ADA 423

Course Code & Number

ADA 423

Course Title

Statistical Inference Methods with Applications

Level

BS

Credit Hours/ ECTS Credits

(3+0+0) 3 TEDU Credits, 6 ECTS Credits

Year of Study:

Junior

Semester:

Fall

Type of Course:

Compulsory

Mode of Delivery:

Face-to-face

Language of Instruction:

English

Pre-requisite / Co-requisite:

Catalog Description

Data structures, loops and conditionals, data wrangling, grouping and summarizing, transforming data, data visualization, exploratory data analytics, statistical inference, hypothesis testing, analysis of variance, introduction to statistical modelling, linear and logistic regression as statistical models.

Course Objectives

The main objective of this course is to make a gentle introduction to basic statistical inference tools. Students are expected to implement and apply the inference methods to statistical hypotheses motivated by real life problems. Using a high level programming language (such as R or Python) throughout the course is mandatory.

Course Learning Outcomes

Upon successful completion of this course, a student will be able to:

1.Develop an ability to apply appropriate statistical methods to summarize and analyze data

2.Use graphical methods and statistical measures to explore data

3.Use several statistical modeling techniques to solve business practice problems

4.Apply linear and logistic regression as a statistical learning method

5.Apply these techniques on large sets of data using a high-level programming language such as R or Python. 

Course Coordinator:

Dr. Seyit Mümin Cılasun