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Course Information
Course Unit Title : Data Analyses in Engineering
Course Unit Code : 01MAD6137
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : 1
Semester : 1.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants :
Learning Outcomes of The Course Unit : Numerical data clearly more to be presented to users for the purpose of the data shows trends and the relationship with other data showing the ability to select the chart type to win
Data reveal a tendency in the selection of trend lines and regression model by adding the appropriate solutions can be
Data is connected to all the terms or not in their series and determine the average ability
Distribution of the data series to decide on the type of ability to earn
By applying statistical tests ability to make distributions
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Mean, standard deviation, kurtosis, skewness, distributions, statistical tests, applications on two dimensional and multiple regression analyses of mining data
Languages of Instruction : Turkish
Course Goals : Mean, standard deviation, kurtosis, skewness of mining data
Applications on two dimensional and multiple regression analyses of mining data
Course Aims : Analyses of mining data with excel and data fit programme.
WorkPlacement   Not Available
Recommended or Required Reading
Textbook :
Additional Resources : Özkan Y. Microsoft Excel, Alfa Yayınları, 2000 İstanbul.
Data Fit Version 7.1.x by Oakdale Engineering.
Mühendisler için istatistik / Saim Saraç, Mersin 2000.
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 6 84  
Homeworks :
2 20 40  
Presentation :
0 0 0  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 2 2  
Finals :
1 2 2  
Workload Hour (30) :
30  
Total Work Charge / Hour :
170  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 80
Quiz :
0 0
Homework :
2 20
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 Introduction: definitions of general concepts in statistics (averages, mode, median, kantiller, standard deviation and coefficient of variation
 
2 Calculating the average of the numeric data
 
3 The average deviation, standard deviation and variance calculation
 
4 Chart types
 
5 Adding trendlines
 
6 Measurement of kurtosis and skewness
 
7 Distributions
 
8 R-square measure of the clarity with
 
9 Multiple regression analysis
 
10 F distribution and F test
 
11 t distribution and t test
 
12 Confidence interval estimates
 
13 Confidence interval estimates
 
14 General Assesment