Course Detail

Course Description Course Outline Course Contribution to Program Qualifications Assessment Methods ECTS-Workload Detail Informations of the Course Numerical Data

Course Description

Course	Code	Semester	T+P (Hour)	Credit	ECTS
STATISTICS II	AVM2252810	Spring Semester	3+0	3	5

Course Program

Prerequisites Courses
Recommended Elective Courses

Language of Course	English
Course Level	First Cycle (Bachelor's Degree)
Course Type	Required
Course Coordinator	Assist.Prof. Esra BAYTÖREN
Name of Lecturer(s)	Assist.Prof. Recep ÖZSÜRÜNÇ
Assistant(s)
Aim	Students are aimed to understand the logic of inferential statistics and to apply hypothesis testing and regression analysis for simple business problems.
Course Content	This course contains; Introduction to Hypothesis Testing , Five - Step Procedure for Hypothesis Testing ,z and t Tests About a Population Mean, z Tests About a Population Proportion ,Sample Size Determination, The Chi–Square Distribution and Statistical Inference for Population Variance , One – Sample Hypothesis Testing Using EXCEL and SPSS,Statistical Inference Based On Two Samples ,Comparing Two Population Proportions and Variances by Using Large Independent Samples ,Two Sample HypothesisTesting Using Excel and SPSS ,Experimental Design and Analysis of Variance ,Two – Way Analysis of Variance ,Chi – Square Tests ,Simple Linear Regression Analysis,Regression Analysis - Confidence and Prediction Intervals ,Simple Coefficients of Determination and Correlation, An F–Test for the Model, Residual Analysis .

Course Learning Outcomes	Teaching Methods	Assessment Methods
1. Will be able to explain the logic of hypothesis tests.	10, 16, 6, 9	A
1.1 Explains the place of hypothesis testing in inferential statistics
1.2 Creates null and alternative hypotheses
1.3 Explains Type I and Type II errors and their probabilities
2. Will be able to explain one-sample and two-sample hypothesis tests.	10, 16, 6, 9	A
2.1 Uses critical values and p-values to perform a z test and t test about a population mean
2.2 Compares two population means when the samples are independent
2.3 Compares two population means when the data are paired
3. Will be able to use computer programs to perform one-sample hypothesis testing and two-sample hypothesis testing.	10, 16, 6, 9	A
3.1 Performs one-sample tests and two–sample tests using Excel
3.2 Performs one–sample tests and two–sample tests using SPSS
4. Will be able to explain variance analysis.	10, 16, 6, 9	A
4.1 Explains the basic terminology and concepts of experimental design
4.2 Compares several different population means by using a one-way analysis of variance
4.3 Compares treatment effects and block effects by using a randomized block design
5. Will be able to define chi-square tests.	10, 16, 6, 9	A
5.1 Describes the properties of the Chi–square distribution
5.2 Uses Chi-square table
6. Will be able to use simple regression analysis.	10, 16, 6, 9	A
6.1 Explains the simple linear regression model
6.2 Describes the assumptions of simple linear regression
6.3 Calculates simple coefficient of determination and simple correlation coefficient

Teaching Methods:	10: Discussion Method, 16: Question - Answer Technique, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:	A: Traditional Written Exam

Course Outline

Order	Subjects	Preliminary Work
1	Introduction to Hypothesis Testing
2	Five - Step Procedure for Hypothesis Testing
3	z and t Tests About a Population Mean, z Tests About a Population Proportion
4	Sample Size Determination, The Chi–Square Distribution and Statistical Inference for Population Variance
5	One – Sample Hypothesis Testing Using EXCEL and SPSS
6	Statistical Inference Based On Two Samples
7	Comparing Two Population Proportions and Variances by Using Large Independent Samples
8	Two Sample HypothesisTesting Using Excel and SPSS
9	Experimental Design and Analysis of Variance
10	Two – Way Analysis of Variance
11	Chi – Square Tests
12	Simple Linear Regression Analysis
13	Regression Analysis - Confidence and Prediction Intervals
14	Simple Coefficients of Determination and Correlation, An F–Test for the Model, Residual Analysis

Resources

[1] Statistics for Business and Economics, 14th edition, McClave, Benson, Sincich, Pearson, 2022 [2] Statistics for Business and Economics, 11th Edition, David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, South-Western Cengage Learning, 2011

[3] İşletme İstatistiğinin Temelleri, 4.basımdan Çeviri, Çeviri Editörleri: N.Orhunbilge, M.Can, Ş.Er, Nobel Akademik Yayıncılık, 2018 [4] Lecture Notes

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
No	Program Qualification	Contribution Level
No	Program Qualification	1	2	3	4	5
1	Defines the theoretical knowledge in the field of aviation management.
2	Explains the necessary of mathematical and statistical methods in the field of aviation management.
3	Uses at least one computer program required in the field of aviation management.
4	Demonstrates proficiency in foreign language proficiency required in the field of aviation management.
5	Prepares projects about his field and manages team works.
6	It critically evaluates the knowledge and skills that it constantly renews and acquires by following the developments in the field of Aviation management with the awareness of lifelong learning in the professional field.
7	Uses theoretical and practical information in the field of aviation management.
8	Follows up to date technologies and communicates verbally/writing using a foreign language at least A2 level.
9	Adopts and uses organizational / corporate, business and social ethical values.
10	It adopts social responsibility principles and takes initiative when necessary, within the framework of public service sensitivity.
11	In order to carry out interdisciplinary studies, analyze basic information and data in different disciplines and use them in the field.
12	It offers appropriate suggestions in both micro and macro frameworks in the face of problems in the aviation management sectors.

Assessment Methods

Contribution Level	Absolute Evaluation
Rate of Midterm Exam to Success		40
Rate of Final Exam to Success		60
Total		100

ECTS / Workload Table
Activities	Number of	Duration(Hour)	Total Workload(Hour)
Course Hours	14	3	42
Guided Problem Solving	0	0	0
Resolution of Homework Problems and Submission as a Report	0	0	0
Term Project	0	0	0
Presentation of Project / Seminar	0	0	0
Quiz	0	0	0
Midterm Exam	1	48	48
General Exam	1	60	60
Performance Task, Maintenance Plan	0	0	0
Total Workload(Hour)			150
*Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30=(150/30)**			5
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.

Detail Informations of the Course