Data analysis with R MasterclassOutcome : Good knowledge in R and statistical analysis by the end of the workshop.

Data science in being integrated in business every day. Now is the time that get in line with the data science era. When your data is presented in an excel sheet or in the database , it is difficult to gain inference from this data to help your business. Whether you are working in marketing, sales ,supply chain,  human resources or finance.

This is the first workshop of three series masterclass that begins with :

  • Data analysis with R
  • Machine learning with R
  • Visualization with R

Module 1 : Introduction to R and Data.

In this module , we will start working and practicing basic R language such as defining data types , rows in the data , getting specific rows or columns and making simple mathematical calculations inside R. Throughout the workshop we will work on one dataset and start analyzing its data step by step.

We will also know how to summarize our data to get important measures such as the average , median , minimum and maximum.

Outcomes of the first module :

  • Data types familiarity.
  • Importing data into R.
  • Data filtering in R.

Module 2 : Exploratory data analysis in R

You will learn how to create graphical and numerical summaries of two categorical variables such as creating Barcharts , summarizing and calculating percentage. We will also get familiar with Histograms and how they can be helpful to know the distribution of our Data .

we will also make box plots that are great tools to define outliers as well as density plots to know the center and spread of your data.

Outcomes of the first module :

  • Numerical and Categorical data in R.
  • Plotting in R for analysis.
  • Manipulation of Data for statistical analysis.

Module 3 : Statistical Data analysis.

Eventually , data analysis is about understanding the relationships between variables , in this module we will use regression analysis and collinearity analysis to understand the relation between our variables .

We will discuss how outliers can affect the results of a linear regression model and how we can deal with them.

We will also learn how to fit a linear model , understand its coefficients and use them to predict data for the use in the future.

Outcome of the third Module :

  • Correlation among variables.
  • Regression analysis .
  • Fitting regression models

Prediction using regression