Ondokuz Mayıs Üniversitesi Bilgi Paketi - Ders Kataloğu

# Description of Individual Course Units

 Course Unit Code Course Unit Title Type of Course Year Semester ECTS IMÖ306 Statistics And Probability-II 927001 3 6 5
Level of Course Unit
First Cycle
Objectives of the Course
Learning Normal and Sampling Distributions
Name of Lecturer(s)
Öğr.gör. Kemal Özcan
Learning Outcomes
1. Students can learn about the normal distribution and apply them.
2. Students can learn about sampling distribution and apply them.
3. Students can learn about the knowledge and confidence intervals and apply them.
Mode of Delivery
Formal Education
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Recommended or Required Reading
Akdeniz, F. 1998; Olasılık ve İstatistik, Baki Kitapevi, Adana
Planned Learning Activities and Teaching Methods
Language of Instruction
Turkish
Work Placement(s)
None
Course Contents
Concept of normal distribution. The characteristics normal distribution. Areas under the standard normal curve. Approximantion of discrete distribution to normal. Approximation of binomial distribution to normal. Approximaton of Poisson distribution to the normal. Approxition of hypergeometric distribution to normal approach and its applications. A brief theoretical knowledge of sampling theory. The average of the sample distribution, sample distribution rates, the average difference between the sample distribution, sampling distributions of differences between proportions and applications. Brief theoretical knowledge about the theory of estimates, point estimates and confidence limits, the average for the confidence interval. Rates for the confidence intervals, standard deviations for the confidence intervals, the average difference between the confidence intervals, confidence intervals for differences between proportions and applied studies.
Weekly Detailed Course Contents
 Week Theoretical Practice Laboratory 1. Concept of normal distribution. 2. The characteristics normal distribution 3. Areas under the standard normal curve 4. Approximantion of discrete distribution to normal. 5. Approximation of binomial distribution to normal. 6. Approximaton of Poisson distribution to the normal. 7. Approxition of hypergeometric distribution to normal approach and its applications. 8. Mid-term exam 9. A brief theoretical knowledge of sampling theory. 10. The average of the sample distribution, sample distribution rates, the average difference between the sample distribution, sampling distributions of differences between proportions and applications. 11. The average of the sample distribution, sample distribution rates, the average difference between the sample distribution, sampling distributions of differences between proportions and applications. 12. Brief theoretical knowledge about the theory of estimates, point estimates and confidence limits, the average for the confidence interval. 13. Brief theoretical knowledge about the theory of estimates, point estimates and confidence limits, the average for the confidence interval. 14. Rates for the confidence intervals, standard deviations for the confidence intervals, the average difference between the confidence intervals, confidence intervals for differences between proportions and applied studies. 15. Rates for the confidence intervals, standard deviations for the confidence intervals, the average difference between the confidence intervals, confidence intervals for differences between proportions and applied studies. 16. End-of-term exam
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight (%) Midterm Examination 1 100 SUM 100 End Of Term (or Year) Learning Activities Quantity Weight (%) Final Examination 1 100 SUM 100 Term (or Year) Learning Activities 40 End Of Term (or Year) Learning Activities 60 SUM 100
Workload Calculation
 Activities Quantity Time(hours) Total Workload(hours) Midterm Examination 1 2 2 Final Examination 1 3 3 Attending Lectures 14 5 70 Problem Solving 10 5 50 SUM 125