ISB104 Introduction to Statistics

6 ECTS - 4-0 Duration (T+A)- 2. Semester- 4 National Credit

Information

Unit FACULTY OF SCIENCE AND LETTERS
STATISTICS PR.
Code ISB104
Name Introduction to Statistics
Term 2020-2021 Academic Year
Semester 2. Semester
Duration (T+A) 4-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 4 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Label C Compulsory
Mode of study Uzaktan Öğretim
Catalog Information Coordinator Prof. Dr. SELAHATTİN KAÇIRANLAR
Course Instructor Prof. Dr. SELAHATTİN KAÇIRANLAR (Bahar) (A Group) (Ins. in Charge)


Course Goal / Objective

Learn the basic concepts of statistics, analysis and reviews statistical problems encountered

Course Content

Students will comprehend gauss distribution, sampling distributions, estimation, confidence intervals, hypothesis testing, power of test, chi-square test

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Learn some continuous distributions
LO02 Learn the methods of sampling and sample selection
LO03 Edit the data and analyzes Understand measures of central tendency and dispersion measures
LO04 understand sampling distributions and the properties
LO05 Learn and use methods of estimation
LO06 Apply hypothesis testing
LO07 make tests of the alignment and independence based on based on Chi-square


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 - Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 5
PLO02 - Emphasize the importance of Statistics in life 5
PLO03 - Define basic principles and concepts in the field of Law and Economics 0
PLO04 - Produce numeric and statistical solutions in order to overcome the problems 4
PLO05 - Use proper methods and techniques to gather and/or to arrange the data 5
PLO06 - Utilize computer systems and softwares 2
PLO07 - Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 3
PLO08 - Apply the statistical analyze methods 5
PLO09 - Make statistical inference(estimation, hypothesis tests etc.) 5
PLO10 - Generate solutions for the problems in other disciplines by using statistical techniques 5
PLO11 - Discover the visual, database and web programming techniques and posses the ability of writing programme 0
PLO12 - Construct a model and analyze it by using statistical packages 0
PLO13 - Distinguish the difference between the statistical methods 5
PLO14 - Be aware of the interaction between the disciplines related to statistics 4
PLO15 - Make oral and visual presentation for the results of statistical methods 5
PLO16 - Have capability on effective and productive work in a group and individually 4
PLO17 - Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs 1
PLO18 - Develop scientific and ethical values in the fields of statistics-and scientific data collection 5


Week Plan

Week Topic Preparation Methods
1 use pdf and properties of the normal distribution, calculate the mean and standard deviation , using the standard normal distribution table Source reading
2 Normal approximation to the binomial distribution, continuity correction and calculation of probability, the use of the table for given probability Source reading
3 Some continuous distributions and their characteristics, sampling and sample selection methods, Introduction to Data Analysis, Frequency Chart, Histogram, frequency polygon drawing Source reading
4 Measures of central tendency (mean, median, mode, geometric mean, harmonic mean) Source reading
5 Measures of Dispersion, Dal leaf display, Box drawing, Coefficient of Variation Source reading
6 Sampling Distributions and estimation, point estimation, estimators, mean and variance of the sample properties Source reading
7 Interval estimation for the population mean, t-distribution, (known and unknown, while sigma), chi-square, F distribution, sample size calculation Source reading
8 Mid-Term Exam Review the topics discussed in the lecture notes and sources
9 The range for the population variance estimation, interval estimation for the difference between two population means (mass variances are known, unknown) Source reading
10 estimation for the proportion of variance , interval estimation for the binomial parameter p, the interval for the difference of two binomial parameter estimation Source reading
11 Hypothesis tests, simple hypothesis testing, hypothesis testing for the population mean (variance of the population is known, unknown) Source reading
12 hypothesis testing for population the variance , hypothesis testing for the difference in the two group averages Source reading
13 Hypothesis test for the equality of population averages Source reading
14 Chi-square tests Source reading
15 Classification tables and problem-solving Source reading
16 Term Exams Review the topics discussed in the lecture notes and sources
17 Term Exams Review the topics discussed in the lecture notes and sources


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100


Student Workload - ECTS

Works Number Time (Hour) 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 12 12
Final Exam 1 28 28
Total Workload (Hour) 152
Total Workload / 25 (h) 6,08
ECTS 6 ECTS

Update Time: 29.04.2025 02:15