- Type
- Official handout
- Course
- MTH302 Business Mathematics & Statistics
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- PDF 5 MB
- Updated
- 23 Oct 2026
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TABLE OF CONTENTS :
Lesson 1 :COURSE OVERVIEW ....................................................................................................... 3 Lesson 2 :APPLICATION OF BASIC MATHEMATICS .................................................................... 12 Lesson 3 :APPLICATION OF BASIC MATHEMATICS .................................................................... 22 Lesson 4 :APPLICATION OF BASIC MATHEMATICS .................................................................... 29 Lesson 5 :APPLICATION OF BASIC MATHEMATICS .................................................................. 399 Lesson 6 :APPLICATION OF BASIC MATHEMATICS .................... Error! Bookmark not defined.8 Lesson 7 :APPLICATION OF BASIC MATHEMATICS .................... Error! Bookmark not defined.9 Lesson 8 :COMPOUND INTEREST............................................................................................... 709 Lesson 9 :COMPOUND INTEREST............................................................................................... 776 Lesson 10:MATRICES.................................................................................................................... 809 Lesson 11: MATRICES................................................................................................................... 854 Lesson 12 :RATIO AND PROPORTION .......................................................................................... 94 Lesson 13 :MATHEMATICS OF MERCHANDISING ................................................................... 1009 Lesson 14 :MATHEMATICS OF MERCHANDISING ..................................................................... 105 Lesson 15 :MATHEMATICS OF MERCHANDISING ................................................................. 11211 Lesson 16 :MATHEMATICS OF MERCHANDISING ................................................................. 12120 Lesson 17 :MATHEMATICS FINANCIAL MATHEMATICS........................................................ 12524 Lesson 18 :MATHEMATICS FINANCIAL MATHEMATICS........................................................ 13029 Lesson 19 :PERFORM BREAK-EVEN ANALYSIS .................................................................... 13433 Lesson 20 :PERFORM BREAK-EVEN ANALYSIS .................................................................... 14241 Lesson 21 :PERFORM LINEAR COST-VOLUME PROFIT AND BREAK-EVEN ANALYSIS.... 14746 Lesson 22 :PERFORM LINEAR COST-VOLUME PROFIT AND BREAK-EVEN ANALYSIS.... 15049 Lesson 23 :STATISTICAL DATA REPRESENTATION................................................................ 1587 Lesson 24 :STATISTICAL REPRESENTATION ........................................................................ 16362 Lesson 25 :STATISTICAL REPRESENTATION ........................................................................ 17170 Lesson 26 :STATISTICAL REPRESENTATION ........................................................................ 18079 Lesson 27 :STATISTICAL REPRESENTATION ........................................................................ 18988 Lesson 28 :MEASURES OF DISPERSION................................................................................ 20099 Lesson 29 :MEASURES OF DISPERSION.................................................................................... 207 Lesson 30 :MEASURE OF DISPERASION.................................................................................... 217 Lesson 31 :LINE FITTING .......................................................................................................... 22524 Lesson 32 :TIME SERIES AND.................................................................................................. 24039 Lesson 33 :TIME SERIES AND EXPONENTIAL SMOOTHING................................................ 25352 Lesson 34 :FACTORIALS........................................................................................................... 26059 Lesson 35 :COMBINATIONS ......................................................................................................... 269 Lesson 36 :ELEMENTARY PROBABILITY................................................................................ 27675 Lesson 37:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .................................................................................................................................27978 Lesson 38:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .................................................................................................................................28483 Lesson 39:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .................................................................................................................................29796 Lesson 40:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .....................................................................................................................................302 Lesson 41: ESTIMATING FROM SAMPLES: INFERENCE .......................................................... 314 Lesson 42 :ESTIMATING FROM SAMPLE : INFERENCE............................................................ 320 Lesson 43 :HYPOTHESIS TESTING: CHI-SQUARE DISTRIBUTION.......................................... 325 Lesson 44 :HYPOTHESIS TESTING : CHI-SQUARE DISTRIBUTION......................................... 328 Lesson 45 :PLANNING PRODUCTION LEVELS: LINEAR PROGRAMMING............................... 335
The title of this course is “BUSINESS MATHEMATICS AND STATISTICS”.
