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Course Description Course Name : Statistical Theory I Course Code : BİS503 Course Type : Compulsory Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 5 Name of Lecturer(s) : Prof.Dr. ZELİHA NAZAN ALPARSLAN Learning Outcomes of the Course : Laerns the concept of a random variable and distribution of a random variable Calculates the Conditional Probability of Independent events, and applies the Bayes´ Theorem Explains the concepts of expected value, mean and variance Explains the distributions of Bernouilli trials, Binomial, Geometric and Poisson and their examples Understands the central limit theorem and its applications. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : BİS501 Mathematical Methods in Statistics I BİS502 Mathematical Methods in Statistics II Recommended Optional Programme Components : Mathematical background accepted to be sufficient by the instructor is the prerequisite for the course. Aim(s) of Course : Giving the basic statistical background needed for a degree in biostatistics Course Contents : Main concepts, main distributions, confidence intervals, sample size 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 Random variables, the algebra of sets Studying the related source reading 2 Probability, sampling Studying the related source, problem solving reading 3 The Bayes Theorem, independence Studying the related source, problem solving reading 4 Expected value, mean, variance Studying the related source, problem solving reading 5 Moment generating functions, Bernoulli trials, binomial distribution Studying the related source, problem solving reading 6 Geometric Distribution, Poisson Distribution Studying the related source, problem solving reading 7 EXAM 8 Continuous random variables, uniform distribution, exponential distribution Studying the related source reading 9 Gamma and Chi-square distributions Studying the related source, problem solving reading 10 Normal distribution Studying the related source, problem solving reading 11 Sums of random variables, distributions of functions of random variables Studying the related source, problem solving reading 12 The Central limit theorem, order statistics Studying the related source, problem solving reading 13 Confidence intervals Studying the related source, problem solving reading 14 Confidence intervals for means and proportions Studying the related source, problem solving reading 15 Sample size Studying the related source, problem solving reading 16/17 EXAM   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Hogg RV., Allen AT. Introduction to Mathematical Statistics  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 3 42     Mid-term Exams (Written, Oral, etc.) 1 3 3     Final Exam 1 3 3 Total Workload: 118 Total Workload / 25 (h): 4.72 ECTS Credit: 5