News

Statistics with R – Introduction to R Language and Statistics

stp2y0 Comments
Statistics with R - Introduction to R Language and Statistics




What is statistics?

Statistics is a science, where we use information from our world to provide answers to the questions created. But how is it science? Using statistics is not enough to just collect data (information), the data needs to be trained, understood and processed to obtain a final result. This entire process until reaching the result brings a learning of great value. Where at each point that you manipulate it can bring a different result. I don’t think it’s that bad, it can be a challenge, having to test and evaluate again until reaching an effective result.

Within statistics there are several visual, mathematical, data collection and software tools. To be able to address various real-world problems. The most incredible thing about statistics is that it is interdisciplinary. Every area that you think will have something statistical connected to it. Starting with the simplest thing, the TV news shows the weather forecast. The weather is constantly changing, but through data collection, there are already known patterns used to forecast the weather for the next day. Going further, understanding space, for example, supernovae, using what is already known to measure cosmic distances.



Why should we study statistics?

By learning statistics, we can understand the biggest problems in our world, where observation alone does not provide answers. By collecting and studying data, we can find more data that we cannot visualize without proper processing.



Why use the R language?

The R language is a programming language focused on statistics. It has a wide variety of algorithms and functions to apply to various statistical problems. It is possible to explore data sets, process data, visualize and more diverse resources available in its documentation. Furthermore, the project is open source, meaning that any human being can consult the code and assist in the development and evolution of the project.



Comments



Single-Line Comments in R

# Hey !!!!!
Enter fullscreen mode

Exit fullscreen mode



Multi-line Comments in R

# Hey !!!
# Hello !!!
# Here !!!!!!
Enter fullscreen mode

Exit fullscreen mode



Variables



Variable Assignment and Output

simple_text <- "Python or R ?"
[1] "Python or R ?"
Enter fullscreen mode

Exit fullscreen mode



Data Types



String Assignment and Structure

example_text <- "Python"
str(example_text)
[1] "Python"
Enter fullscreen mode

Exit fullscreen mode



Integer Assignment and Printing

number_dogs <- 15
number_cats <- 10

print(number_dogs)
[1] 15
print(number_cats)
[1] 10
Enter fullscreen mode

Exit fullscreen mode



Integer Structure

print(str(number_dogs))
int 15
print(str(number_cats))
int 10
Enter fullscreen mode

Exit fullscreen mode



Double Assignment and Structure

salary <- 1300.33
bonus <- 112.67

print(str(salary))
num 1300.33
print(str(bonus))
num 112.67
Enter fullscreen mode

