COURSE UNIT TITLE

: STATISTICAL SOFTWARE IN DATA ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5021 STATISTICAL SOFTWARE IN DATA ANALYSIS ELECTIVE 2 2 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR SEDAT ÇAPAR

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies
Industrial Ph.D. Program In Advanced Biomedical Technologies
Biomedical Tehnologies (English)
Statistics
Statistics
M.Sc. Metallurgical and Material Engineering
Metallurgical and Material Engineering
STATISTICS
Metallurgical and Material Engineering

Course Objective

Overview of MINITAB; One view, display and summaries; Plotting Data, Tables; Statistical distributions; One-Sample confidence intervals and tests for population means; comparing two means, confidence intervals and tests.

Learning Outcomes of the Course Unit

1   Able to Use Some Statistical Packages
2   Data Definition and Managing Data
3   Calculating Descriptive Statistics
4   Making Tables and Graphics
5   Writing Macros
6   Estimation with Confidence Intervals
7   Able to Tests of Hypothesis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Minitab
2 Data Definition and Entering
3 Constructing Frequency Distributions, Graphs for Qualitative and Quantitative Data
4 Numerical Measures for Describing Data
5 Introduction to Macros
6 Macros for Numerical Measures of Central Tendency
7 Macros for Numerical Measures of Variability
8 Midterm exam
9 Discrete Probability Distributions
10 Continuous Probability Distributions
11 Macros for Probability Distributions
12 Estimation with Confidence Interval
13 Tests of Hypothesis
14 Macro Examples

Recomended or Required Reading

Textbook(s): McClave J.T., Sincich T., Statistics, 11th edition, Prentice Hall,USA, 2008.
Supplementary Book(s):
Ryan,B., Joiner, B.L. & Cryer, J.D., MINITAB Handbook, 5th edition, Brooks/Cole - Thomson Learning Inc, Duxbury, Canada, 2005

Planned Learning Activities and Teaching Methods

Lecture and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 +ASG * 0.35 +FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 +ASG * 0.35 +RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams.

Language of Instruction

English

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: sedat.capar@deu.edu.tr
Tel: 0232 301 86 01

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 4 56
Preparation for midterm exam 1 24 24
Preparation for final exam 1 48 48
Preparations before/after weekly lectures 14 3 42
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 174

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15554
LO.25554
LO.35554
LO.45554
LO.5
LO.6345
LO.7

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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