COURSE UNIT TITLE

: STATISTICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IBF 2003 STATISTICS 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

Labour Economics and Industrial Relations (Evening)
Public Finance (Evening)
Labour Economics and Industrial Relations
Public Administration (Evening)
Public Administration
Public Finance
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, sample statistics
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, quartiles. range of variability and asymmetry measurements.
4 basic concepts of probability, The Basic Rules of Counting, sum-product rule, permutation, combination, basic probability theorems, dependent/independent events, conditional probability, bayes theorem.
5 discrete probability distributions: discrete uniform, bernoulli and poisson.
6 continuous probability distributions: exponential and normal distributions.
7 sampling and sampling distributions: basic concepts, basic logic and necessity, central limit theorem, sampling distribution of the means, sampling distribution of the proportions, sampling distribution of difference between the means ,sampling distribution of the difference between the proportions
8 Mid-term
9 Mid-term
10 point esimation: propertis of estimator. interval estimation: for the population mean (small and large samples), for the difference of two populations means, for the population proportion, for the difference of two populations means
11 hypothesis testing: for the population mean (small and large samples), for the difference of two populations means, for the population proportion, for the difference of two populations means
12 chi-square analysis and cross tables: cross tables, test of independence.
13 linear regression: estimation of univariate regression coefficients, determination and correlation coefficients
14 one way and two way anova ( analysis of variance )

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


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 midterm exam 1 25 25
Preparation for final exam 1 28 28
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.13
LO.1111
LO.211
LO.311
LO.411
LO.511
LO.611
LO.711