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1
R as a Calculator --- Chapter 2
2
Simple Objects --- Chapter 3
3
Vectors --- Chapter 4
4
Vectors --- Chapter 4
5
Matrices --- Chapter 5
6
Matrices --- Chapter 5
7
Arrays --- Chapter 6
8
Built-in Functions --- Chapter 7
9
Built-in Functions ---Chapter 7
10
Built-in Functions --- Chapter 7
11
Built-in Functions --- Chapter 7
12
Built-in Functions --- Chapter 7
13
Built-in Functions --- Chapter 7
14
User-written Functions --- Chapter 8
15
User-written Functions --- Chapter 8
16
User-written Functions --- Chapter 8
17
Utlities --- Chapter 9
18
Complex Numbers --- Chapter 10
19
Character Strings --- Chapter 11
20
Character Strings --- Chapter 11
21
Logical Elements --- Chapter 12
22
Relational Operators --- Chapter 13
23
Coercion --- Chapter 14
24
Lists --- Chapter 15
25
Data Frames --- Chapter 16
26
Built-in Data Sets --- Chapter 17
27
Input / Output --- Chapter 18
28
Probability --- Chapter 19
29
High-Level Graphics --- Chapter 20
30
Custom Graphics --- Chapter 21
31
Custom Graphics --- Chapter 21
32
Custom Graphics --- Chapter 21
33
Conditional Execution --- Chapter 22
34
Conditional Execution --- Chapter 22
35
Iteration --- Chapter 23
36
Iteration --- Chapter 23
37
Iteration --- Chapter 23
38
Recursion --- Chapter 24
39
Simulation --- Chapter 25
40
Simulation --- Chapter 25
41
Simulation --- Chapter 25
42
Statistics --- Chapter 26
43
Statistics --- Chapter 26
44
Statistics --- Chapter 26
45
Linear Algebra --- Chapter 27
46
Packages --- Chapter 28
47
Packages --- Chapter 28
Description:
Dive into an 8-hour comprehensive tutorial on Base R programming, covering essential topics from basic calculations to advanced statistical analysis. Master R's fundamental concepts, including vectors, matrices, arrays, and built-in functions. Explore user-written functions, utilities, and complex data types such as character strings and logical elements. Learn data manipulation techniques with lists and data frames, and discover how to work with built-in datasets. Develop skills in input/output operations, probability calculations, and data visualization using high-level and custom graphics. Gain proficiency in conditional execution, iteration, recursion, and simulation techniques. Delve into statistical analysis and linear algebra applications. Finally, understand how to leverage R packages to extend functionality and streamline your data analysis workflows.

Learning Base R

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