Setup Menus in Admin Panel

Course Curriculum

Introduction
1.1 Welcome to R programming 00:00:00
Getting Started
2.1 Changing the appearance in RStudio 00:00:00
2.2 Downloading and installing R & RStudio 00:00:00
2.3 Installing packages and using the library 00:00:00
2.4 Intro 00:00:00
The Building Rocks of R
3.1 Building a function in R 00:00:00
3.2 Coercion rules in R 00:00:00
3.3 Creating an object in R 00:00:00
3.4 Data types in R – Characters and logicals 00:00:00
3.5 Data types in R – Integers and doubles 00:00:00
3.6 Functions and arguments 00:00:00
3.7 Functions in R 00:00:00
3.8 Using the script vs. using the console 00:00:00
Vectors And Vector Operations
4.1 Getting help with R 00:00:00
4.2 Intro 00:00:00
4.3 Introduction to vectors 00:00:00
4.4 Slicing and indexing a vector 00:00:00
4.5 Vector recycling 00:00:00
Matrices
5.1 Categorical data 00:00:00
5.2 Creating a factor in R 00:00:00
5.3 Creating a matrix 00:00:00
5.4 Do matrices recycle 00:00:00
5.5 Faster code creating a matrix in a single line of code 00:00:00
5.6 Indexing an element from a matrix 00:00:00
5.7 Lists in R 00:00:00
5.8 Matrix arithmetic 00:00:00
5.9 Matrix operations 00:00:00
5.10Slicing a matrix 00:00:00
Fundamentals of Programming with R
6.1 Building a Function in R 2.0 00:00:00
6.2 For Loops in R 00:00:00
6.3 If, Else, Else-If Keep-In-Minds 00:00:00
6.4 If, Else, Else-If Statements 00:00:00
6.5 Logical Operators and Vectors 00:00:00
6.6 Logical Operators in R 00:00:00
6.7 Relational Operators in R 00:00:00
6.8 Repeat Loops in R 00:00:00
6.9 Scoping in R Building a Function in R 2.0 (Ctnd) 00:00:00
6.10 While Loops in R 00:00:00
Data Frames
7.1 Creating a data frame Building a Function in R 2.0 (Ctnd) 00:00:00
7.9 The Tidyverse package Building a Function in R 2.0 (Ctnd) 00:00:00
7.2 Data export in R Building a Function in R 2.0 (Ctnd) 00:00:00
7.3 Data import in R Building a Function in R 2.0 (Ctnd) 00:00:00
7.4 Dealing with missing data Building a Function in R 2.0 (Ctn 00:00:00
7.5 Extending a data frame in R Building a Function in R 2.0 (C 00:00:00
7.6 Getting a sense of your data frame Building a Function in R 00:00:00
7.7 Importing a CSV in R Building a Function in R 2.0 (Ctnd) 00:00:00
7.8 Indexing and slicing a data frame in R Building a Function 00:00:00
Manipulating Data
8.1 Data transformation with R – the Dplyr package – Part I Bui 00:00:00
8.2 Data transformation with R – the Dplyr package – Part II Bu 00:00:00
8.3 Intro Building a Function in R 2.0 (Ctnd) 00:00:00
8.4 Sampling data with the Dplyr package Building a Function in 00:00:00
8.5 Tidying your data – gather() and separate() Building a Func 00:00:00
8.6 Tidying your data – unite() and spread() Building a Functio 00:00:00
8.7 Using the pipe operator Building a Function in R 2.0 (Ctnd) 00:00:00
Visualizing Data
9.1 Building a bar chart with ggplot2 Building a Function in R 00:00:00
9.2 Building a box and whiskers plot with ggplot2 Building a Fu 00:00:00
9.3 Building a histogram with ggplot2 Building a Function in R 00:00:00
9.4 Building a scatterplot with ggplot2 Building a Function in 00:00:00
9.5 Intro Building a Function in R 2.0 (Ctnd) (1) 00:00:00
9.6 Intro to data visualization Building a Function in R 2.0 (C 00:00:00
9.7 Intro to ggplot2 Building a Function in R 2.0 (Ctnd) 00:00:00
9.8 Variables revisited Building a Function in R 2.0 (Ctnd) 00:00:00
Exploratory Data Analysis
10.1 Covariance and correlation Building a Function in R 2.0 (Ct 00:00:00
10.2 Mean, median, mode Building a Function in R 2.0 (Ctnd) 00:00:00
10.3 Population vs. sample Building a Function in R 2.0 (Ctnd) 00:00:00
10.4 Skewness Building a Function in R 2.0 (Ctnd) 00:00:00
10.5 Variance, standard deviation, and coefficient of variability 00:00:00
Hypothesis testing
11.1 Comparing Two Means. Independent Samples 00:00:00
11.2 Distributions Building a Function in R 2.0 (Ctnd) 00:00:00
11.3 Test for the Mean. Population Variance Known 00:00:00
11.4 Test for the Mean. Population Variance Unknown 00:00:00
11.5 The P Value 00:00:00
11.6 Type I and Type II Errors 00:00:00
Linear Regression Analysis
12.1 Correlation vs. Regression 00:00:00
12.2 Decomposition of Variability 00:00:00
12.3 Doing the Regression in R 00:00:00
12.4 Geometrical Representation 00:00:00
12.5 How to Interpret the Regression 00:00:00
12.6 R-Squared 00:00:00
12.7 The Linear Regression Model 00:00:00

Course Reviews

N.A

ratings
  • 5 stars0
  • 4 stars0
  • 3 stars0
  • 2 stars0
  • 1 stars0

No Reviews found for this course.

PRIVATE COURSE
  • PRIVATE
  • 1 week, 3 days
0 STUDENTS ENROLLED
    Copyright @2019