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 develop a critical perspective by defining economic theories, comparing theory applications, and economic systems.
PO-2
To identify economic agents (such as government, firms, households, etc.), to understand their roles within the economy, to evaluate and analyze them.
PO-3
To define policies for solving economic problems, to evaluate solution proposals, and to develop policies.
PO-4
To make predictions regarding the resolution of economic problems using numerical methods and econometric analysis techniques.
PO-5
To make future predictions by evaluating national and international economic and financial data.
PO-6
To relate economic growth and development to social events historically.
PO-7
To utilize skills such as independent work, taking responsibility, and creativity.
PO-8
To develop skills in teamwork through verbal and written communication, problem-solving, and to utilize information technologies.
PO-9
To adapt the theoretical knowledge acquired to business life.
PO-10
To evaluate skills that will be useful for future careers.
PO-11
To act in accordance with social, rational, scientific and ethical values during the collection, interpretation and announcement of data related to the field of Managerial Economics and to carry out the thesis within the framework of these principles.
Learning Outcomes
LO-1
to identify variable and data types
LO-2
to be able to analyze univariate data by descriptive and inferential methods
LO-3
to be able to collect data by appropriate methods
LO-4
to be able to analyze the relationships between variables
LO-5
to be able to model the relationships between variables
LO-6
to be able to identify patterns in data
LO-7
to be able to perform data analysis using computer software
