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Course Information
Course Unit Title : Probability and Statistics II
Course Unit Code : MAT208
Type of Course Unit : Compulsory
Level of Course Unit : First Cycle
Year of Study : 2
Semester : 4.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants :
Learning Outcomes of The Course Unit : 1 Skill for organizing given data and computing average and standard deviation
2 Skill for making estimation about a parameter by using confidence intervals and hypotesis testing
3 Skill for construct a linear models for given data set by doing regression analysis
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Data: Data description, stem-and-leaf plot, histogram, looking at data with median and quartiles.
Point Estimation: Definition of estimator, sampling distribution, confidence intervals, hypothesis testing.
Linear Regression: Linear association of two random variables, correlation, regression analysis
Languages of Instruction : Turkish-English
Course Goals : To teach arranging given data set and computing central tendency measures
To teach making estimation for parameter(s) by using confidence intervals and hypothesis testing
To teach linear relationship between two random variables by using regression and correlation analysis
Course Aims : To manage to arrange given data set and give some information about central tendency measures. To make estimation by using confidence interval and hypothesis testing of parameter(s). To determine linear relationship between two random variables by using regression analysis.
WorkPlacement   Not Available
Recommended or Required Reading
Textbook :
Additional Resources : Moore, D.S., McCabe, G.P. ?Introduction to the Practice of Statistics?, Freeman and Co. 1998
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) :
15 3 45  
Time Of Studying Out Of Class :
15 4 60  
Homeworks :
2 15 30  
Presentation :
0 0 0  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 20 20  
Finals :
1 25 25  
Workload Hour (30) :
30  
Total Work Charge / Hour :
180  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 40
Quiz :
0 0
Homework :
0 0
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
40
The ratio of the term to success :
40
The ratio of final to success :
60
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Organizing Data, Frequency Distribution, Graphical Representation of Distributions, Central Tendency Measures, Spreading Measures, Recitaion
 
2 Sampling Distribution, Law of Large Numbers, Central Limit Theorem, Estimator concept, Point Estimation, Recitation
 
3 Confidence Intervals:
Confidence Interval for the Population Mean, t-distribution, Population Proportion
 
4 Chi-Square Distribution, Confidence Interval for the Population Variance, Confidence Interval for Paired Data
 
5 Confidence Interval for Difference of Population Means, Confidence Interval for Difference of Population Proportions
 
6 F-Distribution, Confidence Interval for the ratio of Population Variances, Recitation
 
7 Hypothesis Testing:
Type I and Type II Errors, Power of a test, Test for the Population Mean
 
8 Test for Paired Data, Test for the Difference of two Population Means
 
9 Test for the Population Proportion, Test for the Difference of Population Proportions
 
10 Test for the Population Variance, Test for the ratio of Population Variances, Recitation
 
11 Regression and Corelation:
Linear Regression, Least Squares Method
 
12 Curve Fitting, Estimation and Test for Slope, Recitation
 
13 Contingency Tests by Chi-Square:
A Test of Goodness of Fit, A Test of Independence, A Test of Homogeneity, Recitation
 
14 Introducing SPSS Package:
Application with SPSS