Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
İST203APPLIED STATISTICSCompulsory236
Level of Course Unit
First Cycle
Objectives of the Course
Objective of this course is to provide the students make statistical inferences about a population by using the sample from the population.
Name of Lecturer(s)
Assoc. Prof. Dr. Sevcan DEMİR ATALAY
Learning Outcomes
1Knowledge of Random Sample Concept
2Knowledge of Sampling Distribution
3Knowledge of Properties of Estimators
4Knowledge of Comparing Estimators
5Knowledge of Methods of Point Estimation
6To distinguish single and two sample cases
7Knowledge of Statistical Hypothesis Concept
8Knowledge of Types of Errors Concept
9Knowledge of Hypothesis Testing with Respect to Parameters
10Application of Hypothesis Testing Process Steps
11Knowledge of Analysis of Variance Concept
12Knowledge of to construct One – Way Analysis of Variance Table
13To be able to interpret Results of Hypothesis Testing
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Estimation, hypothesis testing, analysis of variance, Goodness of fit test
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
0Contents, Textbooks Review: Probability Review of basic statistical issues
1Sampling and the Sampling Distribution of a StatisticProblem solving
2Estimation: Point Estimation and Properties of Point Estimators, Methods of Point Estimation Problem solving
3Tests of Parametric Statistical Hypotheses, Fundamental Concepts for Testing Statistical Hypotheses Problem solving
4Decision Outcomes, The Classical Approach to Statistical Hypothesis Testing Problem solving
5Types of Tests or Critical Regions, The Essentials of Conducting a Hypothesis TestProblem solving
6Hypothesis Test for μ Under Random Sampling from a Normal Population with Known Variance: p – value concept, Determining the Probability of a Type II Error β Problem solving
7Midterm Exam
8Hypothesis Tests for μ Under Random Sampling from a Normal Population with Unknown VarianceSolving the questions of midterm exam
9Hypothesis Tests for p Under Random Sampling from a Binomial Population, Hypothesis Tests for variance Under Random Sampling from a Normal PopulationProblem solving
10The Operating Characteristic and Power Functions of a TestProblem solving
11Hypothesis Tests for the Difference of Means When Sampling from Two Independent Normal Populations: Population Variances Equal and Known, Population Variances Unequal But Known, Population Variances Equal But Unknown, Population Variances Unequal and UnknownProblem solving
12 Hypothesis Tests for the Difference of Means When Sampling from Two Dependent Populations: Paired Comparisons, Hypothesis Tests for the Difference of Proportions When Sampling from Two Independent Binomial Populations, Hypothesis Tests for the Difference of Variances When Sampling from Two Independent Normal PopulationsProblem solving
13One Way Analysis of Variance (ANOVA)Problem solving
14 Goodness of Fit Test for Some Discrete Distributions: Binomial, Poisson, Goodness of Fit Test for Some Continuous Distributions: Uniform, NormalProblem solving
15Final Exam
Recommended or Required Reading
1. Advanced Statistics from an Elemantary Point of View, Michael J. Panik, Elsevier Academic Press, 2005 2. Applied Statistics and probability for Engineers, Douglas C. Montgomery, George C. Runger, Third Edition, John Wiley & Sons, 2003
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
SUM0
End Of Term (or Year) Learning ActivitiesQuantityWeight
SUM0
SUM0
Language of Instruction
English
Work Placement(s)
None
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination122
Final Examination122
Attending Lectures14456
Self Study14342
Individual Study for Mid term Examination13030
Individual Study for Final Examination14040
TOTAL WORKLOAD (hours)172
Contribution of Learning Outcomes to Programme Outcomes
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LO1    43   4  3    3     3
LO2  3 43   4  3    3     3
LO3    43   4  3    3     3
LO4  3 43   4  3    3     3
LO5  3 43   4  3    3     3
LO6    43   4  3    3     3
LO7     3   4  3    3     3
LO8     3   4  3    3     3
LO9  3 43   4  3    3     3
LO10     3   4  3    3     3
LO11    43   4  3    3     3
LO12                        
LO13                        
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
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