Course Unit Code  Course Unit Title  Type of Course Unit  Year of Study  Semester  Number of ECTS Credits  İST203  APPLIED STATISTICS  Compulsory  2  3  6 

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 
1  Knowledge of Random Sample Concept  2  Knowledge of Sampling Distribution  3  Knowledge of Properties of Estimators  4  Knowledge of Comparing Estimators  5  Knowledge of Methods of Point Estimation  6  To distinguish single and two sample cases  7  Knowledge of Statistical Hypothesis Concept  8  Knowledge of Types of Errors Concept  9  Knowledge of Hypothesis Testing with Respect to Parameters  10  Application of Hypothesis Testing Process Steps  11  Knowledge of Analysis of Variance Concept  12  Knowledge of to construct One – Way Analysis of Variance Table  13  To be able to interpret Results of Hypothesis Testing 

Mode of Delivery 
Face to Face 
Prerequisites and corequisities 
None 
Recommended Optional Programme Components 
None 
Course Contents 
Estimation, hypothesis testing, analysis of variance, Goodness of fit test 
Weekly Detailed Course Contents 

0  Contents, Textbooks
Review:
Probability
 Review of basic statistical issues   1  Sampling and the Sampling Distribution of a Statistic  Problem solving   2  Estimation:
Point Estimation and Properties of Point Estimators,
Methods of Point Estimation  Problem solving   3  Tests of Parametric Statistical Hypotheses,
Fundamental Concepts for Testing Statistical Hypotheses
 Problem solving   4  Decision Outcomes,
The Classical Approach to Statistical Hypothesis Testing
 Problem solving   5  Types of Tests or Critical Regions,
The Essentials of Conducting a Hypothesis Test  Problem solving   6  Hypothesis 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   7  Midterm Exam    8  Hypothesis Tests for μ Under Random Sampling from a Normal Population with Unknown Variance  Solving the questions of midterm exam   9  Hypothesis Tests for p Under Random Sampling from a Binomial Population,
Hypothesis Tests for variance Under Random Sampling from a Normal Population  Problem solving   10  The Operating Characteristic and Power Functions of a Test  Problem solving   11  Hypothesis 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 Unknown  Problem 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 Populations  Problem solving   13  One 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, Normal  Problem solving   15  Final 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  
Midterm Examination  1  100  SUM  100  
Final Sınavı  1  100  SUM  100  Term (or Year) Learning Activities  40  End Of Term (or Year) Learning Activities  60  SUM  100 
 Language of Instruction  English  Work Placement(s)  None 

Workload Calculation 