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

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

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收录时间：2021-03-25
最近下载：2024-11-13

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文件列表

  • 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 68.8 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 29.0 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 17.7 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
  • 7. Data frames/10. Getting a sense of your data frame.mp4 9.4 MB
  • 4. Vectors and vector operations/13. Changing the dimensions of an object in R.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 7.7 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
  • 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
  • 6. Fundamentals of programming with R/13. Repeat loops in R.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 3.6 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
  • 8. Manipulating data/8.1 billboard.csv 97.6 kB
  • 7. Data frames/8.1 employee_data.csv 76.2 kB
  • 8. Manipulating data/7.1 employee_data.csv 76.2 kB
  • 9. Visualizing data/6.1 employee-data.csv 76.2 kB
  • 7. Data frames/5.1 pokRdex_comma.csv 61.9 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/5.2 pokRdex_tab.txt 33.0 kB
  • 10. Exploratory data analysis/7.1 practical_customer.csv 16.8 kB
  • 8. Manipulating data/11.3 tb_untidy.csv 14.8 kB
  • 10. Exploratory data analysis/7.3 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/8.2 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/6.2 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/11.2 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/11.1 weight_data_exercise_kg.csv 264 Bytes
  • 11. Hypothesis Testing/11.3 weight_data_exercise_lbs.csv 237 Bytes
  • 11. Hypothesis Testing/5.1 ztest-a.csv 234 Bytes
  • 11. Hypothesis Testing/6.2 ztest-a.csv 234 Bytes
  • 10. Exploratory data analysis/4. Exercise 25 Determining Skewness.html 197 Bytes
  • 11. Hypothesis Testing/9.2 Test for the mean - population variance unknown exercise solution.html 180 Bytes
  • 11. Hypothesis Testing/6.1 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/4.1 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/4.3 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/7.2 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/6.1 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
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  • 6. Fundamentals of programming with R/12. Exercise While loops in R.html 134 Bytes
  • 5. Matrices/19.1 Lists in R - Exercise Solution.html 133 Bytes
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  • 6. Fundamentals of programming with R/17.1 Scoping Exercise Solution.html 126 Bytes
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  • 11. Hypothesis Testing/10.1 dependent-samples.csv 102 Bytes
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  • 6. Fundamentals of programming with R/5. Exercise Logical operators.html 67 Bytes
  • 0. Websites you may like/[DesireCourse.Net].url 51 Bytes
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  • 12. Linear Regression Analysis/[DesireCourse.Net].url 51 Bytes
  • 5. Matrices/[DesireCourse.Net].url 51 Bytes
  • 9. Visualizing data/[DesireCourse.Net].url 51 Bytes
  • [DesireCourse.Net].url 51 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 48 Bytes
  • 1. Introduction/[CourseClub.Me].url 48 Bytes
  • 12. Linear Regression Analysis/[CourseClub.Me].url 48 Bytes
  • 5. Matrices/[CourseClub.Me].url 48 Bytes
  • 9. Visualizing data/[CourseClub.Me].url 48 Bytes
  • [CourseClub.Me].url 48 Bytes

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