Преподавател(и):

проф. Димитър Атанасов  д-р
гл. ас. Иван Ванков  д-р

Описание на курса:

Компетенции:

Students graduating the course will have basic knowledge in probability theory and will know how to describe data using numeric measure and graphical plots. They will also be introduced to the fundamentals of frequentist statistical inference.

Предварителни изисквания:
The course requires basic numeric skills and logical reasoning skills.

Форми на провеждане:
Редовен

Учебни форми:
Лекция

Език, на който се води курса:
Английски

Теми, които се разглеждат в курса:

1. The philosophy of science. The scientific method. What is statistics for. Samples and populations. The uncertainty in scientific studies. Descriptive and inferential statistics.
2. Mathematics I. Arithmetic operations - addition, subtraction, multiplication, division. Negative and positive numbers. Integers and real numbers. Coordinate systems - number line, Cartesian coordinates. Fractions. Rational and irrational numbers. Exponentiation - square and square root. Logarithm. Linear and non-linear functions. Linear equations. Compact notations for summation and product.
3. Measurement scales. Measures of central tendency - mean, median, mode.
4. Measures of variance - range, variance, standard deviation.
5. Data plots. Histrograms. Scatter plots. Bar charts. Box plots.
6. Elements of probability theory. Types of events - independent/related, mutually exclusive, complementary. Frequency. Calculating probabilities. Joint probability. Conditional probability. Random variables. Probability distributions. The normal probability distribution.
7. Standardization. Z transformation. Z scores.
8. Sampling distributions. Standard error.
9. Review of material. Exercises. Real world examples. Discussion.
10. Midterm test.
11. End of term test.
12. Assignment

Литература по темите:

Agresti, A. (2012). Statistics: The Art and Science of Learning from Data, Pearson, ISBN: 9780321755940