
Description of Individual Course UnitsCourse Unit Code  Course Unit Title  Type of Course Unit  Year of Study  Semester  Number of ECTS Credits  İŞL23112   Elective  1  1  6 
 Level of Course Unit  Second Cycle  Objectives of the Course  Data to make statistical evaluations, review, existence, basic accounts and formulations
 Name of Lecturer(s)   Learning Outcomes  1  To be able to define the properites of estimators and importance in the theory of statistical estimation
 2  To be able to define the populations according to the representative sample taken
 3  To be able to establish the relationship between probability distributions and hypothesis testing
 4  To be able to propose appropriate regression models the dependent and independent variables

 Mode of Delivery  Daytime Class  Prerequisites and corequisities    Recommended Optional Programme Components    Course Contents  Statistical estimation, hypothesis testing, chisquare test, analysis of correlation and regression, analysis of variance and indexes.
 Weekly Detailed Course Contents  
1  Confidence Intervals: For populations means , population is normal :population variance is known, Student t distribution, For populations means , population is normal :population variance is not known, For population proprotions.      2  Chispuare distribution, Confidence interval for population variance, population are normal, Confidence inreval for the difference of two populations means , populations are normal, Confidence interval for paired samples which are normal, Confidence interval for the difference of two independent sample means      3  Confidence interval for the difference of two populations proprotions. (large samples), Sample size for the confidence interval for population means , population is normal, population variance is known, samples size for the confidence interval for the population proprotion.      4  Hypothesis Testing: basic consepts, hypothesis testing for normal population mean: population variance is known, hypothesis testing for normal population mean: population variance is not known, ( small and large samples ), hypothesis testing for population proportion( large samples)      5  Hypothesis testing for normal population variance, hypothesis testing for two populations means: Paired Saples, Independent Samples, hypothesis testing for two population proportions, F distibution, hypothesis testing of two populations variances, calculation of type II error      6  Chi square goodness of fits test ( uniform, binom, poisson and normal),rxc independent test      7  Chi square goodness of fits test ( uniform, binom, poisson and normal),rxc independent test      8  Regression analysis: Simple linear regression, mean square estimation, the assumptions of linear regression      9  Analysis of variance for regression model, the estimation of coefficient of deternination and significant test, the estimation of correlaiton coefficient and significant test      10  One way and two way anova ( analysis of variance )      11  Index Number : A simple index, Chain Index, Time and Space Indexes, Fixed Based Index, VariableBased Index, an index to the other transition, main (base) Circuit Identification, indexes Average, Weighted Indexes, Some Important Indexes      12  Time Series Analysis and Estimating: A Time Series Components, Moving Averages, Determination of the Effect of Seasonal Using Moving Averages      13  Simple random sampling, Stratified sampling, cluster sampling, systematic sampling Introducing the Social Sciences Applications      14  Simple random sampling, Stratified sampling, cluster sampling, systematic sampling Introducing the Social Sciences Applications     
 Recommended or Required Reading  Anadolu University Publications  Planned Learning Activities and Teaching Methods   Assessment Methods and Criteria  
Midterm Examination  1  100  SUM  100  
Final Examination  1  100  SUM  100  Term (or Year) Learning Activities  40  End Of Term (or Year) Learning Activities  60  SUM  100 
 Language of Instruction  Turkish  Work Placement(s)   
 Workload Calculation 

Midterm Examination  1  1  1  Final Examination  1  1  1  Attending Lectures  1  20  20  Individual Study for Mid term Examination  8  10  80  Individual Study for Final Examination  8  10  80  
Contribution of Learning Outcomes to Programme Outcomes  LO1               LO2               LO3               LO4  4  4  4  4  3  3  3  3  3  3  3  4  3 
 * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High 



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