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Description of Individual Course UnitsCourse Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | İŞL205B2 | Statistics I | Compulsory | 2 | 3 | 4 |
| Level of Course Unit | First Cycle | Objectives of the Course | Can explain the purpose of Statistics 1 course. Statistics is a science that involves the collection, organisation, analysis and interpretation of data. The aim of Statistics 1 course is generally to teach students the basic principles and applications of statistical methods. | Name of Lecturer(s) | Doç Dr. Hakan PABUÇCU | Learning Outcomes | 1 | Basic Statistical Concepts: The student should understand and be able to use statistical terms and concepts correctly. | 2 | Data Collection and Organisation: The learner should understand data collection methods and be able to apply data organisation, cleaning and pre-processing steps. | 3 | Measures of Central Tendency and Dispersion: The student should be able to calculate and interpret appropriate measures to determine the central tendency and dispersion of data sets. | 4 | Probability and Probability Distributions: The student should understand the basic concepts of probability and be able to recognise probability distributions. | 5 | Sampling Theory: The student should be able to understand random sampling methods, determine the sampling distribution and understand the importance of sample size. |
| Mode of Delivery | Normal Education | Prerequisites and co-requisities | None | Recommended Optional Programme Components | None | Course Contents | Data Collection Methods: Giving basic information about how statistical data are collected and organised.
Measures of Central Tendency and Dispersion: To calculate and interpret the central tendency (mean, median, mode) and dispersion (variance, standard deviation) of data sets.
Probability Theory: Basic concepts of probability, probability distributions (e.g., normal distribution, binomial distribution) and their properties.
Discrete and Continuous Variables: Definition of discrete and continuous variables, their differences and methods of working with these variables.
Sampling Theory: Sampling methods, random sampling, sampling distribution and the importance of sample size. | Weekly Detailed Course Contents | |
1 | What is statistics?
Types of data: Numerical and categorical data
Measures of central tendency: Mean, median, mode | | | 2 | Measures of dispersion: Variance, standard deviation
Data visualization: Histograms, box plots, line graphs | | | 3 | Measures of dispersion: Variance, standard deviation
Data visualization: Histograms, box plots, line graphs | | | 4 | What is probability?
Probability concepts: Events, probability distribution | | | 5 | Basic probability rules: Addition rule, multiplication rule
Discrete probability distributions: Binomial distribution, Poisson distribution | | | 6 | Fundamentals of the normal distribution
Properties of the normal distribution | | | 7 | Mid term exam | | | 8 | Standard normal distribution and Z-scores | | | 9 | Probability calculations according to normal distribution
Other continuous probability distributions: Uniform, t, and χ² distributions | | | 10 | Probability calculations according to normal distribution
Other continuous probability distributions: Uniform, t, and χ² distributions | | | 11 | Sampling distributions: Partner's Distribution, t-distribution, χ²-distribution
Examples and applications related to sampling distributions | | | 12 | Sampling distributions: Partner's Distribution, t-distribution, χ²-distribution
Examples and applications related to sampling distributions | | | 13 | What is hypothesis testing?
One sample and two sample hypothesis tests | | | 14 | Steps of hypothesis testing: Hypothesis formulation, test statistic calculation, p-value calculation, decision making
Examples and applications related to hypothesis testing | | |
| Recommended or Required Reading | Akdeniz, F. (2022). Olasılık ve istatistik. Akademisyen Kitabevi. | Planned Learning Activities and Teaching Methods | | Assessment Methods and Criteria | |
Midterm Examination | 1 | 100 | SUM | 100 | |
Final Examination | 1 | 100 | SUM | 100 | Term (or Year) Learning Activities | 40 | End Of Term (or Year) Learning Activities | 60 | SUM | 100 |
| Language of Instruction | Turkish | Work Placement(s) | None |
| Workload Calculation | |
Midterm Examination | 1 | 50 | 50 | Final Examination | 1 | 80 | 80 | |
Contribution of Learning Outcomes to Programme Outcomes | LO1 | 4 | 5 | 5 | 1 | 3 | 2 | 3 | 4 | 2 | 3 | LO2 | 5 | 5 | 4 | 1 | 3 | 2 | 4 | 4 | 2 | 3 | LO3 | 4 | 5 | 5 | 1 | 3 | 2 | 4 | 5 | 1 | 4 | LO4 | 5 | 5 | 4 | 1 | 3 | 2 | 5 | 5 | 2 | 4 | LO5 | 5 | 5 | 5 | 1 | 3 | 2 | 4 | 4 | 2 | 5 |
| * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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