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Course Description Course Name : Statistics Course Code : MT 262 Course Type : Compulsory Level of Course : First Cycle Year of Study : 2 Course Semester : Spring (16 Weeks) ECTS : 5 Name of Lecturer(s) : Prof.Dr. SADULLAH SAKALLIOĞLU Learning Outcomes of the Course : Learns some continuous distributions. Knows the methods of sampling and sample selection. Is able to analyze the data. Understands measures of central tendency and dispersion measures. Knows and understands sampling distributions and their properties. Learns and uses methods of estimation. Is able to apply hypothesis testing. Is able to carry out Chi-square tests for independence and goodness of fits. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : To understand some continuous distributions, to teach sampling and sample selection methods, to analyze the data, measures of central tendency and dispersion are given, to teach the methods of sampling distributions and estimation, hypothesis tests, to apply tests based on chi-square tests. Course Contents : Gauss distribution, sampling distributions, estimation, confidence intervals, hypothesis testing, power of test, chi-square test Language of Instruction : Turkish Work Place : Faculty of Arts and Sciences Annex Classrooms   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Normal Distribution, Standard Normal Distribution, Normal Approximation to the Binomial Distribution Required readings Lecture, discussion and problem-solving 2 Some Important Continuous Random Variables and Distributions, Problem Solving Required readings Lecture, discussion and problem-solving 3 Simple random sampling, systematic sampling, stratified sampling, cluster sampling Required readings Lecture, discussion and problem-solving 4 Preparation of data, Frequency distribution, Graphical Representations Required readings Lecture, discussion and problem-solving 5 Measures of Central Tendency, Comparison between Central Tendency Required readings Lecture, discussion and problem-solving 6 Measures of Dispersion, Coefficient of Variation, Problem Solving Required readings Lecture, discussion and problem-solving 7 Some Properties of Sample Mean and Variance, Point Estimation, Confidence Interval Required readings Lecture, discussion and problem-solving 8 Mid-term exam Review the topics discussed in the lecture notes and sources Written exam 9 Determination of Sample Size, Confidence interval for variance Required readings Lecture, discussion and problem-solving 10 Confidence Interval for the Difference Between Two Means, Confidence Interval for the Difference Between Two Proportions Required readings Lecture, discussion and problem-solving 11 Hypotheses testing for mean, hypotheses testing for variance, hypothesis testing for equality of variances Required readings Lecture, discussion and problem-solving 12 Hypotheses testing for the Difference Between Two Means, hypotheses testing for the Difference Between Two Proportions Required readings Lecture, discussion and problem-solving 13 Goodness of fit tests Required readings Lecture, discussion and problem-solving 14 Chi-Square Test for Independence Required readings Lecture, discussion and problem-solving 15 Chi-Square Test for Independence Required readings Lecture, discussion and problem-solving 16/17 Final exam Review the topics discussed in the lecture notes and sources Written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Akdeniz,F. (2010). Olasılık ve İstatistik , Nobel Kitabevi, Adana.  Gürsakal, N. (1997). Bilgisayar Uygulamalı İstatistik I,II, Marmara Kitabevi,Bursa.  McClave,J.T., Dietrich,F.H. And Sincich,T. (1997). Statistics,Prentice-Hall,Inc.  Spiegel, M.R.(1975). Theory and Problems of Probability and Statistics, Schaum´s Outline Series, McGraw-Hill. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 100     Homeworks/Projects/Others 0 0 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 Is able to prove Mathematical facts encountered in secondary school. 3 2 Recognizes the importance of basic notions in Algebra, Analysis and Topology 2 3 Develops maturity of mathematical reasoning and writes and develops mathematical proofs. 5 4 Is able to express basic theories of mathematics properly and correctly both written and verbally 3 5 Recognizes the relationship between different areas of Mathematics and ties between Mathematics and other disciplines. 5 6 Expresses clearly the relationship between objects while constructing a model 3 7 Draws mathematical models such as formulas, graphs and tables and explains them 3 8 Is able to mathematically reorganize, analyze and model problems encountered. 4 9 Knows at least one computer programming language 4 10 Uses effective scientific methods and appropriate technologies to solve problems 1 11 Knows programming techniques and is able to write a computer program 0 12 Is able to do mathematics both individually and in a group. 0 13 Has sufficient knowledge of foreign language to be able to understand Mathematical concepts and communicate with other mathematicians 0 14 In addition to professional skills, the student improves his/her skills in other areas of his/her choice such as in scientific, cultural, artistic and social fields 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 4 56     Out of Class Study (Preliminary Work, Practice) 14 4 56 Assesment Related Works     Homeworks, Projects, Others 0 0 0     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 15 15 Total Workload: 137 Total Workload / 25 (h): 5.48 ECTS Credit: 5