COURSE UNIT TITLE

: STATISTICS IN PLANNING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PLN 1254 STATISTICS IN PLANNING COMPULSORY 2 0 0 2

Offered By

City and Regional Planning

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR EBRU ÇUBUKÇU

Offered to

City and Regional Planning

Course Objective

This course describes the basic concepts of statistics. First the statistical analyses will be described. For each analysis at least one example related to city planning will be solved. Upon completion of the course students would be able to understand how to collect and analyse necessary data for various planning problems. Collecting real data is out of the scope of this course, examples will be given on hypothetical data.

Learning Outcomes of the Course Unit

1   Students would be able to identify basic concepts related to statistics in general and descriptive statistics in particular
2   Students would be able to understand applied value of various statistical analyses techniques for planning
3   Students would be able to interpret the findings of statistical analyses in planning

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic Concepts (population, sample, variable, quantitative and qualitative data)
2 Descriptive Statistics (graphics; eg. bar graph, stem and leaf, histogram)
3 Descriptive Statistics (graphics; eg. bar graph, stem and leaf, histogram)
4 Descriptive Statistics (evaluation of graphics; shape, mid point, distrubition)
5 Descriptive Statistics (evaluation of graphics; shape, mid point, distribution)
6 Descriptive Statistics (quantitative evaluation; mean, median, mode, standard deviation, interquartile range)
7 Descriptive Statistics (Computer application)
8 Mid Term
9 Correlation
10 Normal Distribution
11 Compare means (t-test)
12 Compare means (t-test)
13 Non Parametrical Test (ChiSquare)
14 Regression Analyses

Recomended or Required Reading

Moore, D. S. & McCabe G. P. (1996). Introduction to the practice of statistics. W. H. Freeman and Company, NewYork.
Ramsey, F. L. & Schafer D. W. (1997). The Statistical Sleuth A course in methods of Data Analysis. Wadsworth Publishing Company.
Spiegel, M. R. DiFranco, D. (1998) Statistics. The McGraw-Hill Companies, Inc. and MathSoft Inc.
Minium, E. W. & Clarke R. B. (1982) Elements of Statistical Reasoning. John Wiley Sons Inc.
Huff, D. (1993) How to lie with Statistics. W.W. Norton & Company Inc. NewYork.

Planned Learning Activities and Teaching Methods

Lectures, theoretical presentations and solved examples.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FINS FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FINS * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.50 + 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)

ebru.cubukcu@deu.edu.tr

Office Hours

Wednesday 09:30 12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Preparations before/after weekly lectures 14 1 14
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 46

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15PO.16PO.17
LO.111
LO.211
LO.311