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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS SIV 1011 BUSINESS STATISTICS COMPULSORY 3 0 0 3

Offered By

Civil Aviation Management

Level of Course Unit

Short Cycle Programmes (Associate's Degree)

Course Coordinator

HAKAN SÖNMEZ

Offered to

Civil Aviation Management

Course Objective

To give the student an elementary introduction to the practice of statistics. This course will give insight into how an analyst gathers, summarizes, and draws conclusions from economical or business data. At the end of the course, the student should be a critical consumer of this information.

Learning Outcomes of the Course Unit

1   Students will be able to define the basic concepts of statistics 2   Students will be able to use measures of central tendency and variation 3   Students will be able to present frequencies with graphs 4   Students will be able to classify variables with regard to their features 5   Students will be able to identify the shape of the distribution by using the measures of central tendency 6   Students will be able to define the properites of estimators and importance in the theory of statistical estimation 7   Students will be able to propose appropriate regression models the dependent and independent variables 8   Students will be able to define the populations according to the representative sample taken 9   Students will be able to identify representative sample for populations

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 The definition of statistics, subject and the issue of applications; variable types: qualitative and quantitative; classification of data; with the help of graphic representation of data 2 Measures of central tendency: arithmetic, weighted, geometric, harmonic means, mode, median 3 Variability criterias: variability range, mean deviation, variance, standard deviation, skewness, kurtosis 4 The theory of probability: probability classification, collection of probability, multiplication rule of probability and Bayes' rule 5 Discrete random variables and probability distributions 6 Continuous random variables and probability distributions 7 Mid-Term Exam 8 Sampling theory: concepts of sampling, sampling techniques,sample distribution 9 Estimation of confidence interval; average and rate of sampling estimate of confidence intervals, estimate of the average and the rate difference confidence interval 10 Hypothesis testing: the stage of hypothesis testing, error types in hypothesis testing, hypothesis testing unidirectional, bidirectional hypothesis testing 11 Hypothesis testing for one population; small sampling theory; Student-t distribution, chi-square tests of independence and homogeneity 12 Hypothesis testing for one population; small sampling theory; Student-t distribution, chi-square tests of independence and homogeneity 13 Regression and correlation analysis 14 Regression and correlation analysis 15 Final Exam

Recomended or Required Reading

Textbook(s): 1)Işletme ve Iktisat için Istatistik, Literatür Yayın evi, Newbold,P. , Paul William Carlson and B. Thorne (Çeviren Ümit Şenesen),2010. 2) Probability and Statistics for Engineering and the Sciences (Jay L. Devore, Second Edition) 3) Istatistiğe Giriş, Fakülteler Barış Yayınları, Fikret Ikiz, Halis Püskülcü, Şaban Eren, 2006

Planned Learning Activities and Teaching Methods

Lecturing and preparing to subjects

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 QUZ QUIZ 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + QZ * 0.10 + FIN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + QZ * 0.10 + RST * 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 2 24 Preparation about subject 12 1 12 Preparation for midterm exam 1 12 12 Preparation for final exam 1 12 12 Preparations before/after weekly lectures 12 1 12 Reading 4 1 4 Midterm 1 2 2 Final 1 2 2 Quiz etc. 6 1 6 TOTAL WORKLOAD (hours) 86

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 PO.15 PO.16 LO.1 5 LO.2 4 LO.3 4 LO.4 5 LO.5 3 LO.6 5 LO.7 LO.8 LO.9