COURSE UNIT TITLE

: PROBLEM BASED LEARNING I

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 1001 PROBLEM BASED LEARNING I COMPULSORY 2 0 0 3

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR SELMA GÜRLER

Offered to

Statistics(Evening)
Statistics

Course Objective

This course will be based on case studies providing applications to theoretical and conceptual aspects of Probability and Statistics I. Students will discuss on practical implications of statistical concepts in the literature. The aim of this course is to make students to describe data sets by graphical and numerical methods, to calculate probability, to form probability distributions for both discrete and continuous random variables and to calculate mathematical expectation.

Learning Outcomes of the Course Unit

1   Describing fundamental elements of Statistics
2   Distinguishing types of data
3   Calculating the measures which are used for describing data
4   Describing the fundamental elements of Probability
5   Calculating probabilities
6   Calculating probabilities by probability functions of discrete and continuous random variables
7   Calculating expected value
8   Obtaining moments of random variables

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Case study 1: Application of fundemantal elements of statistics
2 Case study 1: Application of fundemantal elements of statistics
3 Case study 1: Application of fundemantal elements of statistics
4 Case study 2: Application of describing sets of data by graphical methods
5 Case study 2: Application of describing sets of data by graphical methods
6 Case study 3: Application of measures of central tendency and measures of variation
7 Case study 3: Application of measures of central tendency and measures of variation
8 Midterm exam
9 Discussion on midterm exam questions
10 Case study 4: Application of probability
11 Case study 4: Application of probability
12 Case study 4: Application of probability
13 Case study 5: Application of calculation of probability
14 Case study 5: Application of calculation of probability

Recomended or Required Reading

Textbook(s):
J.T. McClave and T. Sincich, Statistics, 12th Edition, Prentice-Hall.
Supplementary Book(s):
1. P. Newbold, W. L. Carlson, B. Thorne, Statistics for Business and Economics, Seventh Edition, Pearson Education , 2010.

Planned Learning Activities and Teaching Methods

Lecture format built around case studies and problem based learning. Questions are encouraged and discussion of material stressed.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 FIN FINAL EXAM
2 FCG FINAL COURSE GRADE FCG * 1
3 RST RESIT
4 FCGR FINAL COURSE GRADE (RESIT) FCGR * 1

Further Notes About Assessment Methods

None

Assessment Criteria

Since this is an active learning system based lecture, the grades will be evaluated with 40% of the midterm exam and 60% of the final exam , but these grades will be shown as 100% final note on the system.

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-posta: selma.erdogan@deu.edu.tr
Tel: 0232 301 85 71
e-posta: firat.ozdemir@deu.edu.tr
Tel: 0232 301 86 00

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparation for midterm exam 1 14 14
Preparation for final exam 1 20 20
Preparing assignments 1 6 6
Midterm 1 2 2
Final 1 2 2
Quiz etc. 1 1 1
TOTAL WORKLOAD (hours) 71

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.155543
LO.255543
LO.355543
LO.455543
LO.555543
LO.655543
LO.755543
LO.855543