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  Course Description
Course Name : Statistical Theory II

Course Code : BİS504

Course Type : Compulsory

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Spring (16 Weeks)

ECTS : 4

Name of Lecturer(s) : Prof.Dr. ZELİHA NAZAN ALPARSLAN

Learning Outcomes of the Course : Knows the parameter estimation with normal models
Understands the concept of regression
Calculates the power of a hypothesis test
Does a binomail test and percentile tests
Does the Wilcoxon test and randomness tests
Does goodness-of- fit test of Kolmogorov Smirnov
Understands the concept of correlation and does correlation analysis

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : BİS503 Statistical Theory I

Recommended Optional Programme Components : None

Aim(s) of Course : Giving the basic statistical background needed for a degree in biostatistics

Course Contents : Estimation, regression, hypothesis testing, correlation

Language of Instruction : Turkish

Work Place : Class


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Estimation with normal models, means studying the related source reading
2 Estimation with normal models, means and variances studying the related source,problem solving reading
3 Point estimation, the functions of parameters studying the related source,problem solving reading
4 Regression studying the related source,problem solving reading
5 Hypothesis test: variance and differences between means studying the related source,problem solving reading
6 The power of a hypothesis test studying the related source,problem solving reading
7 Binomial tests, percentile tests studying the related source,problem solving reading
8 EXAM
9 the Wilcoxon test, randomness tests studying the related source reading
10 Kolmogorov_Smirnov goodness- of- fit test studying the related source,problem solving reading
11 Multivariate distributions, conditional distributions studying the related source,problem solving reading
12 The Correlation coefficient studying the related source,problem solving reading
13 Chi square distribution, testing probability distribution models studying the related source,problem solving reading
14 Analysis of variance studying the related source,problem solving reading
15 Likelihood ratio test, the decision theory studying the related source,problem solving reading
16/17 EXAM


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  Hogg RV., Tannis EA. Probability and Statistical Inference.
 Hogg RV., Tannis EA. Probability and Statistical Inference.
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 25
    Homeworks/Projects/Others 14 75
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Students design scientific research studies in order to give response to the problem arising from health and clinical sciences 0
2 Students provide consulting services by using effective communication skills; take part in research teamworks; defend the ethical rules. 0
3 Students collect data from research studies, analyze, and make inferences 0
4 Students design health survey, determine the sampling method and conduct the survey 0
5 Students knows the system of international classification of diseases, obtain and analyze hospital statistics. 0
6 Students select the appropriate statistical procedure for analysis , apply and make inferences. 3
7 Students use the necessary statistical packages for analysis, if necessary write and develop software. 0
8 Students select and use proper statistical procedure for diagnosis and in making inferences for the data in health and clinical medicine and provide consultance to clinicians in the field. 0
9 Students comprehends the fundamentals of statistical theory related to the field of health ( probability and bayesian biostatistics). 5
10 Students explain demographic terminologies and statistical methods in the field of health sciences. 0
11 Students understand and use medical terminology. 0
12 Students develop the ability of critical thinking, make a conclusion with a critical approach to the evidence 0
13 Students apply analytical procedure to frequently used survival data, multivariate procedure and regression techniques. 0
14 Students follow the latest development in medical informatics and employ frequently used tools and methods. 0
15 Students explain the fundamental terminologies in epidemiology, guide researchers conducting field survey and clinical studies, develop methodologies in determining disease risk factor and disease burden and advise for choosing proper diagnostic test. 0
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 14 2 28
Assesment Related Works
    Homeworks, Projects, Others 14 2 28
    Mid-term Exams (Written, Oral, etc.) 1 3 3
    Final Exam 1 3 3
Total Workload: 104
Total Workload / 25 (h): 4.16
ECTS Credit: 4