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Course Objectives: This course aims to provide hands-on experience in data analytics using R programming, enabling students to process, visualize, and statistically analyze data to support data-driven decision-making in business environments.
Course Outcomes: Upon completion of this course, students will be able to:
CO1. Explain the fundamental concepts of data analytics, types of data, and key characteristics relevant to analytical tasks.
CO2. Demonstrate proficiency in R programming, including variables, control statements, and basic data structures.
CO3. Read, manipulate, and visualize diverse data sets using R for exploratory data analysis and presentation.
CO4. Apply statistical methods and modeling techniques in R, including regression, ANOVA, and time series analysis.
This Lab would be based on the course BBA-CAM 303: Data Analytics with R Programming
1. Introduction to R Studio Environment: Installation and configuration, Creating and executing R scripts, Console and environment operations
2. Basic Syntax and Commands in R: Variables, data types, operators, and keywords, Scope of variables, User input and output functions
3. Control Structures and Functions: Conditional statements: if, if-else, switch, Loops: for, while, repeat, Functions: built-in and user-defined
4. Working with Data Structures: Vectors, lists, matrices, arrays, and data frames, Data manipulation using indexing and functions
5. Reading and Importing Data: Loading data from CSV, Excel, JSON, XML, and databases, Web data import techniques
6. Data Visualization in R: Bar charts, line graphs, scatterplots, pie charts, Boxplots, histograms, and custom visualizations using libraries
7. Descriptive Statistics and Distributions: Mean, median, mode, variance, standard deviation.
Frequency distribution and data summaries. Normal and binomial distributions
8. Statistical Analysis Techniques: One-way and Two-way ANOVA. Correlation and regression analysis (linear, multiple, logistic). Time series analysis and forecasting
9. Mini Project: Exploratory Data Analysis (EDA) on a real-world dataset. Visualizing trends and interpreting outcomes using statistical tools in R
As per the latest IPU syllabus — cross-check electives with your college.
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Data Analytics using R Programming Lab (BBA-CAM 325) is a semester 5 subject in the IPU BBA BBA (Computer Aided Management) (BBA-CAM) curriculum.
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