COURSE UNIT TITLE

: DATA MANAGEMENT IN STATISTICS WITH EXCEL

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4155 DATA MANAGEMENT IN STATISTICS WITH EXCEL ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ENGIN YILDIZTEPE

Offered to

Statistics
Statistics(Evening)

Course Objective

This course aims to learn students the VBA macro development, to use Excel effectively in data manipulation, tabulation and reporting.

Learning Outcomes of the Course Unit

1   To be able to organize data in spreadsheets
2   To be able to use built-in functions
3   To be able to use array functions
4   To be able to use Excel worksheets as a database, to obtain pivot tables and charts
5   Developing macro with VBA

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Using Excel applications; ribbon interface, shortcuts, file types
2 Data organization in spreadsheets, Data and Formula manipulation
3 Excel functions; math, statistical functions
4 Excel functions; date, list management and look up, text functions
5 Array Formulas
6 Array Formulas
7 Using Excel as a Database, to sort data, to filter data, data validation
8 Using Excel as a Database, to find duplicate values, to share data with other applications
9 Making pivot tables and charts
10 Programming with Excel; macros, VBA code editor, essential VBA language elements
11 Sub and Function procedures
12 Conditional statements, loops and arrays
13 VBA and working Excel object
14 Review of Excel applications in different fields

Recomended or Required Reading

Textbook(s):
Wayne L. Winston, Microsoft Excel 2019: Data Analysis and Business Modeling, 6th Ed., Microsoft Press, 2019.
Supplementary Book(s):
1. Alexander, M., & Kusleika, D. (2016). Excel 2016 power programming with VBA. Wiley.
2. Held, B., Moriarty, B., & Richardson, T. (2019). Microsoft Excel Functions and Formulas. Stylus Publishing, LLC.
3. Karl W. Broman & Kara H. Woo (2018) Data Organization in Spreadsheets, The American Statistician, 72:1, 2-10
4. Materials, Lecture slides

Planned Learning Activities and Teaching Methods

Lecture, examples and PC laboratory exercises.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FIN * 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

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 https://fen.deu.edu.tr/

Contact Details for the Lecturer(s)

DEU Faculty of Science Department of Statistics
e-mail: engin.yildiztepe@deu.edu.tr
Phone:+90 232 301 86 04

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 20 20
Preparation for final exam 1 30 30
Web Search and Library Research 2 7 14
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 124

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.155
LO.255
LO.355
LO.455
LO.555