Exit fullscreen mode



Class of Double

class(salary)
[1] "numeric"
class(bonus)
[1] "numeric"
Enter fullscreen mode

Exit fullscreen mode



Convert Double to Integer

to_int <- as.integer(bonus)
[1] 112
Enter fullscreen mode

Exit fullscreen mode



Rounding Numbers

round(bonus)
[1] 113
round(salary)
[1] 1300
Enter fullscreen mode

Exit fullscreen mode



Convert Double to Character

to_char <- as.character(salary)
[1] "1300.33"
Enter fullscreen mode

Exit fullscreen mode



Print Double and Character

print(salary)
[1] 1300.33
print(to_char)
[1] "1300.33"
Enter fullscreen mode

Exit fullscreen mode



Logical, Arithmetic, and Relational Operators



Multiplication

a <- 3
b <- 10

print(a * b)
[1] 30
Enter fullscreen mode

Exit fullscreen mode



Division

a <- 3
b <- 10

print(a / b)
[1] 0.3
Enter fullscreen mode

Exit fullscreen mode



Addition

a <- 3
b <- 10

print(a + b)
[1] 13
Enter fullscreen mode

Exit fullscreen mode



Subtraction

a <- 3
b <- 10

print(a - b)
[1] -7
Enter fullscreen mode

Exit fullscreen mode



Equality Check

"a" == "b"
[1] FALSE
Enter fullscreen mode

Exit fullscreen mode



Equality Check

1 == 1
[1] TRUE
Enter fullscreen mode

Exit fullscreen mode



Logical Class

logic_ <- TRUE

class(logic_)
[1] "logical"
Enter fullscreen mode

Exit fullscreen mode



Multiplication with Logical False

FALSE * 2
[1] 0
FALSE * 100
[1] 0
FALSE * 300
[1] 0
Enter fullscreen mode

Exit fullscreen mode



Multiplication with Logical True

TRUE * 2
[1] 2
TRUE * 100
[1] 100
TRUE * 300
[1] 300
Enter fullscreen mode

Exit fullscreen mode



Greater Than Check

2 > 5
[1] FALSE
Enter fullscreen mode

Exit fullscreen mode



Equality Check

2 == 5
[1] FALSE
Enter fullscreen mode

Exit fullscreen mode



Power Calculation

5^2
[1] 25
Enter fullscreen mode

Exit fullscreen mode



Vectors, Matrices, Dataframe



Create and Display Vector

group_numbers <- c(1,2,3,4,5,6,7,8,9,10)
[1] 1 2 3 4 5 6 7 8 9 10
Enter fullscreen mode

Exit fullscreen mode



Vector Multiplication

group_numbers * 5
[1]  5 10 15 20 25 30 35 40 45 50
Enter fullscreen mode

Exit fullscreen mode



Vector Power

group_numbers ^ 2
[1]   1   4   9  16  25  36  49  64  81 100
Enter fullscreen mode

Exit fullscreen mode



Vector Division

g <- group_numbers / 2
[1] 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Enter fullscreen mode

Exit fullscreen mode



Class of Vector

class(g)
[1] "numeric"
Enter fullscreen mode

Exit fullscreen mode



Create and Display Vector with Integers

x <- c(133, 45, 23, 12, 1)
typeof(x)
[1] "double"
length(x)
[1] 5
Enter fullscreen mode

Exit fullscreen mode



Create and Display Mixed Type Vector

x <- c(33, 132.4, TRUE, "Python", FALSE)
[1] "33"     "132.4"  "TRUE"   "Python" "FALSE"
typeof(x)
[1] "character"
Enter fullscreen mode

Exit fullscreen mode



Create and Display Named Vector

x <- c("first_name"='Xeroxnildo', "last_name"='Carlomeu', "year"=97)
names(x)
[1] "first_name" "last_name"  "year"      
x["first_name"]
[1] "Xeroxnildo"
x["last_name"]
[1] "Carlomeu"
x["year"]
[1] "97"
Enter fullscreen mode

Exit fullscreen mode



Sequence with Increment

seq(1, 40, by=0.7)
[1]  1.0  1.7  2.4  3.1  3.8  4.5  5.2  5.9  6.6  7.3  8.0  8.7  9.4 10.1 10.8 11.5 12.2 12.9 13.6 14.3 15.0 15.7 16.4 17.1 17.8 18.5 19.2 19.9 20.6 21.3 22.0 22.7 23.4 24.1 24.8 25.5 26.2 26.9 27.6 28.3 29.0 29.7 30.4 31.1 31.8 32.5 33.2 33.9 34.6 35.3 36.0 36.7 37.4 38.1 38.8 39.5 40.2
Enter fullscreen mode

Exit fullscreen mode



Sequence with Length

seq(1, 10, length.out=6)
[1]  1.0  2.8  4.6  6.4  8.2 10.0
Enter fullscreen mode

Exit fullscreen mode



Decision and repetition structures



Variable Assignment and Printing

question <- 'Python is better than R ?'
print(question)
[1] "Python is better than R ?"
Enter fullscreen mode

Exit fullscreen mode



Simple If Statement

x <- TRUE
if(x){
   print("True")
}
[1] "True"
Enter fullscreen mode

Exit fullscreen mode



If-Else Statement

x <- -100
if(x > 0){
   print("TRUE")
} else {
   print("FALSE")
}
[1] "FALSE"
Enter fullscreen mode

Exit fullscreen mode



For Loop with Conditional Increment

x <- c(33,12,6,2,1,13,154)
count <- 0
for (val in x) {
    if(val %% 2 == 0)  count = count+1
}
print(count)
[1] 4
Enter fullscreen mode

Exit fullscreen mode



My Latest Posts



Favorites Projects Open Source



About the author:

A little more about me…

Graduated in Bachelor of Information Systems, in college I had contact with different technologies. Along the way, I took the Artificial Intelligence course, where I had my first contact with machine learning and Python. From this it became my passion to learn about this area. Today I work with machine learning and deep learning developing communication software. Along the way, I created a blog where I create some posts about subjects that I am studying and share them to help other users.

I’m currently learning TensorFlow and Computer Vision

Curiosity: I love coffee



Source link
lol

By stp2y

Leave a Reply

Your email address will not be published. Required fields are marked *

No widgets found. Go to Widget page and add the widget in Offcanvas Sidebar Widget Area.