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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS LGM 2003 STATISTICS FOR BUSINESS AND MANAGEMENT COMPULSORY 3 0 0 6

Offered By

Logistics Management

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR VOLKAN ÇETINKAYA

Offered to

Logistics Management

Course Objective

To learn basic statistics concept and how statistics can be used in management by different applications and make data analyses via MS Excel and SPSS.

Learning Outcomes of the Course Unit

1   To know collecting and sampling data. 2   To learn probality statistical distrubitions. 3   To know how to make a hypothesis test. 4   To learn Basic Regression Analysis. 5   To forecast by Time Series Method. 6   To make data analysis in MS Excel and SPSS

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to the Course and Overview of Course and Requirements Types of variables; data collection principles; types of studies 2 Numerical Data Graphical methods: histograms and other graphs 3 Measures of central tendency and dispersion Tabular methods: contingency tables graphical methods: bar plots and other graphs 4 Measures of central tendency and dispersion Numerical methods: the average, the standard deviation, etc. 5 Probability Probability rules 6 Probability Distributions Normal distribution-Normal approximation 7 Probability Distributions Binomial distribution, Poisson Distribution 8 Sampling and Estimation Sampling and Estimation 9 Sampling and Estimation Types of sampling, sampling methods, confidence intervals 10 Hypothesis Testing One sample, two sample z test, One sample, two sample t-test 11 Hypothesis Testing Comparing means with ANOVA 12 Regression Simple and multiple regression 13 Time Series And Forecasting Trends, forecasting with time series 14 MS Excel and SPSS Application Regression, time series calculations drawing graph 15 MS Excel and SPSS Application Review of applications 16 Final Exam

Recomended or Required Reading

Newbold, P., Carlson W.L., Thorne B.M., Statistics for Business and Economics, Pearson. McClave, J., Benson, P.G, Sincich, T., Statistics for Business and Economics, Pearson. Goodwin E.M., Kemp, J. Marine Statistics Theory and Practice, Stanford Maritime.

Planned Learning Activities and Teaching Methods

Literature review, case studies, problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MD Midterm 2 HW Homework 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MD * 0.30 + HW * 0.20 + FN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MD * 0.30 + HW * 0.20 + BUT * 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Oral and written competencies regarding the use of knowledge, abilities and skills in the field of Statistics in terms of research, investigation and evaluation will be evaluated.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Room: 211 Tel: 301 88 21 e-mail:volkan.cetinkaya@deu.edu.tr

Office Hours

Monday 11:00-12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 13 4 52 Preparation for midterm exam 1 15 15 Preparation for final exam 1 20 20 Preparing assignments 1 10 10 Final 1 2 2 TOTAL WORKLOAD (hours) 141

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 LO.1 3 3 3 3 3 3 3 LO.2 3 3 3 3 3 3 3 3 3 LO.3 3 3 3 3 3 3 3 3 3 3 LO.4 3 3 3 3 3 3 3 LO.5 3 3 3 3 3 3 3 3 3 3 3 LO.6 3 3 3 3 3 3 3 3 3 3 3 3 3