

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 
: 
FaceToFace

Prerequisities and Corequisities Courses 
: 
Unavailable

Recommended Optional Programme Components 
: 
Unavailable

Course Contents 
: 
Data: Data description, stemandleaf 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 
: 
TurkishEnglish

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

:


Course Duration (Excluding Exam Week)

:


Time Of Studying Out Of Class

:


Homeworks

:


Presentation

:


Project

:


Lab Study

:


Field Study

:


Visas

:


Finals

:


Workload Hour (30)

:


Total Work Charge / Hour

:


Course's ECTS Credit

:



Assessment Methods and Criteria
Studies During Halfterm

: 

Visa

: 

Quiz

: 

Homework

: 

Attendance

: 

Application

: 

Lab

: 

Project

: 

Workshop

: 

Seminary

: 

Field study

: 




TOTAL

: 

The ratio of the term to success

: 

The ratio of final to success

: 

TOTAL

: 


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, tdistribution, Population Proportion



4

ChiSquare 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

FDistribution, 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 ChiSquare: A Test of Goodness of Fit, A Test of Independence, A Test of Homogeneity, Recitation



14

Introducing SPSS Package: Application with SPSS



























































































