 Bytes
9. Visualizing data/6.2 Building a histogram with ggplot2 - solution.html
160 Bytes
9. Visualizing data/10.1 Building a boxplot with ggplot2 - solution.html
158 Bytes
10. Exploratory data analysis/4.2 skew_1.csv
156 Bytes
2. Getting started/4. RStudio's GUI.html
156 Bytes
3. The building blocks of R/14. Objects and Functions.html
156 Bytes
3. The building blocks of R/5. Objects and Data Types.html
156 Bytes
4. Vectors and vector operations/11. Extracting elements from a vector.html
156 Bytes
4. Vectors and vector operations/12.1 Indexing and slicing a vector - solution.html
156 Bytes
4. Vectors and vector operations/7. Introduction to vectors.html
156 Bytes
4. Vectors and vector operations/9. Getting Help with R.html
156 Bytes
5. Matrices/12. Matrix operations.html
156 Bytes
5. Matrices/16. Factors in R.html
156 Bytes
5. Matrices/3. Creating a matrix.html
156 Bytes
5. Matrices/8.1 Indexing and slicing a matrix - solution.html
156 Bytes
6. Fundamentals of programming with R/14. Loops in R.html
156 Bytes
6. Fundamentals of programming with R/4. Relational and Logical operators in R.html
156 Bytes
7. Data frames/12. Data frame operations.html
156 Bytes
7. Data frames/9. Creating data frames.html
156 Bytes
8. Manipulating data/10. Tidying data.html
156 Bytes
8. Manipulating data/6. Manipulating data.html
156 Bytes
8. Manipulating data/7.1 Data transformation with Dplyr - solution.html
155 Bytes
3. The building blocks of R/12.1 The arguments of a function - solution.html
154 Bytes
3. The building blocks of R/15.1 Building a function in R - solution.html
151 Bytes
3. The building blocks of R/2.1 Creating an object in R - solution.html
150 Bytes
4. Vectors and vector operations/6.1 Vector attributes - names - solution.html
150 Bytes
4. Vectors and vector operations/14.1 Changing dimensions in R - solution.html
149 Bytes
5. Matrices/17.1 Creating a factor in R - solution.html
149 Bytes
5. Matrices/4.1 Creating a matrix in R - solution.html
149 Bytes
8. Manipulating data/11.1 Data tidying with Tidyr - solution.html
148 Bytes
12. Linear Regression Analysis/6.2 Linear regression in R - solution.html
147 Bytes
7. Data frames/3.1 Creating a data frame in R - solution.html
146 Bytes
3. The building blocks of R/10.1 Using functions in R - solution.html
145 Bytes
3. The building blocks of R/8.1 Coercion Rules in R - Solution.html
144 Bytes
7. Data frames/14.1 Data frames operations - solution.html
144 Bytes
3. The building blocks of R/6.1 Data types in R - solution.html
140 Bytes
6. Fundamentals of programming with R/7.1 If, else, else if - exercise solution.html
140 Bytes
5. Matrices/10.1 Matrix arithmetic - solution.html
138 Bytes
5. Matrices/13.1 Matrix operations - solution.html
138 Bytes
6. Fundamentals of programming with R/5.1 Logical operators exercise solution.html
138 Bytes
4. Vectors and vector operations/4.1 Vector recycling - solution.html
137 Bytes
10. Exploratory data analysis/7.2 Practical Example RE Data - Solution.html
136 Bytes
6. Fundamentals of programming with R/15.1 Generate the data we used in the previous lessons.html
136 Bytes
6. Fundamentals of programming with R/12. Exercise While loops in R.html
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