COURSE UNIT TITLE

: STATISTICAL AND FORMAL METHODS IN UNDERWATER ARCHAEOLOGY

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
SAA 5020 STATISTICAL AND FORMAL METHODS IN UNDERWATER ARCHAEOLOGY ELECTIVE 2 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR EYÜP MÜMTAZ TIRAŞIN

Offered to

UNDERWATER ARCHAELOGY

Course Objective

The aim of the course is to teach basic data analysis tools used in modern underwater archaeological research. Basic concepts will be discussed with emphasis on the role of quantitative methods in solving underwater archaeological problems.

Learning Outcomes of the Course Unit

1   Recognize basic data analysis tools in modern underwater archaeological research.
2   Become able to apply the quantitative methods in solving underwater archaeological problems.
3   Provide the background necessary for informed, critical reading of quantitative archaeological literature.
4   Provide the background needed for designing research projects that will generate data that can be productively analyzed using quantitative methods.
5   Demonstrate an ability to use of computers and other equipments such as GPS etc in managing and analyzing underwater archaeological data.
6   Demonstrate methods for conveying quantitative arguments in scholarly publications.
7   Be able to collect underwater archaeological data and use statistical programme packages.
8   Demonstrate critical thinking skills for underwater archaeology.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction Course Outline, Textbook, Homework and Reference Books. General Review of the Structure and Collection of Underwater Archaeological Data.
2 Underwater Archaeological Data Collection Types of Data, Types of Data Sources, Populations and Samples, Sampling Techniques in Underwater Archaeology, Sampling Designs, Why are Data Presentation Methods Important Preparing Data for Presentation.
3 Introduction to Statistical Programme Packages Introduction to MS Excel and SPSS Programme Packages, Statistical Modules, Data Import and Export, Some Exemplary Applications of Marine Archaeological Data.
4 Review of Descriptive Statistics Review of Descriptive Statistics, Measures of Central Tendency, Measures of Variability, Random Variables.
5 Review of Basic Discrete and Continuous Probability Distributions Basic Probability Definitions and Rules, Probability Distributions, Binomial Distribution, Poisson Distribution, Uniform Distribution, Normal Distribution, t distribution, Chi Square Distribution, F Distribution, Classical and Bayesian Approaches to Inference and Estimation.
6 Estimation Techniques Point and Interval Estimates of Population Parameters, Sample Size and Estimation Error, Applications with Marine Underwater Archaeological Data.
7 Review of Hypothesis Testing Hypothesis-Testing Steps and Procedures, Developing Decision Rules, Hypothesis Tests about a Population Mean, Hypothesis Tests about a Population Proportion, Type I and II Errors, Choosing the Significance Level in Hypothesis Testing, Hypothesis Tests about the Difference between Two Population Means, Hypothesis Testing for Means: Dependent and Independent Samples.
8 Midterm Exam
9 Analysis of Variance Hypothesis-Testing Steps and Procedures, Developing Decision Rules, Hypothesis Tests about a Population Mean, Hypothesis Tests about a Population Proportion, Type I and II Errors, Choosing the Significance Level in Hypothesis Testing, Hypothesis Tests about the Difference between Two Population Means: Dependent and Independent Samples.
10 Regression Statistical Background, Sample Regression Line, Analysis of Residuals, Coefficient of Simple Determination, Multiple Regression.
11 Correlation and Multivariate Methods Linear Equations, Transformations of Data for Fitting Linear Models, Correlation Coefficient, Partial and Multiple Correlation, Multivariate Distances, Principal Component Analysis, Factor Analysis, Cluster Analysis.
12 Analysis of Frequencies Tests for Goodness of Fit, Single Classification Goodness of Fit, Analysis of Two-Way Tables, Analysis Three- and Multi-Way Tables, Analysis of Proportions.
13 Midterm Exam
14 GPS and Coordinate Applications Demonstration of application of GPS, Coordinate Systems and Transformations, Introduction to GIS software.

Recomended or Required Reading

Textbook:

Drennan, R. D., 1996. Statistics for Archaeologists: A Common Sense Approach (Interdisciplinary Contributions to Archaeology). Plenum Press, New York, USA.
Shennan, S., 1997. Quantifying Archaeology (2nd edition). Edinburgh University Press, Edinburgh, UK.

Reference books:

Snedecor, G. W. and Cochran, W. G., 1989. Statistical Methods (8th edition).Iowa State University Press, Iowa, USA.
Sokal, R. R. and Rohlf, F. J., 2012. Biometry (4th edition). W. H. Freeman Co., New York, USA.

Planned Learning Activities and Teaching Methods

1. Lectures
Class lectures are carried out in a highly interactive format. The instructor prompts students for response to questions posed and solicits their thoughts on issues discussed. Lectures will focus on the transfer of basic statistical concepts and techniques rather than rigorous mathematics. Additional elaboration and illustration will be provided for better comprehension.

2. Class Discussions
In-class assignments and homework assignments are the basis of problems to be solved in classroom discussions. Individual participation by students in classroom discussions will be strongly encouraged.

3. Computer Applications
In the laboratory component, MS Excel and SPSS (a software for statistical computing and graphics) will be introduced to perform analyses of data and to produce graphics.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 MTE 1 MIDTERM EXAM 1
3 MTE 2 MIDTERM EXAM 2
4 FIN FINAL EXAM
5 PAR PARTICIPATION
6 FCG FINAL COURSE GRADE ASG * 0.15 + MTE 1 * 0.175 + MTE 2 * 0.175 + FIN * 0.40 + PAR * 0.10
7 RST RESIT
8 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.15 + MTE 1 * 0.175 +MAKRMTE 2 * 0.175 + RST * 0.40 + PAR * 0.10


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

1. Regular attendance is essential for satisfactory completion of this course. Statistics is a cumulative subject and each lesson day builds on the previouslessons' material. If you have excessive absences, you cannot develop to your fullest potential in the course.
2. The student is responsible for all homework assignments, changes in assignments or other verbal information given in the class, whether in attendance or not.
3. Homework assignments must be delivered at the beginning of the lesson on the date they are due.
4. Students are required to have their own calculator for this course.

Contact Details for the Lecturer(s)

Dr. E. Mümtaz TIRAŞIN
Dokuz Eylül University, Institute of Marine Sciences and Technology,
Inciraltı 35340, Balçova - Izmir.
Phone:(+90) 232 2785565 /165
Fax: (+90) 232 2785082
E-mail: mumtaz.tirasin@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Preparing assignments 10 4 40
Preparations before/after weekly lectures 12 7 84
Preparation for midterm exam 2 9 18
Preparation for final exam 1 14 14
Midterm 2 2 4
Final 1 4 4
TOTAL WORKLOAD (hours) 188

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.1243311222111
LO.2443111133111
LO.3552111132112
LO.4453211343122
LO.5543211355444
LO.6442311122232
LO.7543311122132
LO.8443332223244