COURSE UNIT TITLE

: STATISTICS I

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IBF 1007 STATISTICS I COMPULSORY 3 0 0 5

Offered By

Faculty of Economics and Administrative Sciences

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR HAMDI EMEÇ

Offered to

Management Information Systems
Economics
Econometrics (Evening)
Economics (Evening)
Business Administration (Evening)
Business Administration
Econometrics
Faculty of Economics and Administrative Sciences

Course Objective

The main objective of the course is 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   To be able to understand the relation of science and statistics
2   To be able to use measures of central tendency and variation
3   To be able to present frequencies with graphs
4   To be able to classify variables with regard to their features
5   To be able to identify the shape of the distribution by using the measures of central tendency
6   To be able to define the basic concepts of statistics
7   To be able to show the relations between distributions

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to statistics, basic concepts, statistic, population, parameter, variable, data
2 Gathering data, classifying, graphical representations, frequency distributions, pie nd bar charts, time series charts, scatter diagrams, histograms, frequency poligons.
3 Measures of central tendency: mean, mode, median, geometric mean, harmonic mean, quartiles.
4 Measures of variation and asymmetry: range, Standard deviation, variance, absolute deviation, men absolute deviation.
5 Bowley and pearson asymmetry measures.
6 Permutation, combination
7 Probability theorems, dependent/independent events, conditional probability, Bayes Theorem, discrete/continuous random variable, probability density function, expected value, moments.
8 Mid-term
9 Mid-term
10 Discrete probability distributions
11 Normal Distribution
12 Central Limit Theorem
13 Sampling distributions
14 Properties of estimators

Recomended or Required Reading

Statistics for Business and Economics, Paul Newbold.

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 MTEG MIDTERM GRADE MTEG * 1
3 FIN FINAL EXAM
4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60


*** 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 3 36
Preparations before/after weekly lectures 12 2 24
Preparation for final exam 1 28 28
Preparation for midterm exam 1 25 25
Midterm 1 1 1
Final 1 1 1
TOTAL WORKLOAD (hours) 115

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.111
LO.211
LO.311
LO.411
LO.511
LO.611
LO.711