| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Statistics I | ISF201 | Compulsory | Bachelor's degree | 2 | Fall | 6 |
Name of Lecturer(s)
Prof. Dr. Muhsin HALİS
Assistant Prof. Dr. Serdar YARLIKAŞ
Learning Outcomes of the Course Unit
1) Organize , draw graphical presentation and compute the necessary sample statistics from the data collected for the statistical study.
2) Apply statistical software.
3) Interpret the statistical summary data.
4) Comment on sample statistics.
5) List probabilities for discrete and continuous variables.
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
| Learning Outcomes | |||||||||||
| 1 | High | Middle | Middle | Middle | Middle | Middle | Low | Low | High | High | |
| 2 | High | Middle | Middle | Middle | Middle | Middle | Low | Low | High | Low | |
| 3 | High | Middle | Middle | Middle | Middle | Middle | Low | Low | High | Low | |
| 4 | High | Middle | Middle | Middle | Middle | Middle | Low | Low | High | Low | |
| 5 | High | Middle | Middle | Middle | Middle | Middle | Low | Low | High | Low | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
None
Course Contents
This course covers organization, presentation, summarization and interpretation of the data, basic properties and theories of probability, discrete and continuous probability distributions.
Weekly Schedule
1) Data and Statistics2) Descriptive Statistics: Tabular and Graphical Methods
3) Descriptive Statistics: Summarizing Quantitative Data, Crosstabulations and Scatter Diagrams
4) Descriptive Statistics: Measures of location (mean, trimmed mean, median, mode, percentiles, quartiles)
5) Descriptive Statistics: Measures of location (mean, trimmed mean, median, mode, percentiles, quartiles)
6) Descriptive Statistics: Range, Interquartile Range, Variance, Standard Deviation, Coefficient of Variation
7) Descriptive Statistics: Some Uses of Standard Deviation and Mean (Z-scores and Chebyshev's Theorem)
8) Midterm Examination/Assessment
9) Descriptive Statistics : Exploratory Data Analysis, Measures of Association and Covariance
10) Introduction to Probability
11) Introduction to Probability
12) Discrete Probality Distributions - Random Variables, Expected Value and Variance, Binom and Poisson Probability Distribution
13) Discrete Probality Distributions - Random Variables, Expected Value and Variance, Binom and Poisson Probability Distribution
14) Continuous Probability Distribution- Normal and Exponential Probability Distribution
15) Continuous Probability Distribution- Normal and Exponential Probability Distribution
16) Final Examination
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
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
English
Work Placement(s)
Not Required