# COURSE UNIT TITLE

: STATISTICAL SOFTWARE IN DATA ANALYSIS

#### 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

Biomedical Tehnologies (English)
Industrial Ph.D. Program In Advanced Biomedical Technologies
Statistics
M.Sc. 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

Face -to- Face

None

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 FIN FINAL EXAM 3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60

None

#### Assessment Criteria

Evaluation of exams.

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

To be announced.

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.10PO.11PO.12
LO.123
LO.223
LO.323
LO.423
LO.523
LO.623
LO.723