Download Faculty of Arts and Sciences - EMU

EASTERN MEDITERRANEAN UNIVERSITY
FACULTY OF ARTS AND SCIENCES
DEPARTMENT OF MATHEMATICS
2008-2009 SUMMER SEMESTER
COURSE CODE
MATH211
COURSE TITLE
Introduction to Statistics
COURSE TYPE
University Core (UC) - Mathematics
LECTURER(S)
Yücel Tandoğdu (Office AS356, Extension: 1004)
Kamil Kutoğlu
ASSISTANT
EMU CREDITS
(3,0,1) 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
Elementary Statistics, A Step by Step Approach, A. G. Bluman.
6th Edition, Isbn: 978007126703-8. McGraw-Hill 2008.
TIME TABLE
Grp. 1: Mdy-Tdy 12.30 –14.20, Wdy 8.30 – 10.20,
Thdy. 10.30-12.30
Tutorial:
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
2 Quizzes - %20, MT - %30, Final - %40, class
participation/H.work: 10%.
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’s 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.
Some combinatorial concepts, sample space, events, independence.
Discrete and continuous random variables.
2
Probability distribution, expectation, mean and variance
Some important probability distributions (Binomial, Hypergeometric,
Poisson, Normal, Normal approximation to the binomial). Quiz.1
3
Relationship between some theoretical distributions.
Data, types of data, data collection and validation (cleaning data).
Sampling techniques.
4
Statistical measures of central tendency (mean (arithmetic, weighted,
geometric, Harmonic), median, mode), variation and deviation from raw
data. (Midterm exam). Grouping and graphing data (histograms and ogive
curve). Estimation using the ogive curve.
5
Computation of central tendency (mean, median, mode) measures from
grouped data. Quartiles, interquartile range, deciles, percentiles.
6
Measure of variation, range, variance, standard deviation. Percent of data
falling within k std. dev. from mean. Measure of symmetry. (Quiz 2). Curve
fitting, method of least squares.
7
Linear regression, explained and unexplained variation. Coefficient of
determination and correlation coefficient. Estimation using linear regression
FINAL EXAMINATIONS (31 Aug. – 2 Sept.)
8
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
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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.