Course Name Code Semester T+U Hours Credit ECTS
Engineering Statistics-II ENM 206 4 4 + 0 4 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Course Coordinator Dr.Öğr.Üyesi GÜLTEKİN ÇAĞIL
Course Lecturers Dr.Öğr.Üyesi GÜLTEKİN ÇAĞIL, Dr.Öğr.Üyesi TİJEN ÖVER ÖZÇELİK,
Course Assistants
Course Category
Course Objective

Introducing students to the probability theory and basic statistical sampling methods

Course Content

Statistical distributions, point and interval estimation, one sample hypothesis tests, two sample hypothesis tests

# Course Learning Outcomes Teaching Methods Assessment Methods
1 Student will be able to use the concepts of sample mean, sample variance, population mean, population variance and Central Limit Theorem Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
2 Student will be able to explain the general concepts of estimating the parameters of a population or a probability distribution Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
3 Student will be able to construct confidence intervals on the mean of a normal distribution, using appropriate distribution method Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Simulation, Testing, Homework,
4 Student will be able to construct confidence intervals on a population proportion Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Simulation, Testing, Homework,
5 Student will be able to structure engineering decision-making problems as hypothesis tests Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
6 Student will be able to test hypotheses on the mean of a normal distribution using appropriate test procedure Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
7 Student will be able to test hypotheses on a population proportion Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
8 Student will be able to test hypotheses on the difference in means of two normal distributions using appropriate test procedure Lecture, Question-Answer, Discussion, Drilland Practice, Testing, Homework,
9 Student will be able to test hypotheses on the ratio of the variances of two normal distributions Discussion, Drilland Practice, Demonstration, Lecture, Question-Answer, Testing, Homework,
10 Student will be able to test hypotheses on the difference in two population proportions Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
11 Student will be able to use the P-value approach for making decisions in hypotheses tests Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
12 Student will be able to compute power, beta, and make sample size selection decisions for tests on means, variances, and proportions Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
13 Student will be able test significance of the hypothesis by Analysis of Variance Approach (ANOVA) Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
14 Student will be able to determine the relations between dependent and independent variables and use the regression model to make prediction of future observations. Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
15 Student will be able to test and construct the coefficients of the regression model. Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Homework, Testing,
Week Course Topics Preliminary Preparation
1 Probability Distributions, Discrete Probability Distributions, Bernoulli and Binomial Distributions
2 Sampling distributions and Estimation-II
3 Sampling distributions and Estimation-III
4 Normal, Standard Normal, Log Normal Distribution, Introduction of Normal Distribution Table
5 Gamma, Weibull Distribution, Normal Distribution Approach to Binomial Distribution
6 Sampling Distributions, Sampling Distribution of Means, Central Limit Theorem
7 Hypothesis tests: one sample-II
8 Sampling Distribution of Variances, Presentation of Chi Square Table, Presentation of F Table
9 Statistical Estimation and Confidence Intervals, Confidence Interval of Means, Confidence Interval of Ratios, Presentation of Table t
10 Confidence interval of difference of two mass means, Confidence interval of difference of two mass means in conjugate samples, Confidence interval of difference between two mass ratios, Confidence interval of variance ratios
11 Determination of sample size and estimation of sample size and mean and proportions
12 Hypothesis Testing, Errors in Hypothesis Testing, Stages of Hypothesis Testing
13 Hypothesis Testing of Mass Mean, Alpha and Beta Error, Hypothesis Testing of Small Samples, Proportions Hypothesis Testing
14 Multiple linear regression models
Resources
Course Notes <p>http://www.gultekincagil.edu.tr</p> <p>lecture notes on this link</p>
Course Resources

1. Serper, Ö., “Applied Statistics - 1”, Ezgi Bookstore, 2014.
2. Serper, Ö., “Applied Statistics - 2”, Ezgi Kitapevi, 2014.
3. Ersöz, F., Ersöz, T., “Statistical Data Analysis with IBM SPSS, Elit Publications, 2018
4. Arslan, İ., Statistical Programming with R ”, Pusula Publishing and Communication, 2018
5. Topal, B., Probability Statistics Lecture Notes

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. X
2 Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. X
3 Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods. X
4 Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. X
5 Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. X
6 Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually
7 Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language
8 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology
9 Engineering graduates with well-structured responsibilities in profession and ethics
10 Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development. X
11 Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions.
Evaluation System
Semester Studies Contribution Rate
1. Ödev 30
1. Ara Sınav 50
1. Kısa Sınav 10
2. Kısa Sınav 10
Total 100
1. Final 50
1. Yıl İçinin Başarıya 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 5 5
Assignment 6 8 48
Performance Task (Laboratory) 1 5 5
Final examination 1 5 5
Total Workload 159
Total Workload / 25 (Hours) 6.36
dersAKTSKredisi 6