365 Data Science - Introduction to R Programming [CoursesGhar]

Creation Time	Aug. 21, 2023, 7:22 p.m.
Last Access Time	Sept. 28, 2024, 10:02 a.m.
File Size	2.7 GB
Keywords	CoursesGhar Introduction Science - to R Programming 365 Data
Total Requests	22
Total Files	93
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8. Manipulating data/1. Intro.mp4 105.7 MB
4. Vectors and vector operations/1. Intro.mp4 88.0 MB
11. Hypothesis Testing/1. Distributions.mp4 80.7 MB
2. Getting started/1. Intro.mp4 75.0 MB
9. Visualizing data/1. Intro.mp4 72.9 MB
9. Visualizing data/8. Building a scatterplot with ggplot2.mp4 65.9 MB
8. Manipulating data/6. Tidying your data - gather() and separate().mp4 63.4 MB
2. Getting started/5. Installing packages and using the library.mp4 56.2 MB
3. The building blocks of R/7. Building a function in R.mp4 50.1 MB
9. Visualizing data/5. Building a histogram with ggplot2.mp4 49.8 MB
9. Visualizing data/3. Intro to ggplot2.mp4 49.5 MB
4. Vectors and vector operations/5. Getting help with R.mp4 49.5 MB
5. Matrices/6. Matrix arithmetic.mp4 47.0 MB
10. Exploratory data analysis/5. Covariance and correlation.mp4 44.5 MB
2. Getting started/3. Quick guide to the RStudio user interface.mp4 42.8 MB
5. Matrices/9. Creating a factor in R.mp4 42.1 MB
9. Visualizing data/7. Building a box and whiskers plot with ggplot2.mp4 41.4 MB
4. Vectors and vector operations/6. Slicing and indexing a vector.mp4 40.1 MB
12. Linear Regression Analysis/1. The Linear Regression Model.mp4 39.9 MB
11. Hypothesis Testing/2. Standard Error and Confidence Intervals.mp4 39.7 MB
9. Visualizing data/6. Building a bar chart with ggplot2.mp4 39.1 MB
11. Hypothesis Testing/8. Comparing Two Means. Dependent Samples.mp4 38.3 MB
5. Matrices/1. Creating a matrix.mp4 38.0 MB
7. Data frames/1. Creating a data frame.mp4 37.9 MB
11. Hypothesis Testing/5. Test for the Mean. Population Variance Known.mp4 37.9 MB
8. Manipulating data/2. Data transformation with R - the Dplyr package - Part I.mp4 37.7 MB
12. Linear Regression Analysis/5. How to Interpret the Regression Table.mp4 36.4 MB
6. Fundamentals Of Programming With R/6. For Loops in R.mp4 35.7 MB
10. Exploratory data analysis/4. Variance, standard deviation, and coefficient of variability.mp4 33.7 MB
7. Data frames/8. Extending a data frame in R.mp4 33.7 MB
7. Data frames/9. Dealing with missing data.mp4 33.7 MB
5. Matrices/7. Matrix operations.mp4 33.1 MB
11. Hypothesis Testing/7. Test for the Mean. Population Variance Unknown.mp4 33.1 MB
10. Exploratory data analysis/2. Mean, median, mode.mp4 32.9 MB
7. Data frames/7. Indexing and slicing a data frame in R.mp4 32.5 MB
5. Matrices/10. Lists in R.mp4 32.1 MB
12. Linear Regression Analysis/7. R-Squared.mp4 31.2 MB
6. Fundamentals Of Programming With R/10. Scoping in R _ Building a Function in R 2.0 (Ctnd).mp4 31.1 MB
11. Hypothesis Testing/6. The P Value.mp4 30.7 MB
6. Fundamentals Of Programming With R/4. If, Else, Else-If Statements.mp4 30.5 MB
5. Matrices/4. Indexing an element from a matrix.mp4 30.2 MB
3. The building blocks of R/1. Creating an object in R.mp4 29.9 MB
