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Week
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Topics
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Study Metarials
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1
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Introduction
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K1.Lecture Note
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2
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Basic definitions
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K1.Lecture Note
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3
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Desired features of the estimations
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K1.Lecture Note
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4
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Definitions of sampling methods
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K1.Lecture Note
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5
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Simple random sampling
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K1.Lecture Note
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6
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Sample selection and table of random numbers
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K1.Lecture Note
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7
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The estimation of ratio of two variables
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K1.Lecture Note
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8
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The estimation of ratio of two variables
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K1.Lecture Note
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9
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Estimation of ration of units having constant features
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K1.Lecture Note
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10
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Stratified sampling
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K1.Lecture Note
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11
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Mean and sum estimations in stratified sampling, variance estimations and estimations of variances
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K1.Lecture Note
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12
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Stratified random sampling
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K1.ecture Note
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13
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Layer distribution of sample width: Optimal distrubiton,Neyman distrubition,equally distrubiton
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K1.Lecture Note
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14
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Exercise
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K1.Lecture Note
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Prerequisites
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-
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Language of Instruction
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Turkish
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Responsible
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Dr. Öğr. Üyesi Tolga ZAMAN
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Instructors
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-
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Assistants
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-
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Resources
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K1. Ders Notu
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Supplementary Book
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YK1.H. Çıngı, Örnekleme Kuramı, H. Ü. Fen Fak. Basımevi, Beytepe , Ankara, 1994
YK2.Steven T., 1992, Sampling, Wiley.
YK3.T. Yamane, Temel Örnekleme Yöntemleri, Çevirenler: A. Esin, M. A. Bakır, C. Aydın, E. Gürbüzsel, Literatür Yayınları, No:53, Ankara, 2000.
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Goals
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The Objective of this course is to teach what is sampling is and how it is applied,determine the number of samples and teach the methods of sampling.
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Content
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Basic concepts, first and second degree estimators, introduction of probabilistic and non-probabilistic sampling methods. The desired properties of the estimators, simple random sampling, and sample capture operation. Separation of the layers (sub-masses) of the mass to reduce the variance and sampling methods from these layers.
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Program Learning Outcomes |
Level of Contribution |
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1
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To have informations about conceptional, theoretical and applied statistics and and associates the concepts with each other.
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3
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2
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To collect, save and arrange the statistical data, builds the proper tables and graphics to summarize data
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2
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3
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To analyse the data, to able to determine suitable statistical method, to make more efficient inferences and forecasts for the future
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3
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4
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To design and analyse an experiment and interpreting the results
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5
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5
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To have the knowlegde about Mathematics and Economics
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-
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6
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To define statistics problems and develop suggestions by using statistical survey.
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-
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7
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To use the profiency knowlegde on interdiscipliner studies
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-
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8
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To have the ability of planing, managing and reporting of a project
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-
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9
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To use computer softwares and programmes for statistics methods.
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-
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10
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To have the ability of analythical thinking
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-
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11
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To have the individual study skills and be capable of independent decision-making
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-
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12
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To have the qualifications required for team work
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-
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13
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To follow developments in statistics field by using a foreign language and can be connected with their colleagues.
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-
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14
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To have scientific and ethnical values in data collection and interpretation in statistics dicipline.
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4
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