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Course Information
Course Unit Title : Evaluation of Experimental Data
Course Unit Code : 01MAD9620
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : Preb
Semester : 255.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants :
Learning Outcomes of The Course Unit : Learn to determine the possible errors in the experimental data
Learn to apply statistical tests to data
Learn to draw scatter graphs of experimental data and determine the fit model
Learn to make reliability tests to generated models
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Basic concepts of measurement, measurement, units, measurement uncertainties, mod, median, range, precision, accuracy, absolute error, relative error, experimental error in the data types and systematic error, random error, statistical analysis of experimental data, data collection and processing, data presentation, regression analysis, confidence intervals, Q and F tests
Languages of Instruction : Turkish
Course Goals : Determination of errors in the experimental data
Mean, standard deviation, kurtosis and skewness measure to experimental data
Simple and multiple regression, correlation, analysis of variance application
Performing to reliability tests
Course Aims : Be able to make analysis (regression, correlation, variance) of the data obtained from experiments made to determine the engineering properties of rocks with statistical programs (SPSS, MS Excel), determinate the errors in the experimental data and perform to reliability tests.
WorkPlacement  
Recommended or Required Reading
Textbook : Saim SARAÇ, 2000. Statistics for Engineers, Course note
Additional Resources : 1. Experimental Methods for Engineers", Jack P. Holman, McGraw-Hill Mechanical Engineering, 7th Edition., 2001. 2. "Measurement and Data Analysis for Engineering and Science", Patrick F. Dunn, McGraw-Hill Mechanical Engineering, 1st Edition, 2005. 3. "Introduction to Engineering Experimentation:2/e", Anthony Wheeler and Ahmad Ganji,Prentice Hall, 2004. 4. Ölçme tekniği :boyut, basınç, akış ve sıcaklık ölçmeleri. Genceli, Osman F., Birsen Yayınevi, 1995 5. Morris, Alan S. Measurement and instrumentation principles. Butterworth-Heinemann, 2006 6. Dally, James W. Instrumentation for engineering measurements. Wiley, 1993 7. Measurement and Data Analysis for Engineering and Science. Patrick F. Dunn, McGraw-Hill Mechanical Engineering, 1st Edition, 2005
Material Sharing
Documents :
Assignments :
Exams :
Additional Material :
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
ECTS / Table Of Workload (Number of ECTS credits allocated)
Student workload surveys utilized to determine ECTS credits.
Activity :
Number Duration Total  
Course Duration (Excluding Exam Week) :
14 3 42  
Time Of Studying Out Of Class :
14 3 42  
Homeworks :
3 15 45  
Presentation :
0 0 0  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 15 15  
Finals :
1 25 25  
Workload Hour (30) :
30  
Total Work Charge / Hour :
169  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 50
Quiz :
1 20
Homework :
1 30
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
40
The ratio of final to success :
60
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Basic concepts related to statistics
 
2 Experimental data acquisition and measurement techniques
 
3 Types of error in the experimental data
 
4 Determination of the average, mode, median, quantile, standard deviation and variation of the data
 
5 Determination of kurtosis and skewness in data
 
6 Graphical presentation of data and add trend lines
 
7 Analysis of variance
 
8 Quiz
 
9 Introduction of SPSS
 
10 Data analysis with SPSS
 
11 Simple regression analysis with SPSS
 
12 Multiple regression analysis with SPSS
 
13 F and t test with SPSS
 
14 Analysis of variance with SPSS