TYPE OF COURSE UNIT	Compulsory Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	2
SEMESTER	Fourth Term (Spring)
NUMBER OF ECTS CREDITS ALLOCATED	4
NAME OF LECTURER(S)	Professor Serpil Cula Assistant Professor Sinem Kozpınar
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Know and use sampling distributions. 2) Distinguish and interpret the difference between a point estimate and a confidence interval estimate. 3) Know how to use the test statistics and formulate null and alternative hypotheses for applications involving a single population means, proportions, variances. 4) Carry out hypotheses test and establish interval estimates for the difference between two population means for both independent and paired samples, two population proportion, two population variances. 5) Recognize applications that call for the use of analysis of variance, conduct and interpret post-analysis of variance pairwise comparions procedures. 6) Utilize the chi-square goodness of fit test to determine whether data from a process fit a specified distribution. 7) Set up a contingency analysis table and perform a chi-square test of independence. 8) Calculate and interpret the simple correlation between two variables and the simple linear regresision coefficients for a set of data. 9) Use SPSS program.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	Yes(TBF221)
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Sampling and sampling distributions; introduction to interference; point and interval estimation; hypothesis testing; small sample distributions (t, Chi-square, F); Chi-square goodness of fit test and cross tables; introduction to analysis of variance; regression are the main topics examined in this course.
COURSE CONTENTS	WEEK TOPICS 1st Week Sampling and Sampling Distributions 2nd Week Point and Confidence Interval Estimates 3rd Week Hypothesis Testing for Single Population Mean, Proprtion, Variance 4th Week Hypothesis Testing for Single Population Mean, Proprtion, Variance 5th Week Hypothesis Testing and Estimation for two population parameters 6th Week Hypothesis Testing and Estimation for two population parameters 7th Week One-Way Analysis of Variance 8th Week Midterm 9th Week Goodness of Fit Tests 10th Week Goodness of Fit Tests 11th Week Contiıngency Tables 12th Week Introduction to Linear Regression and Correlation Analysis 13th Week Introduction to Linear Regression and Correlation Analysis 14th Week Recap
RECOMENDED OR REQUIRED READING	1. S.Cula, F.Z. Muluk, Temel İstatistik Yöntemleri, Başkent Üniversitesi, İkinci Baskı 2010. 2. D.F. Groebner, P.W. Shannon, P. C. Fry, K. D. Smith, Business Statistics, Pearson Education 3. Bluman, Allan G. Elementary statistics: A step by step approach. New York, NY: McGraw-Hill Higher Education, 2009.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Quiz 2 10 Project 1 15 Total(%) 55 Contribution of In-term Studies to Overall Grade(%) 55 Contribution of Final Examination to Overall Grade(%) 45 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 1 1 Preparation for Quiz 2 5 10 Individual or group work Preparation for Final exam 1 45 45 Course hours 13 3 39 Preparation for Midterm exam 1 25 25 Laboratory (including preparation) Final exam 1 1 1 Homework Project 1 10 10 Total Workload 131 Total Workload / 30 4,36 ECTS Credits of the Course 4
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No