What you'll learn

Master practical business mathematics and data analysis skills to solve real-world business problems, make smarter decisions, and build career-ready analytical abilities for the modern business world. After completion of the course, students will be able to: 1. Apply mathematical techniques to solve business problems. 2. Analyze financial and statistical data effectively. 3. Interpret business trends using statistical tools. 4. Use correlation and regression for predictive analysis. 5.Develop quantitative decision-making skills for business applications.

  • Introduction to matrices, uses of matrices in business and economics, types of matrices.
  • Addition, subtraction, scalar multiplication and equality of matrices.
  • Rules and methods of matrix multiplication up to 3×3 matrices.
  • Concept of determinant, minors and cofactors of matrices.
  • Adjoint and inverse of matrices with business applications.
  • Concept of ratio, percentage and business calculations.
  • Direct proportion and its practical applications in business.
  • Concept and applications of inverse variation.
  • Meaning, properties and applications of arithmetic progression.
  • Meaning, properties and applications of geometric progression.
  • Application of AP and GP in installment, sales and growth calculations.
  • Concept, formula and applications of simple interest.
  • Compound interest and its computation methods.
  • Interest compounded continuously and related calculations.
  • Effective interest rate and comparison of borrowing options.
  • Meaning and types of statistical data: univariate, bivariate and multivariate.
  • Calculation and interpretation of arithmetic mean.
  • Concept and computation of median and mode.
  • Computation and applications of combined mean.
  • Business applications of measures of central tendency.
  • Concepts and computation of range and quartile deviation.
  • Meaning and computation of mean deviation.
  • Concept and calculation of standard deviation.
  • Relative measure of dispersion and comparison of datasets.
  • Concept and interpretation of skewness in data distribution.
  • Meaning, types and uses of correlation in business.
  • Calculation and interpretation of Pearson’s coefficient.
  • Spearman’s rank correlation and applications.
  • Introduction to regression analysis and regression equations.
  • Properties of regression coefficients and relation between correlation and regression.

Dr. Devinder Kumar
Assistant Professor

Dr. Devinder Kumar Ph.D., M.Phil. in Economics Assistant Professor, Economics Mittal School of Business (MSB), Lovely Professional University (LPU) Dr. Devinder Kumar is an academician and researcher with more than 4 years of teaching experience in the field of Economics, Business Mathematics, and Quantitative Techniques. He specializes in Mathematical Economics, Statistics for Business Studies, Business Mathematics, and Data Analysis. He is recognized for his engaging and application-oriented teaching methodology that connects quantitative concepts with real-world business and economic scenarios. His sessions focus on enhancing students’ analytical thinking, problem-solving abilities, and data-driven decision-making skills required in today’s competitive business environment. Dr. Kumar is also actively involved in research, academic mentoring, and Ph.D. guidance. His research interests include financial studies, business analytics, development economics, and applied quantitative research. Through his practical and interactive approach, he aims to make quantitative subjects more accessible, skill-oriented, and career-focused for learners.