Instructor’s Resume
The instructor of the course is Dr. Zahir Fikri who holds a Ph.D. in Electric Power Systems Engineering from the Royal Institute of Technology, Stockholm, Sweden. The title of Dr. Fikri’s thesis was “Statistical Load Forecasting for Distribution Network Planning”.
Objective
The purpose of the course is to provide the student with a mathematical basis for personal and business financial decisions through eight instructional modules. The course stresses business applications using arithmetic, algebra, and ratio-proportion and graphing. Applications include payroll, cost-volume-profit analysis and merchandising mathematics. The course also includes Statistical Representation of Data, Correlation, Time Series and Exponential Smoothing, Elementary Probability and Probability Distributions. This course stresses logical reasoning and problem solving skills.
Access to Microsoft Excel software is required for the course.
Course Outcomes
Successful completion of this course will enable the student to: 1. Apply arithmetic and algebraic skills to everyday business problems. 2. Use ratio, proportion and percent in the solution of business problems. 3. Solve business problems involving commercial discount, markup and markdown. 4. Solve systems of linear equations graphically and algebraically and apply to cost volumeprofit analysis. 5. Apply Statistical Representation of Data, Correlation, Time Series and Exponential Smoothing methods in business decision making 6. Use elementary probability theory and knowledge about probability distributions in developing profitable business strategies.
Unit Outcomes Resources/Tests/Assignments
Successful completion of the following units will enable the student to apply mathematical methods to business problems solving.
Required Student Resources (Including textbooks and workbooks)
Text: Selected books on Business Mathematics and Statistics.
Optional Resources
Handouts supplied by the professor. Instructor’s Slides Online or CD based learning materials.
Prerequisites
The students are not required to have any mathematical skills. Basic knowledge of Microsoft Excel will be an advantage but not a requirement.
Evaluation
In order to successfully complete this course, the student is required to meet the following evaluation criteria: Full participation is expected for this course All assignments must be completed by the closing date. Overall grade will be based on VU existing Grading Rules. All requirements must be met in order to pass the course.
COURSE MODULES
The following are the main modules of this course:
Module 1
Overview (Lecture 1) Perform arithmetic operations in their proper order (Lecture 2) Convert fractions their percent and decimal equivalents. (Lecture 2) Solve for any one of percent, portion or base, given the other two quantities. (Lecture 2) Using Microsoft Excel (Lecture 2) Calculate the gross earnings of employees paid a salary, an hourly wage or commissions. (Lecture 3) Calculate the simple average or weighted average given a set of values. (Lecture 4) Perform basic calculations of the percentages, averages, commission, brokerage and discount (Lecture 5) Simple and compound interest (Lecture 6) Average due date, interest on drawings and calendar (Lecture 6)
Module 2
Exponents and radicals (Lecture 7) Solve linear equations in one variable (Lecture 7) Rearrange formulas to solve for any of its contained variables (Lecture 7) Solve problems involving a series of compounding percent changes (Lecture 8) Calculate returns from investments (Lecture 8) Calculate a single percent change equivalent to a series of percent changes (Lecture 8) Matrices ( Lecture 9) Ratios and Proportions ( Lecture10) Set up and manipulate ratios ( Lecture11) Allocate an amount on a prorata basis using proportions ( Lecture11)
Module 3
Discounts ( Lectures 12) Mathematics of Merchandising ( Lectures 13-16)
Module 4
Applications of Linear Equations ( Lecture 17-18) Break-even Analysis ( Lecture 19-22)
Module 5
Statistical data ( Lectures 23) Measures of central tendency ( Lectures 24-25) Measures of dispersion and skewness ( Lectures 26-27)
Module 6
Correlation ( Lectures 28-29) Line Fitting (Lectures 30-31) Time Series and Exponential Smoothing ( Lectures 31-33)
Module 7
Factorials ( Lecture 34) Permutations and Combinations ( Lecture 34) Elementary Probability ( Lectures 35-36) Patterns of probability: Binomial, Poisson and Normal Distributions ( Lecture 37-40)
Module 8
Estimating from Samples: Inference ( Lectures 41-42) Hypothesis testing : Chi-Square Distribution ( Lectures 43-44) Planning Production Levels: Linear Programming (Lecture 45)
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