Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
3MATH230Statistics And Probability3+0+035

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program Mechatronics Engineering (English)
Mode of Delivery Face to Face
Type of Course Unit Compulsory
Objectives of the Course Basic Statistics and Probability subjects to teach.
Course Content Descriptive statistical measures, probability and probability operations, discrete and continuous probability distributions, inferential statistics
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator Asist Prof. Merve Doğruel Anuşlu
Name of Lecturers Asist Prof.Dr. ÖZER ÖZTÜRK
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources
Lectures, Question-Answer, Homework.
Dönem ödevi
Vize ve Final Sınavları

Course Category
Mathematics and Basic Sciences %30
Engineering %10
Social Sciences %0
Education %0
Science %0
Health %0
Field %60

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 40
Final examination 1 % 60
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 4 56
Mid-terms 1 10 10
Final examination 1 20 20
Total Work Load   Number of ECTS Credits 5 128

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Analytical and non-analytical mean methods can be calculated and interpreted.
2 Distribution measures can be calculated and interpreted.
3 Skewness and kurtosis can be calculated and interpreted.
4 Basic probability and probability operations are known.
5 Discrete and continuous probability distributions are known.
6 Basic statistics of numerical data can be calculated and interpreted.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 1. WHAT IS STATISTICS? 1.1. Introduction 1.2. Types of Statistics 1.3. Descriptive Statistics 1.4. Inferential Statistics 1.5. Types of Variables 1.6. Levels of Measurement Course Notes
2 2. DESCRIBING DATA: FREQUENCY 2.1 Distributions and Graphic Presentation 2.2 Relative Frequency Distribution 2.3 Graphic Presentation of a Frequency Distribution Course Notes
3 3. DESCRIBING DATA: NUMERICAL MEASURES 3.1 The Population Mean 3.2 The Sample Mean 3.3 Properties of the Arithmetic Mean 3.4 The Weighted Mean 3.5 The Median 3.6 The Mode 3.7 The Geometric Mean Course Notes
4 3.8 Why Study Dispersion? 3.9 Measures of Dispersion 3.9.1 Range 3.9.2 Mean Deviation 3.9.3 Variance and Standard Deviation 3.10 Chebyshev's Theorem 3.11 The Empirical Rule Course Notes
5 4. DESCRIBING DATA: DISPLAYING AND EXPLORING DATA 4.1 Dot Plots 4.2 Quartiles, Deciles, and Percentiles 4.3 Box Plots 4.4 Skewness 4.5 Describing the Relationship between Two Variables Course Notes
6 5. A SURVEY OF PROBABILITYCONCEPTS 5.1 What Is a Probability? 5.2 Approaches to Assigning Probabilities 5.3 Classical Probability 5.4 Empirical Probability 5.5 Subjective Probability Course Notes
7 5.6 Some Rules for Computing Probabilities 5.6.1 Rules of Addition 5.6.2 Rules of Multiplication 5.7 Contingency Tables 5.8 Tree Diagrams 5.9 Principles of Counting 5.10 The Multiplication Formula 5.11 The Permutation Formula 5.12 The Combination Formula Course Notes
8 Mid-Term Exam Course Notes
9 6. DISCRETE PROBABILITY DISTRIBUTIONS 6.1 What Is a Probability Distribution? 6.2 Random Variables 6.2.1 Discrete Random Variable 6.2.2 Continuous Random Variable 6.3 The Mean, Variance, and Standard Deviation of a Probability Distribution 6.4 Binomial Probability Distribution 6.5 How Is a Binomial Probability Distribution Computed 6.6 Poisson Probability Distribution Course Notes
10 7. CONTINUOUS PROBABILITY DISTRIBUTIONS 7.1 The Family of Uniform Distributions 7.2 The Family of Normal Probability Distributions 7.3 The Standard Normal Distribution 7.4 The Empirical Rule 7.5 Finding Areas under the Normal Curve Course Notes
11 8. SAMPLING METHODS AND THE CENTRAL UMIT THEOREM 8.1 Sampling Methods 8.2 Reasons to Sample 8.3 Simple Random Sampling 8.4 Systematic Random Sampling 8.5 Stratified Random Sampling 8.6 Cluster Sampling Course Notes
12 8.7 Sampling "Error" 8.8 Sampling Distribution of the Sample Mean 8.9 The Central Limit Theorem 8.10 Using the Sampling Distribution of the Sample Mean Course Notes
13 9. ESTIMATION AND CONFIDENCE INTERVALS 9.1 Point Estimates and Confidence Intervals 9.2 Known 0' or a Large Sample 9.3 Unknown Population Standard Deviation and a Small Sample 9.4 A Confidence Interval for a Proportion 9.5 Finite-Population Correction Factor 9.6 Choosing an Appropriate Sample Size Ders Notes
14 10. ONE-SAMPLE TESTS OF HYPOTHESIS 10.1 What Is a Hypothesis? 10.2 What Is Hypothesis Testing? 10.3 Five-Step Procedure for Testing a Hypothesis 10.4 One-Tailed and Two-Tailed Tests of Significance Course Notes
15 10.5 Testing for a Population Mean with a Known Population Standard Deviation 10.6 p-Value in Hypothesis Testing 10.7 Tests Concerning Proportions Course Notes


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
C1 5 5
C2 5 5
C3 5 5
C4 5 5
C5 5 5
C6 5 5

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