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	Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area
2	Can apply gained knowledge and problem solving abilities in inter-disciplinary research
3	Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary
4	Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study
5	Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework
6	Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility
7	Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation
8	To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2)
9	Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge
10	Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach.
11	Has professional 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