Bachelor of Commerce (B.Com) with a Focus on Statistics
Year 1: Foundation Courses*
*Semester 1:*
- *Financial Accounting I*: Basics of accounting principles, journal entries, and balance sheets.
- *Business Economics I*: Microeconomics concepts (demand, supply, market structures).
- *Business Mathematics I*: Algebra, calculus, and matrices.
- *Principles of Management*: Organizational behaviour and management theories.
- *Business Communication*: Report writing, presentations, and professional communication.
- *Environmental Studies*: Sustainability and business ethics.
*Semester 2:*
- *Financial Accounting II*: Advanced accounting (partnerships, cash flow statements).
- *Business Economics II*: Macroeconomics (GDP, inflation, fiscal policy).
- *Business Mathematics II*: Probability, permutations, and financial mathematics.
- *Business Statistics I*: Descriptive statistics, data visualization, and basic probability.
- *Computer Fundamentals*: Introduction to Excel for data handling.
*Year 2: Intermediate Courses*
*Semester 3:*
- *Corporate Accounting*: Company financial statements and mergers.
- *Cost Accounting*: Costing methods (job, process, activity-based).
- *Business Statistics II*: Inferential statistics (sampling, hypothesis testing, t-tests, chi-square).
- *Business Law*: Contract and commercial law basics.
*Semester 4:*
- *Income Tax Law*: Tax computation and filing procedures.
- *Auditing*: Audit principles and practices.
- *Statistical Methods*: Regression analysis, correlation, ANOVA.
- *Entrepreneurship*: Business planning and startup strategies.
*Year 3: Advanced Specialization*
*Semester 5:*
- *Management Accounting*: Budgeting and variance analysis.
- *Advanced Statistical Methods*: Time series analysis, index numbers, multivariate techniques.
- *Elective I* (Choose one):
- Econometrics: Statistical methods in economic data.
- Marketing Research: Survey design and data analysis.
- Business Analytics: Predictive modeling and data mining.
- *Statistical Software Lab*: Hands-on training in R/Python/SPSS for data analysis.
*Semester 6:*
- *Financial Management*: Capital budgeting and risk management.
- *Applied Statistics*: Case studies in business decision-making.
- *Elective II* (Choose one):
- Operations Research: Linear programming, optimization.
- Actuarial Science: Risk assessment in insurance/finance.
- Data Visualization: Tools like Tableau/Power BI.
- *Project Work/Dissertation*: Real-world statistical analysis project (e.g., market trend forecasting, financial data modelling).
*Practical Components*
- *Software Training*: Labs on Excel, R, Python, or SPSS.
- *Case Studies*: Application of statistical tools in business scenarios.
- *Internships/Projects*: Industry collaborations for hands-on experience.
*Elective Options*
- Data Analysis & Interpretation
- Financial Econometrics
- Risk Management
- Digital Marketing Analytics
- Supply Chain Statistics