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Course Code: 
MATH 134
Course Period: 
Spring
Course Type: 
Core
P: 
3
Lab: 
0
Credits: 
3
ECTS: 
5
Course Language: 
İngilizce
Course Content: 

Limits, compound interest, continuity. Derivative and rules of differentiation. Exponential and logarithmic functions. Extremal values, trends, elasticity of demands. Linear programming and multiple optimum solutions. Simplex method and optimization. Applications to compound interest, present value, annuities, amortization of loans. Applications to modeling in economics and business. Introduction to probability and statistics.

Course Methodology: 
1: Lecture
Course Evaluation Methods: 
A: Written examination

Vertical Tabs

Course Learning Outcomes

Learning Outcomes

Teaching Methods

Assessment Methods

1) Learns the foundational notions of Calculus: limit and continuity.

1

A

2) Learns the notion of derivative through limit, learns properties of derivation and the chain rule.

1

A

3) Learns implicit differentiation.

1

A

4) Learns sketching of curves in cartesian coordinates, can do extremum calculations. Learns the notion of concavity. Learns: 1st derivative test, 2nd derivative test and the applications of the notions maxima and minima

1

A

5) Solves compound interest questions and learns the notion of present value.

1

A

6) Learns basic counting techniques and can do elemantary probability and statistical calculations.

1

A

Course Flow

Week

Topics

Study Materials

1

 Chapter 10: Limit and Continuity

  Limits

10.1, 10.2

2

  Continuity

10.3

3

 Chapter 11: Differentiation

  The Derivative, Rules of Differentiation

11.1, 11.2

4

  The product rule and the Quetient rule, The chain rule

11.4, 11.5

5

 Chapter 4: Exponential and Logarithmic  Functions

  Exponential Functions, Logarithmic Functions

4.1, 4.2

6

  Properties of Logarithms, Logarithmic and Exponential Equations

4.3, 4.4

7

  Chapter 12: Additional Differentiation Topics

  Derivative of logarithmic functions, Derivatives of Exponential  Functions

12.1, 12.2

8

 Implicit Differentiation, Logarithmic Differentiation

12.4, 12.5

9

 Chapter 13: Curve Sketching

  Relative Extreme Absolute Extrema on Closed Interval, Concavity         

13.1, 13.2, 13.3

10

 The Second Derivative Test, Asymptotes, Applied Maxima and Minima

13.4, 13.5, 13.6

11

  Chapter 5: Mathematics of Finance

  Compound Interest, Present Value

5.1, 5.2, 5.4

12

 Interest Compounded Continuously

5.3

 

13

 Chapter 8: Introduction to Probability and Statistics

  Basic Counting Principle and Permutations,  Combinations and Other Counting Principles

8.1, 8.2

14

  Sample Spaces and Events, Probability

8.3, 8.4

Recommended Sources

Textbook

Introductory Mathematical

Analysis, 13th Edition by Ernest Haeussler, Richard S. Paul, Richard Wood, Pearson Prentice Hall

Additional Resources

 

 

Material Sharing

Documents  
Assignments  
Exams  

Assessment

IN-TERM STUDIES

NUMBER

PERCENTAGE

Mid-terms

1

100

Quizzes

 

 

Assignments

 

 

Total

 

100

CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE

 

60

CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE

 

40

Total

 

100

 

COURSE CATEGORY

 

Course’s Contribution to Program

No

Program Learning Outcomes

Contribution

1

2

3

4

5

 

1

The ability to make computation on the basic topics of mathematics such as limit, derivative, integral, logic, linear algebra and discrete mathematics which provide a basis for the fundamenral research fields in mathematics (i.e., analysis, algebra, differential equations and geometry)

 

 

 

 

 

 

2

Acquiring fundamental knowledge on fundamental research fields in mathematics

 

 

 

 

 

 

3

Ability form and interpret the relations between research topics in mathematics

 

 

 

 

 

 

4

Ability to define, formulate and solve mathmatical problems

 

 

 

 

 

 

5

Consciousness of professional ethics and responsibilty

 

 

 

 

 

 

6

Ability to communicate actively

 

 

 

 

 

 

7

Ability of self-development in fields of interest

 

 

 

 

 

 

8

Ability to learn, choose and use necessary information technologies

 

 

 

 

 

 

9

Lifelong education

 

 

 

 

 

 

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities

Quantity

Duration
(Hour)

Total
Workload
(Hour)

Course Duration (14x Total course hours)

14

3

42

Hours for off-the-classroom study (Pre-study, practice)

14

4

56

Mid-terms (Including self study)

1

12

12

Final examination (Including self study)

1

15

15

Total Work Load

 

 

125

Total Work Load / 25 (h)

 

 

5

ECTS Credit of the Course

 

 

5

1