Probability and Statistics II (MATH292) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Probability and Statistics II	MATH292	Diğer Bölümlere Verilen Ders	3	0	0	3	5

Pre-requisite Course(s)
MATH291

Course Language	English
Course Type	Service Courses Given to Other Departments
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	By providing basic knowledge on the some inferential statistics topics such as sampling and sampling distributions, point and interval estimations, hypothesis testing, simple linear regression and analysis of variance, to enable the students to get objective decision within uncertain environments
Course Learning Outcomes	The students who succeeded in this course; Upon completing the course, students are expected to; 1) have knowledge on the sampling and special sampling distributions, 2) be able to estimate the unknown population parameters by point and , 3) interval estimation techniques, 4) be able to test the hypothesis based on population parameters, 5) be able to use the goodness of fitting and independency tests on the data structure, 6) be able to apply simple linear regression and correlation analysis, 7) be able to use one way analysis of variance
Course Content	Sampling and sampling distributions, Central Limit Theorem, point estimation, confidence interval, hypothesis testing, regression and correlation, variance analysis.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Sampling Concept, Parameter and Statistics, Sampling Distributions	pp. 207-210
2	Central Limit Theorem	pp.211-220
3	Applications on the Sampling Distribution of Sample Mean and Sample Proportion	pp. 225-230
4	The Concept of Point and Interval Estimation, Unbiased and Consistent Estimators	pp. 240-242
5	Confidence Intervals for Population Mean and Population Proportion	pp. 246-250
6	Confidence Interval for Population Standard Deviation	pp.276-280
7	Midterm Exam
8	The Concept of Hypothesis Testing, Simple and Composite Hypothesis,,α, β Errors, Significance Level	pp.298-308
9	Hypotheses on Population Mean and Population Proportion	pp.315-317,337-338
10	Hypothesis on Population Variance	pp. 346-347
11	Hypothesis Based on The Difference Between Two Population Parameters	pp. 361-365
12	Goodness of Fitting Test and Independency Test	pp. 482-488
13	Relationship between two variables, Meaning of Covariance, Perason Correlation Coefficient and its Significance test	pp. 521- 525
14	Simple Linear Regression Model, Least Squared Method, Analysis of Regression Model, Determination Coefficient	pp. 531-535
15	Analysis of Variance and Overview of The Course	pp. 441-445

Sources

Course Book	1. D.H. Sanders, R. K. Simidt, Statistics, A First Course, 1990 Other Sources
Other Sources	2. Elementary Statistics, A step by step Approach, Bluman, 2001

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	2	10
Presentation	-	-
Project	-	-
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	2	50
Final Exam/Final Jury	1	40
Toplam	5	100

Percentage of Semester Work	60
Percentage of Final Work	40
Total	100

Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	Acquires skills to use the advanced theoretical and applied knowledge obtained at the mathematics bachelors program to do further academic and scientific research in both mathematics-based graduate programs and public or private sectors.
2	Transplants and applies the theoretical and applicable knowledge gained in their field to the secondary education by using suitable tools and devices.
3	Acquires the skill of choosing, using and improving problem solving techniques which are needed for modeling and solving current problems in mathematics or related fields by using the obtained knowledge and skills.
4	Acquires analytical thinking and uses time effectively in the process of deduction
5	Acquires basic software knowledge necessary to work in the computer science related fields and together with the skills to use information technologies effectively.
6	Obtains the ability to collect data, to analyze, interpret and use statistical methods necessary in decision making processes.
7	Acquires the level of knowledge to be able to work in the mathematics and related fields and keeps professional knowledge and skills up-to-date with awareness in the importance of lifelong learning.
8	Takes responsibility in mathematics related areas and has the ability to work affectively either individually or as a member of a team.
9	Has proficiency in English language and has the ability to communicate with colleagues and to follow the innovations in mathematics and related fields.
10	Has the ability to communicate ideas with peers supported by qualitative and quantitative data.
11	Has professional and ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class	14	3	42
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	10	20
Prepration of Final Exams/Final Jury	1	15	15
Total Workload			77