**Introduction to Analytics(Associate Analytics - I)**

**Unit I: Introduction to Analytics and R programming**

After the completion of this unit students can learn basics of R language and learn how to use R to handle the files with data. Students can understand different files formats like .csv and .txt and learn how access these files.

**Unit II: Summarizing Data & Revisiting Probability**

At the end of this unit students will lern how to summarize data with R and learn how to work on probability using R and learn how to plot graphs easily. Also, here students will learn Expected, Bivariate, Random variables and Central Limit theorem. In this unit students can learn soft skills on how to Work effectively with Colleagues when they are working in an Organization.

By the end of the unit the students will learn NoSQL databases and learn how to connect R language to NoSQL databases. Students also will learn how towork on Excel and R integration with R connector.

**Unit IV: Correlation and Regression Analysis**

By the end of the unit students will learn Regression Analysis, Assumptions of OLS Regression and Regression Modelling. Students will also learn how to find relationship between two variables using Regression and Correlation using R and learn Forecasting, Heteroscedasticity, Autoicorrelation and Multiple Regression etc.

**Unit V: Understand the Verticals - Engineering, Financial and others (NOS 9002)**

By the end of this unit students will be able to solve Engineering and Manufacturing issues and learn how to create Business Models. Students can also understand Samart Utilities, Production Lines, Automotive, Technology etc.

**Text Books:**

**1. **** **Student’s Handbook for**Associate Analytics.**

**Downloads:**

**Module 1 (Introduction to Analytics)**

**Reference Books:**

**1. **** **Introduction to Probability and Statistics Using R, ISBN: 978-0-557-24979-4, is a textbook written for an undergraduate course in probability and statistics.

**2. **** **An Introduction to R, by Venables and Smith and the R Development Core Team. This may be downloaded for free from the R Project website (http://www.r-project.org/, see Manuals). There are plenty of other free references available from the R Project website.

**3. **** **Montgomery, Douglas C., and George C. Runger, Applied statistics and probability for engineers. John Wiley & Sons, 2010

**4. **** **The *Basic Concepts of Time Series Analysis*.http://anson.ucdavis.edu/~azari/sta137/AuNotes.pdf

**5. **** **Time Series Analysis and Mining with R,Yanchang Zhao.

**WEB REFERENCES:**

**1. **** **https://www.jigsawacademy.com

2. https://www.edx.org

3. www.tutorialspoint.com/r/

4. www.cyclismo.org/tutorial/R/

5. https://www.programiz.com/r-programming