EMU - FACULTY OF ARTS AND SCIENCES
DEPARTMENT OF MATHEMATICS
COURSE DESCRIPTION
2015 - 16 Fall
Course Code and Title: MATH523: Statistical Data Analysis
Instructor:
Yücel Tandoğdu (Office: AS252, ext. 1004)
Textbook:
Probability and Statistics for Engineers and Scientists. R. E.
Walpole, R. H. Myers, S. L. Myers. 8th Edition. Prentice Hall,
2007.
Mathematical Statistics with Applications. J. F. Freund. 7th
Edition. Prentice Hall, 2004.
Other References:
TIME TABLE
Lecture hrs.
Office hrs.
Friday: 13.30 -16.20, Place: ASG02.
Friday: 10.30 -11.20
Course Objectives
Collecting data and analyzing is a common practice in all fields of scientific study. In this course the
data analysis will be studied at a level that will enable the student or researcher to understand the
theoretical background as well as its application.
OUTLINE
Week
1
Start Date
05/10 /2015
2
12/10/2015
3
19/10/2015
4
26/10/2015
5
02/11/2015
6
09/11/2015
Topics
Brief Review of Some Important Probability Concepts:
Random functions, probability distribution and probability
density function, independence of random variables.
Expectation and moments, moment generating functions.
Sampling Methods. Random, Stratified Random, Cluster,
Systematic sampling methods. Data Description. Data
validation, graphical representation of data.
Sample statistics. mean, median, mode, variance, and
standard deviation; sampling distribution of means and
variances. t,  2 , and F distributions.
HW/Prj 1: Collecting data from your research topic and
analyzing. Due date: 06/11/2015
Estimation Problems: Statistical inference, Classical methods
of estimation. Single Sample; Estimating the mean, standard
error of a point estimate, tolerance limits, estimating a
proportion, estimating the variance.
Estimating the difference between two means, paired
observations, estimating the difference between two
7
16/11/2015
8
23/11/2015
9
10
07/12/2015
11
14/12/2015
12
21/12/2015
13
28/12/2015
14
02/01/2016
17
12-27Jan 2016
proportions, estimating the ratio of two variances. Bayesian
methods of estimation. Maximum likelihood estimation.
HW/Prj 2: Use of research topic related data in estimating
necessary parameters and commenting on findings. Due date:
20/11/2015
Hypothesis Tests: Important points in setting a hypothesis.
Errors in hypothesis testing and how to minimize them. Power
of a test.
Single sample; tests concerning a single mean when the
variance is known and when it is unknown. Relationship to
confidence interval estimation. Two samples; tests on two
means, choice of sample sizes for testing means.
P value and its use in decision making. One sample test on
single proportion. Two sample tests on two proportions. One
and two sample tests concerning variances. Goodness of fit
tests. Test for independence (categorical data), test for
homogeneity, test for several proportions. Two sample case
study.
HW/Prj 3: Use of research topic related data in an integrated
hypothesis testing and related conclusions. Due date:
18/12/2015
Linear regression. Properties of the Least Squares
Estimators, inferences concerning the regression coefficients,
confidence interval for the regression parameters, confidence
and prediction interval for the response variable Y x .
Choice of a regression model, analysis of variance approach,
test for linearity of regression
Multiple linear regression. Estimating the coefficients, linear
regression using matrices, properties of the least squares
estimators
Inferences in multiple linear regression. HW/Prj 4: Use of
research topic related multivariate data in regression analysis.
Due date: 08/01/2016.
FINAL EXAM PERIOD.
GRADING
Midterm examination : 30%
Homework/Project
: 30%
Final examination
: 40%