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SÜRMENE FACULTY of MARINE SCIENCES / DEPARTMENT of FISHERIES TECHNOLOGY ENGINEERING

Course Catalog
http://www.ktu.edu.tr/baltekmuh
Phone: +90 0462 7522805
SDBF
SÜRMENE FACULTY of MARINE SCIENCES / DEPARTMENT of FISHERIES TECHNOLOGY ENGINEERING /
Katalog Ana Sayfa
  Katalog Ana Sayfa  KTÜ Ana Sayfa   Katalog Ana Sayfa
 
 

BTM2012Bioistatistics2+0+0ECTS:2
Year / SemesterSpring Semester
Level of CourseFirst Cycle
Status Compulsory
DepartmentDEPARTMENT of FISHERIES TECHNOLOGY ENGINEERING
Prerequisites and co-requisitesNone
Mode of DeliveryFace to face
Contact Hours14 weeks - 2 hours of lectures per week
LecturerProf. Dr. Ertuğ DÜZGÜNEŞ
Co-LecturerAssoc. Prof. Dr. Hacer SAĞLAM
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
Provide basic principles of experimental design, data collection and evaluation methods before the intensive use of statistical software to get better outputs and prevent misunderstandings during the analysing stage of the research data.. Correlation and regression. χ 2 test, t test, and ANOVA, time series and indices.
 
Learning OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
LO - 1 : gain insight about population-sample, parameter-statistic relationships in fisheries and oceanography.3,12,13,161,3
LO - 2 : construct hypothesis, design scientific experiments, collect and present data.3,12,13,161
LO - 3 : apply measure of central tendency and dispersion for different types of statistical distributions.3,12,13,161,3
LO - 4 : recognise data coming from such distributions as normal, binomial and poisson, sampling (means, difference of means, ratios) and test distributions (z, t, chi-square, F) in order to applye them in their professional field.3,12,13,161
LO - 5 : test hypothesis using Z, Chi-square and variance analysis.3,12,13,161
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome

 
Contents of the Course
Variables and graphs. Frequency distributions. Measures of central tendency (mean, mode, median, etc. ) . Measure of dispersion (range, mean and standard deviation. Elementary probability theory. Normal, binomial and poisson distributions. Elementary sampling theory. Statistical estimation theory, statistical decision theory and tests of hypothesis and significance. Small sampling theory. Curve fitting and the methods of least squares
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Introduction to statistics, terms and definitions, population and sample, sample size and sampling methods, discrete and continuous variables, tables and graphs.
 Week 2Raw data, arrays, frequency distributions, class intervals and class limits, class boundaries, the size of class intervals, class mark, general rules for forming frequency distributions, histograms and frequency polygons, relative and cumulative frequency distributions.
 Week 3Measure of central tendency, arithmetic mean, weighed arithmetic mean, median, mode, empirical relation between mean median and mode, geometric mean, harmonic mean, properties of different measures.
 Week 4Measures of dispersion, range, mean deviation, variation, standard deviation, coefficient of variation, properties of variance, Sheppard's correction for variance.
 Week 5Elementary probability theory, classical and statistical definition, probability theorems, independent and dependent events, conditional probability, probability distributions, mathematical expectation, factorial n, permutations, combinations.
 Week 6Classical populations, normal distributions, binomial distributions, poisson distributions.
 Week 7Relationship between variables, definitions, regresion lines and coefficients, estimation, correaltion coefficient, lineer and non-lineer relationships, computation, least square method.
 Week 8Mid-term exam
 Week 9Sampling distributions, definitions, distribution of means, distribution of difference of means, distribution of proportions.
 Week 10Standart error, standart error of mean, difference of means, correlation and regression coefficients.
 Week 11Test distributions, Z, t, Chi-square, F distributions, estimation of parameters, confidence intervals.
 Week 12Problem solving exercises
 Week 13Hypothesis testing, Type I and Type II errors, significance levels, Z, Student's t, chi-square tests and tables.
 Week 14Analysis of variance, mathematical model and analyses, means of squares, F test, computations evaluation of analyses, determination of different groups, least significance, Duncan method.
 Week 15Determination of different groups, least significance, Duncan method.
 Week 16End-term exam
 
Textbook / Material
1Düzgüneş, O., Kesici, T., Gürbüz, F. 1993. İstatistik Metodları (Statistical Methods). A.Ü. Ziraat Fak. Yay. No:1291, 218 pp.
2Spiegel, M.R.1972. Theory and Problems of Statistics. Schaum
 
Recommended Reading
1s Outline Series. McGraw-Hill Book Company, 359 pp.
2Yıldız, N., Bircan, H. 1994. Araştırma ve Deneme Metodları. Atatürk. Ün. Zir. Fak. No 305. Erzurum. 266 s.
3Düzgüneş, O. 1963. Bilimsel Araştırmalarda İstatistik Prensipleri ve Metodları. EÜ. Matbaası.375 s.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 8 10/04/2018 50
End-of-term exam 16 31/05/2018 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 14 42
Sınıf dışı çalışma 2 14 28
Arasınav için hazırlık 5 2 10
Arasınav 2 1 2
Kısa sınav 2 1 2
Dönem sonu sınavı için hazırlık 15 1 15
Dönem sonu sınavı 2 1 2
Total work load101