Statistical Applications In Engineering
Metallurgical and Materials Engineering
Faculty of Engineering
First Cycle (Bachelor's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Statistical Applications In Engineering | MMT435 | Elective | Bachelor's degree | 2 | Fall | 2 |
Name of Lecturer(s)
Associate Prof. Dr. Şeyda POLAT
Assistant Prof. Dr. Barış AKSU
Learning Outcomes of the Course Unit
1) Explaning the statistical methods, objectives, stages, basic concepts.
2) Collecting, organizing and presenting the data in statistics.
3) Explaining the central value measures and analytical averages.
4) Calculating the dispersion measures, variation and standard values.
5) Explaining the binomial, Poisson, hypergeometric and normal distributions.
6) Defining the sampling theory and calculating the standard error.
7) Applying the hypothesis tests.
8) Explaining the estimates based on small samples.
9) Defining the Chi-square distribution.
10) Explaining the F distribution and analyzing the variance.
11) Making the simple regression and correlation.
12) Making the multiple regression and correlation.
13) Explaining the Weibull statistics.
Program Competencies-Learning Outcomes Relation
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| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
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| 1 | Low | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 2 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 3 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 4 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 5 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 6 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 7 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 8 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 9 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 10 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 11 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 12 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
| 13 | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Mathematics
Course Contents
Statistical Methods; Objectives, Stages, Basic Concepts Collection, Reduction and Presentation of Data in Statistics Central Value Measures, Analytical Averages Dispersion Measures, Variation, Standard Values Binomial, Poisson, Hypergeometric and Normal Distributions Sampling Theory, Standard Error Hypothesis Tests Estimates Based on Small Samples and Hypothesis Tests Mid-Term Exam Chi-square Distribution FDistribution and Analysis of Variance (ANOVA) Simple Regression and Correlation Multiple Regression and Correlation Weibull Statistics
Weekly Schedule
1) Basic concepts of statistics and probability2) Descriptive statistics
3) Basic concepts of probability
4) Probability distributions
5) Normal distribution
6) Sampling distribution and central limit theorem
7) Sampling
8) Midterm examination/Assessment
9) Point estimation and confidence intervals
10) Hypothesis tests - I
11) Hypothesis tests - II
12) Non-Parametric tests
13) Analyse of variance
14) Correlation and regression
15) Time series
16) Final examination
Recommended or Required Reading
1- Özer SERPER, Uygulamalı İstatistik 1-2, Ezgi Yayınevi
2- Enis Sınıksaran, Teori ve Uygulamalarıyla İstatstiksel Yöntemler, Türkmen Kitabevi
3- Paul Newbold (Çev:Ümit Şenesen), İstatistik, Literatür Yayınları
4- M.R.Spiegel, L.J. Stephans (Çev: Alptekin Esin, Salih Çelebioğlu), İstatistik, Nobel Yayın
5- J.Neter, W.Wasserman, G.A. Whitmore, Applied Statistics, Allyn and Bacon
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Modelling
4) Group Study
5) Lab / Workshop
6) Problem Solving
7) Project Based Learning
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
40% |
|---|---|
Contribution of Final Examination to Course Grade |
60% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required