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EASTERN MEDITERRANEAN UNIVERSITY
FACULTY OF ARTS AND SCIENCES
DEPARTMENT OF MATHEMATICS
2011-2012 FALL SEMESTER
COURSE CODE
MATH211
COURSE TITLE
Introduction to Statistics
COURSE TYPE
University Core (UC) - Mathematics
LECTURER(S)
Yücel Tandoğdu (Office AS356, Extension: 1004)
ASSISTANT
Hamed Sadeghi (AS349, Extension: 1011)
EMU CREDITS
(3,1,0) 3
ECTS CREDITS
6
PREREQUISITES
MATH112
COREQUISITES
None
WEB LINK
http://brahms.emu.edu.tr/tandogdu
TEXTBOOK
Statistics. Schaum’s Outline Series. M. R. Spiegel, L. J. Stephens. 3rd Edition.
isbn: 007060281-6, McGraw Hill, 1999.
OTHER REFERENCES
Miller and Freund’s Probability and Statistics for Engineers, R. A. Johnson. 7 th
Edition, Isbn: 0131278401. Prentice Hall 2005.
TIME TABLE
Grp. 1: WEDNESDAY 10.30 –12.20. FRIDAY 8.30 – 09.20
Tutorial: Friday 9.30 – 10.20
Y. Tandoğdu: FRIDAY 10.30 – 11.20.
OFFICE HOUR
AIMS & OBJECTIVES
To give the student some basic ideas about statistics. This starts with some
concepts of probability, conditional probability and independence, some
important discrete and continuous probability distributions. Statistical part will
include use of data both in graphical and theoretical ways to estimate
population parameters, some basics about regression analysis and hypothesis
testing.
.
CATALOGUE DESCRIPTION Variables and Graphs; Statistic, population and sample, inductive and
descriptive statistics. Variables; Discrete and continuous. Frequency
Distributions; General rules of forming frequency distributions. Histograms and
frequency polygons. Measures of central tendency; the arithmetic mean, the
median and the mode. Harmonic and geometric mean, root mean square,
quartiles deciles and percentiles. Measures of dispersion; the range, the mean
deviation, the semi-interquartile range, the 10-90 percentile range, the standard
deviation, the variance. Elementary probability theory; conditional probability,
probability distributions, expectation, relation between population, sample,
mean and variance. Some discrete probability distributions; binomial and
normal distributions, poisson distribution, multinomial distribution. Elementary
sampling theory. Curve fitting and method of least squares.
GRADING CRITERIA
Quizzes (best 2 out of 3) - %20, MT - %30, Final - %40, class
10%.
participation:
METHOD OF ASSESSMENT
85–100 (A); 80–84 (A-); 75–79 (B+); 70–74 (B); 66–69 (B-);
63–65 (C+); 60–62 (C); 57–59 (C-); 54–56 (D+); 50–53 (D);
45–49 (D- /FAIL); 0-44 (F/FAIL). These intervals are subject to change based
on the overall achievement in the course.
TEACHING METHOD
Lectures, tutorials and assignments.
RELATION TO OTHER COURSES. The course is essential for the students to successfully follow topics in the
junior and senior classes that require some background in probability and statistics.
GENERAL LEARNING OUTCOMES
On successful completion of this course, all students will have developed knowledge and understanding of:
 Basic probability concepts,
 Conditional probability and independence of events
 Some important discrete and continuous probability distributions.
 Sample and population concepts, raw data, graphing data and drawing conclusions from processed
data
 Some introductory concepts of estimation of population parameters using sample statistics
On successful completion of this course, all students will have developed their skills in:
 Probability related matters and their practical use,
 Essential statistical knowledge towards statistical decision making.
On successful completion of this course, all students will have developed their appreciation of and respect for
values and attitudes regarding the issues of:
 Probability’ role in life,
 Decision making based on statistical knowledge,
 Application areas of probability and statistics in their professions.
COURSE OUTLINE
WEEK TOPICS
1
Review of some mathematical concepts needed in probability and statistics.
2
Some combinatorial concepts, sample space, events, independence
Probability distribution, expectation, mean and variance. Quiz. 1
3
4
Some important probability distributions (Binomial, Hypergeometric,
Poisson, Normal, Normal approximation to the binomial).
5
Relationship between some theoretical distributions.
Data, data collection and validation. Quiz.2
6
7
Grouping and picturing data.
MIDTERM WEEK. (3 - 13 November)
8
9
Statistical measures of central tendency
10
Computation of central tendency measures from raw and grouped data
Measure of variation, range, variance, standard deviation. Quiz.3
11
12
Curve fitting, method of least squares
13
Linear regression, explained and unexplained variation.
14
Estimation using linear regression
FINAL EXAMINATIONS (3 - 18 January)
15
ACADEMIC HONESTY
Copying from others or providing answers or information (written or oral) to others is cheating. Copying from
another student’s paper or from another text without written acknowledgement is plagiarism. According to
University’s bylaws cheating and plagiarism are serious offences resulting in a failure from exam or project
and disciplinary action (which includes an official warning or/and suspension from the university for up to one
semester).
IMPORTANT NOTES



Attendance is compulsory. Any student who has poor attendance and/or misses an examination without
providing valid excuse will be given NG grade.
Students missing an examination should provide a valid excuse within three days following the
examination they missed. One make-up examination will be given at the end of the semester after the
final examination period. No make-up will be given for missed quizzes.
Use of Mobile telephones in the class or during examination is prohibited.