Course code

INFO 14012

Key Facts

Mathematics for Computing and Data Analysis (SPSS)

Current Students

To access your official course details for the year you started your Diploma, please visit the handbook

Course Overview

The purpose of this course is to develop an overall understanding of basic mathematical principles required to understand computing concepts and data analysis using SPSS software.

Course Content

Mathematical Preliminaries

Main branches of mathematics, Basic mathematical terms, Mathematical notations using BODMAS, Number Systems, Exponents, Monomials, Binomials, Trinomials, Polynomials, and Polynomial reversal (factoring), Types of equations, Gradient, Intercept, & Intersect, Rectangular coordinate system, Mathematical modeling Simultaneous equations.

Matrices and Business Applications

Matrix, Null Matrices, Augmented matrices, Solve matrices: Gaussian elimination method, Cremer’s rule

Calculus

Calculus and its branches, Pre-calculus (including; one-sided and general), algebraic rules, rules in differential calculus (including; constant, power, sum/difference, product, quotient, and chain), higher-order derivatives, basic rules of Integral calculus, Calculus in Practice.

quantitative Data Analysis- Part I

Scales of the variables, Data cleaning in conducting quantitative analysis, univariate, bivariate, and multivariate data analysis techniques, Theoretical assumptions underlying univariate, bivariate, and multivariate analysis techniques, descriptive statistics, graphical representation, display interpretation.

Quantitative Data Analysis- Part II

Assumptions of bivariate analysis, bivariate analysis, missing data and non-missing data situations, reliability analysis, parametric and non-parametric bivariate statistics, multivariate statistics.