Business Mathematics and Statistics Coaching In Noida

Business Mathematics and Statistics Coaching In Noida

Matrices: Definition of a matrix. Types of matrices. Algebra of matrices. Applications of matrices operations for solution to simple business and economic problems. Calculation of values of determinants up to third order. Finding inverse of a matrix through determinant method. Solution of system of linear equation up to three variables.

Differential Calculus: Mathematical functions and their types – linear, quadratic, polynomial. Concepts of limit, and continuity of a function. Concept of differentiation. Rules of differentiation – simple standard forms. Applications of differentiation – elasticity of demand and supply. Maxima and Minima of functions (involving second or third order derivatives) relating to cost, revenue and profit.

Basic Mathematics of Finance: Simple and compound interest. Rates of interest – nominal, effective and continuous – and their inter-relationships. Compounding and discounting of a sum using different types of rates.

Uni-variate Analysis Measures of Central Tendency including Arithmetic mean, Geometric mean and Harmonic mean: properties and applications; Mode and Median. Partition values - quartiles, deciles, and percentiles. Measures of Variation: absolute and relative. Range, quartile deviation and mean deviation; Variance and Standard deviation: calculation and properties.

Bi-variate Analysis Simple Linear Correlation Analysis: Meaning, and measurement. Karl Pearson's co-efficient and Spearman's rank correlation. Simple Linear Regression Analysis: Regression equations and estimation. Relationship between correlation and regression coefficients.

Time-based Data: Index Numbers and Time Series Analysis Meaning and uses of index numbers; Construction of index numbers: Aggregative and average of relatives – simple and weighted, Tests of adequacy of index numbers, Construction of consumer price indices. Components of time series; additive and multiplicative models; Trend analysis: Finding trend by moving average method and Fitting of linear trend line using principle of least squares.

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