This course aims to familiarize graduate students of business and economics and all other students of social sciences with the basic principles, techniques, and applications of applied statistics and applied data analysis, and to provide students with the ability to collect and analyze data with the right methods. In addition, it is aimed to gain the ability to perform data analysis using computer package programs.
Prerequisite(s)
Corequisite(s)
Special Requisite(s)
Instructor(s)
Dr.Öğretim Üyesi Hasan Boztoprak
Course Assistant(s)
Schedule
Office Hour(s)
Teaching Methods and Techniques
The lectures will be given orally by the lecturer of the course. It is aimed that the students master the subjects with the weekly/term homework given.
Principle Sources
Cleff, T. (2019) Applied Statistics and Multivariate Data Analysis for Business and Economics:
A Modern Approach Using SPSS, Stata, and Excel, Springer, Cham, Switzerland.
Other Sources
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction – basic concepts; Types of statistics; Data collecting; measurement levels; Scaling and coding; Missing values and outliers
oral presentantion
2. Week
Univariate data analysis; Graphical representation of data; Measures of central tendency – mode, median, geometric mean, harmonic mean, quartiles, percentiles; Box plots;
oral presentantion
3. Week
Univariate data analysis; Measures of dispersion – standard deviation, variance, coefficient of variation; skewness, kurtosis
oral presentantion
4. Week
Bivariate association; Two nominal variables – contingency tables, chi-square calculations, phi coefficient, contingency coefficient, Cramer's V
oral presentantion
5. Week
Bivariate association; Two metric variables – scatterplot, pearson correlation coefficient; Two ordinal variables – Spearman's rank correlation coefficient, Kendall's Tau; Measuring the relationships between two variables with different scales; Computer software applications
Some Important Probability Distributions; Binomial Probability Distribution; Normal distribution; Computer software applications
oral presentantion
8. Week
Sampling and parameter estimation; Sampling methods; Point estimation; central limit theorem; interval estimation; Computer software applications
oral presentantion
9. Week
Hypothesis testing – I; Fundamentals of hypothesis testing; Single sample tests (z-test, t-test, p-value); Tests for two paired samples (t-test, Wilcoxon's signed-order test); Test of two independent samples (t test, Mann-Whitney U test); Computer software applications
oral presentantion
10. Week
Hypothesis testing – II; test for k independent samples (ANOVA, ANCOVA, Kruskal-Wallis' H test); Chi-square test of independence; tests for Normal distribution; Computer software applications
oral presentantion
11. Week
Regression analysis; Modeling relationships between variables; Bivariate regression; Multivariate regression; Calculation of goodness of fit; Regression diagnostics; influential observations; Computer software applications
A student who successfully completes the program will be able
To expand and deepen his/her field knowledge in the field of Money and Capital Markets at the level of expertise based on the undergraduate qualifications he/she has acquired.
PO-2
To use the knowledge gained in the field of Money and Capital Markets theoretically and practically.
PO-3
To evaluate information about Money and Capital Markets from a critical perspective and to work independently.
PO-4
To understand the interaction of Money and Capital Markets with different disciplines and fields.
PO-5
To have sufficient social responsibility and awareness about social needs, to acquire the experience and ability to organize activities that can affect social dynamics when necessary.
PO-6
To gain model development, technical analysis and policy making skills in the field of Money and Capital Markets.
PO-7
To understand and evaluate any event or problem in the field of Money and Capital Markets on its own and to produce solutions to the problems that arise.
PO-8
To analytically evaluate the problems related to Money and Capital Markets and to recommend economic and financial policies suitable for solving the problems.
PO-9
To adapt the theoretical knowledge acquired to business life.
PO-10
To develop original approaches and to take responsibility in extraordinary situations encountered in the fields of Money and Capital Markets.
PO-11
To act in accordance with social, rational, scientific and ethical values in the processes of collecting, interpreting and announcing data related to Money and Capital Markets and to carry out the thesis work within the framework of these principles
Learning Outcomes
LO-1
to be able to analyze the relationships between variables
LO-2
to be able to model the relationships between variables
LO-3
to be able to identify patterns in data
LO-4
to be able to perform data analysis using computer software
LO-5
to identify variable and data types
LO-6
to be able to analyze univariate data by descriptive and inferential methods
