MTH302 Highlighted Handouts by Haalim

Business Mathematics & Statistics (MTH 302) VU

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.....................................................................39 Lesson 6 :APPLICATION OF BASIC MATHEMATICS.....................................................................47 Lesson 7 :APPLICATION OF BASIC MATHEMATICS.....................................................................57 Lesson 8 :COMPOUND INTEREST..................................................................................................66 Lesson 9 :COMPOUND INTEREST..................................................................................................72 Lesson 10:MATRICES ......................................................................................................................75 Lesson 11: MATRICES .....................................................................................................................80 Lesson 12 :RATIO AND PROPORTION ...........................................................................................90 Lesson 13 :MATHEMATICS OF MERCHANDISING........................................................................95 Lesson 14 :MATHEMATICS OF MERCHANDISING......................................................................101 Lesson 15 :MATHEMATICS OF MERCHANDISING......................................................................107 Lesson 16 :MATHEMATICS OF MERCHANDISING......................................................................115 Lesson 17 :MATHEMATICS FINANCIAL MATHEMATICS ............................................................119 Lesson 18 :MATHEMATICS FINANCIAL MATHEMATICS ............................................................124 Lesson 19 :PERFORM BREAK-EVEN ANALYSIS.........................................................................128 Lesson 20 :PERFORM BREAK-EVEN ANALYSIS.........................................................................136 Lesson 21 :PERFORM LINEAR COST-VOLUME PROFIT AND BREAK-EVEN ANALYSIS ........140 Lesson 22 :PERFORM LINEAR COST-VOLUME PROFIT AND BREAK-EVEN ANALYSIS ........143 Lesson 23 :STATISTICAL DATA REPRESENTATION ..................................................................150 Lesson 24 :STATISTICAL REPRESENTATION.............................................................................155 Lesson 25 :STATISTICAL REPRESENTATION.............................................................................163 Lesson 26 :STATISTICAL REPRESENTATION.............................................................................171 Lesson 27 :STATISTICAL REPRESENTATION.............................................................................179 Lesson 28 :MEASURES OF DISPERSION ....................................................................................189 Lesson 29 :MEASURES OF DISPERSION ....................................................................................197 Lesson 30 :MEASURE OF DISPERASION ....................................................................................206 Lesson 31 :LINE FITTING...............................................................................................................212 Lesson 32 :TIME SERIES AND.......................................................................................................226 Lesson 33 :TIME SERIES AND EXPONENTIAL SMOOTHING.....................................................239 Lesson 34 :FACTORIALS ...............................................................................................................245 Lesson 35 :COMBINATIONS ..........................................................................................................254 Lesson 36 :ELEMENTARY PROBABILITY.....................................................................................261 Lesson 37:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .........................................................................................................263 Lesson 38:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .........................................................................................................267 Lesson 39:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .........................................................................................................277 Lesson 40:PATTERNS OF PROBABILITY: BINOMIAL, POISSON AND NORMAL DISTRIBUTIONS .........................................................................................................283 Lesson 41: ESTIMATING FROM SAMPLES: INFERENCE ...........................................................294 Lesson 42 :ESTIMATING FROM SAMPLE : INFERENCE.............................................................300 Lesson 43 :HYPOTHESIS TESTING: CHI-SQUARE DISTRIBUTION...........................................304 Lesson 44 :HYPOTHESIS TESTING : CHI-SQUARE DISTRIBUTION..........................................307 Lesson 45 :PLANNING PRODUCTION LEVELS: LINEAR PROGRAMMING ...............................314

MTH 302 · LECTURE 1 · COURSE TITLE

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)

End-Term Examination Note: The course modules are subject to change.

MARKING SCHEME

As per VU Rules