4. Vectors and vector operations/7. Changing the dimensions of an object in R.mp4 29.2 MB
9. Visualizing data/4. Variables - revisited.mp4 28.8 MB
11. Hypothesis Testing/9. Comparing Two Means. Independent Samples.mp4 28.7 MB
7. Data frames/2. The Tidyverse package.mp4 27.9 MB
2. Getting started/2. Downloading and installing R _ RStudio.mp4 27.9 MB
7. Data frames/6. Getting a sense of your data frame.mp4 27.4 MB
7. Data frames/4. Importing a CSV in R.mp4 27.1 MB
3. The building blocks of R/2. Data types in R - Integers and doubles.mp4 26.7 MB
11. Hypothesis Testing/4. Type I and Type II Errors.mp4 25.2 MB
12. Linear Regression Analysis/4. Doing the Regression in R.mp4 24.8 MB
8. Manipulating data/5. Using the pipe operator.mp4 24.1 MB
6. Fundamentals Of Programming With R/7. While Loops in R.mp4 24.0 MB
10. Exploratory data analysis/3. Skewness.mp4 23.9 MB
8. Manipulating data/3. Data transformation with R - the Dplyr package - Part II.mp4 23.9 MB
6. Fundamentals Of Programming With R/1. Relational Operators in R.mp4 23.8 MB
5. Matrices/5. Slicing a matrix.mp4 23.3 MB
5. Matrices/8. Categorical data.mp4 23.2 MB
6. Fundamentals Of Programming With R/9. Building a Function in R 2.0.mp4 22.8 MB
4. Vectors and vector operations/2. Introduction to vectors.mp4 22.8 MB
12. Linear Regression Analysis/6. Decomposition of Variability.mp4 22.7 MB
11. Hypothesis Testing/3. Hypothesis Testing.mp4 22.7 MB
10. Exploratory data analysis/1. Population vs. sample.mp4 21.5 MB
7. Data frames/3. Data import in R.mp4 20.6 MB
3. The building blocks of R/3. Data types in R - Characters and logicals.mp4 20.6 MB
6. Fundamentals Of Programming With R/5. If, Else, Else-If Keep-In-Minds.mp4 20.4 MB
6. Fundamentals Of Programming With R/8. Repeat Loops in R.mp4 20.3 MB
9. Visualizing data/2. Intro to data visualization.mp4 20.2 MB
7. Data frames/5. Data export in R.mp4 19.7 MB
3. The building blocks of R/5. Functions in R.mp4 19.5 MB
8. Manipulating data/7. Tidying your data - unite() and spread().mp4 19.1 MB
3. The building blocks of R/8. Using the script vs. using the console.mp4 18.8 MB
4. Vectors and vector operations/4. Naming a vector.mp4 18.4 MB
1. Introduction/1. Welcome to R programming.mp4 18.4 MB
3. The building blocks of R/4. Coercion rules in R.mp4 18.1 MB
5. Matrices/2. Faster code - creating a matrix in a single line of code.mp4 18.0 MB
6. Fundamentals Of Programming With R/2. Logical Operators in R.mp4 15.6 MB
3. The building blocks of R/6. Functions and arguments.mp4 13.9 MB
2. Getting started/4. Changing the appearance in RStudio.mp4 12.4 MB
8. Manipulating data/4. Sampling data with the Dplyr package.mp4 12.3 MB
6. Fundamentals Of Programming With R/3. Logical Operators and Vectors.mp4 11.9 MB
5. Matrices/3. Do matrices recycle.mp4 10.6 MB
12. Linear Regression Analysis/2. Correlation vs. Regression.mp4 10.1 MB
4. Vectors and vector operations/3. Vector recycling.mp4 9.5 MB
12. Linear Regression Analysis/3. Geometrical Representation.mp4 6.5 MB
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365 Data Science - Introduction to R Programming [CoursesGhar]

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