ECTS - Introduction to Probability and Statistics II
Introduction to Probability and Statistics II (MATH294) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Introduction to Probability and Statistics II | MATH294 | Diğer Bölümlere Verilen Ders | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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MATH293 ve MATH293 |
Course Language | Turkish |
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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 Lecturer(s) |
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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;
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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 |
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1 | Sampling Concept, Parameter and Statistics, Sampling Distributions | pp.207-210 |
2 | Central Limit Theorem | pp.211-220 |
3 | Some Applications on the Sampling Distribution of Sample Mean and Sample Proportion | pp.228-233 |
4 | The Concept of Point and Interval Estimation, Unbiased and Consistent Estimators | pp.241-248 |
5 | Confidence Intervals for Population Mean and Population Proportion | pp.249-275 |
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, Level of Significance | pp. 300-305 |
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 | s. 361-365 |
12 | Goodness of Fitting Test , Independency Test, relating to the Structure of Data | pp. 482-488 |
13 | Relationship between two variables, Meaning of Covariance, Pearson Correlation Coefficient and its Significance | 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 |
16 | Final Exam |
Sources
Course Book | 1. D.H. Sanders, R. K. Simidt, Statistics, A First Course, 1990 |
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Other Sources | 2. -Elementary Statistics, A step by step Approach, Bluman, 2001 |
Evaluation System
Requirements | Number | Percentage of Grade |
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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 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | |
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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 | ||||
---|---|---|---|---|---|---|
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 |
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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 |