1	Course Title:	STATISTICS
2	Course Code:	MAK2037
3	Type of Course:	Compulsory
4	Level of Course:	First Cycle
5	Year of Study:	2
6	Semester:	3
7	ECTS Credits Allocated:	3
8	Theoretical (hour/week):	2
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. MUHSİN KILIÇ
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:	mkilic@uludag.edu.tr
18	Website:
19	Objective of the Course:	Students are expected to learn a basic understanding of data analysis and statistical concepts, in order to be able to think critically about the quantitative information they encounter every day.
20	Contribution of the Course to Professional Development	Distinguish between different types of data. Interpret examples of methods for summarising data sets, including common graphical tools (such as boxplots, histograms and stemplots) and summary statistics Identify the features that describe a data distribution.

21

Learning Outcomes:

1 Presents the data by visualizing them with graphic methods;; 2 Can sort the data numerically with the help of various statistical parameters,; 3 Able to know the basic concepts of probability.; 4 Uses curve fitting techniques for given data.; 5 Knows sampling type and techniques in data collection.; 6 Can estimate population mean and sample proportions; 7 Can use test hypothesis methods;

22	Course Content:

Week	Theoretical	Practical
1	Defining general statistical concepts such as variable, sample, population Classification of variables Graphical representation of quantitative variables and interpretation of graphs Relative frequency histograms
2	Defining numerical parameters such as arithmetic mean, median, mode in which the center is measured and interpreting the distributions by comparing the parameters Defining numerical parameters that determine the variability of the distribution, such as variance and standard deviation. Box representation method
3	Determining the direction and direction of the relationship between variables by defining the correlation coefficient Introduction of the linear curve fitting (regression) method
4	Introducing the basic concepts of probability The use of count rule and product rule in calculating probabilities Permutation and combination Conditional probability, aggregate probability and Bayes' laws
5	Binomial probability distributions Poisson random variable Hypergeometric probability distribution
6	Reading the standard normal distributions and probabilities from the Z table Normal distribution approximation to the binomial distribution
7	Sample question solution
8	Sample question solution
9	Central limit theorem Calculation of probabilities for sample mean Statistical process control for normal distribution and binomial distribution
10	Estimation of population mean using confidence interval method Estimating the success rate of the binomial distribution using the confidence interval method Estimation of the difference between two means using the confidence interval method Estimating the difference between two success rates using the confidence interval method
11	Large sample (n> 30) hypothesis testing method One-way and two-way hypothesis tests Types of errors in test statistics method
12	Large sample hypothesis testing of the difference between two means Hypothesis testing in binomial probability distributions Big sample hypothesis testing of the difference between the two success rates
13	Small sample (n <30) hypothesis testing method Completing the t distribution and reading the probabilities from the t table Estimation of the population mean by small sample hypothesis testing Estimating the difference between the small sample hypothesis test and the two population means Paired difference tests
14	Sample question solution

23	Textbooks, References and/or Other Materials:	Introduction to probability and statistics lecture notes, solved questions and slides, Prof. Dr. Muhsin Kılıç. Statistics, 3rd Ed., M.R. Spiegel, l.j. Stephens. Schaums Outline Series Mc Graw-Hill, New York, 1999. Applied Statistics, S. Özer, Filiz Kitapevi, İstanbul 1996. Introduction to Probability and Statistics, 3rd Ed., Wadsworth, California, 1971.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	40
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	60
Total	2	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Measurement and evaluation are performed according to the Rules & Regulations of Bursa Uludağ University on Undergraduate Education.
Information

25

ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	2	28
Practicals/Labs	0	0	0
Self Study and Preparation	14	4,5	63
Homeworks, Performances	0	0	0
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	1	1	1
Others	0	0	0
Final Exams	1	1	1
Total WorkLoad			93
Total workload/ 30 hr			3,1
ECTS Credit of the Course			3

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 PQ13 PQ14 LO1 5 3 0 0 0 0 0 0 0 0 0 0 0 0 LO2 5 3 3 0 0 0 0 2 0 2 0 2 0 2 LO3 4 3 3 2 5 2 2 2 0 2 0 2 0 1 LO4 5 5 3 3 2 2 1 3 0 1 1 2 1 2 LO5 5 3 2 2 1 1 1 3 0 1 1 1 1 1 LO6 3 3 2 1 0 0 0 0 0 1 1 1 1 1 LO7 4 3 2 4 5 1 2 2 0 1 1 1 1 1

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High