INDUSTRIAL ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
ECO2062 Applied Statistics Spring 3 0 3 6
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Assist. Prof. EMİNE ZEREN TAŞPINAR
Course Lecturer(s): Assist. Prof. EMİNE ZEREN TAŞPINAR
Assist. Prof. SERKAN YEŞİLYURT
Recommended Optional Program Components: None
Course Objectives: This course builds on ECO2061. The course's main objective is to understand statistical inference and its applications. Topics include sampling distributions, confidence interval estimations, and hypothesis testing with their applications in Excel.

Learning Outcomes

The students who have succeeded in this course;
• acquire the meaning of statistical inference and the scope of its practices.
• estimate a confidence interval for mean, variance, and proportion of one population and two populations, then run these estimations on Excel.
• do hypothesis testing about parameters from one population and two populations, then run these hypothesis testing on Excel.

Course Content

Sampling and Sampling Distributions

Sampling Distribution Properties

Point and Interval Estimates
Confidence Interval for population mean

Confidence Intervals for the
Population Proportion, π
Fundamentals of Hypothesis Testing: One-Sample Tests
Hypothesis Testing for Mean and Proportion
Two-Sample Tests for Mean

Two-Sample Tests for Proportion

One-Way Analysis of Variance

Two-Way Analysis of Variance

Chi-Square Tests and Nonparametric Tests

Introduction to Simple Linear Regression


Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction
2) Distributions of Sample Statistics, NCT6 Sampling from a Population Sampling Distributions of Sample Means
3) Distributions of Sample Statistics, NCT6 Sampling Distributions of Sample Means Sampling Distributions of Sample Proportions
4) Distributions of Sample Statistics, NCT6 Sampling Distributions of Sample Variances Excel applications
5) Confidence Interval Estimation: One Population, NCT7 Properties of Point Estimators Confidence Interval Estimation for the Mean of a Normal Distribution (Population Variance Known)
6) Confidence Interval Estimation: One Population, NCT7 Confidence Interval Estimation for the Mean of a Normal Distribution (Population Variance Unknown) Confidence Interval Estimation for Population Proportion
7) Confidence Interval Estimation: One Population, NCT7 Confidence Interval Estimation for the Variance of a Normal Distribution Sample-Size Determination: Large Populations Excel applications
8) Midterm Exam
9) Confidence Interval Estimation: Further Topics, NCT8 Confidence Interval Estimation of the Difference Between Two Normal Population Means Confidence Interval Estimation of the Difference Between Two Population Proportions Excel applications
10) Hypothesis Tests of a Single Population, NCT9 Concepts of Hypothesis Testing Tests of the Mean of a Normal Distribution:
11) Hypothesis Tests of a Single Population, NCT9 Tests of the Population Proportion Tests of the Variance of a Normal Distribution Excel applications
12) Two Populations Hypothesis Tests, NCT10 Tests of the Difference Between Two Normal Population Means: Tests of the Difference Between Two Normal Population Means, Independent Samples
13) Two Populations Hypothesis Tests, NCT10 Tests of the Difference Between Two Population Proportions Tests of the Equality of the Variances Between Two Normally Distributed Population Excel applications
14) Review

Sources

Course Notes / Textbooks: Statistics for Business and Economics, Paul Newbold, William L. Carlson and Betty Thorne, 9th Edition, Pearson. (NCT)
References: .

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Midterms 1 % 40
Final 1 % 60
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 16 3 48
Study Hours Out of Class 14 7 98
Midterms 1 2 2
Final 1 2 2
Total Workload 150

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Build up a body of knowledge in mathematics, science and industrial engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2) Identify, formulate, and solve complex engineering problems; select and apply proper analysis and modeling methods for this purpose.
3) Design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. The ability to apply modern design methods to meet this objective.
4) Devise, select, and use modern techniques and tools needed for solving complex problems in industrial engineering practice; employ information technologies effectively.
5) Design and conduct experiments, collect data, analyze and interpret results for investigating the complex problems specific to industrial engineering.
6) Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working independently.
7) Demonstrate effective communication skills in both oral and written English and Turkish. Writing and understanding reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instructions.
8) Recognize the need for lifelong learning; show ability to access information, to follow developments in science and technology, and to continuously educate him/herself. 3
9) Develop an awareness of professional and ethical responsibility, and behaving accordingly. Information about the standards used in engineering applications.
10) Know business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development. 4
11) Know contemporary issues and the global and societal effects of modern age engineering practices on health, environment, and safety; recognize the legal consequences of engineering solutions.
12) Develop effective and efficient managerial skills.