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CE21 ENGINEERING STATISTICS Course Syllabus
Second Semester, AY 2014-2015
COURSE DESCRIPTION Frequency distribution, averages, measures of
variation, simple probability theory, theory of large and small
sampling. Correlation and applications in engineering. PREREQUISITE
: Math 53 Course Credit : 3.0 units COURSE GOALS After completing
this course, a student must be able to
(1) use the concepts of probability to guide in making
statistical inferences (2) apply several common probability
distributions to relevant scientific and engineering problems (3)
use statistical tools such as estimation, regression and hypothesis
testing to as decision tools
REFERENCES (1) Principles of statistics for engineers and
scientists by WC Navidi (Main Reference) (2) Probability and
Statistics for Scientists and Engineers by Walpole et al (3)
Probability Concepts in Engineering (Emphasis on Applications to
Civil and Environmental Engineering)
LECTURER
Resurreccion, Augustus C. PhD Environment and Energy Engineering
Group Construction Engineering and Management Group
Consultation Time/Place: WF 9:00-11:00AM and F 1:00-5:00 PM ERDT
Office MH 203 Melchor Hall
Email: [email protected] Phone: 09285526442
GENERAL CLASS POLICIES
Attendance Attendance is required. A student is considered late
if he/she arrives in between 9:15 and 10:00 AM. He/She is
considered absent if he/she arrives after 10:00 AM. Three instances
of tardiness will be counted as one absence. A student who incurs 6
unexcused absences will be given a grade of 5.0 if he/she does not
drop before April 27, 2015. Course Requirements Students will be
evaluated on the basis of class participation, long exams and group
project/case study.
Class Participation (CP). Students are expected to actively
participate in class discussions. Class participation
includes attendance, recitation, homework, problem sets and
quizzes (or even a small activity outside the classroom).
Long Exam (LE). There will be FOUR long exams. Students are
required to submit answer sheets on the first day of the class.
Note: Complaints will be entertained for a period of one week after
the exam result has been returned.
Final Exam (FE). Final exam covering all topics discussed will
be given at the end of the semester. Exemption from taking the
final exam: a. All long exams are passing (i.e., at least 60% score
in all long exams), and b. The average of the four long exam scores
is at least 76%.
Note on Intellectual Dishonesty Any form of intellectual
dishonesty (i.e cheating, plagiarism) will be penalized with a
grade of 5.0 and will be dealt will full force of the law
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Grading System The students final grade will be computed using:
If the student is exempted from taking the final exam, the class
standing is computed as:
Class Standing = Average of four long exam scores If the student
takes the final exam, the class standing is computed as:
Class Standing = 0.10 CP + 0.60 LE + 0.30 FE Final exam shall be
subsitituted for a missed exam, only those with a valid reason.
Only one long exam can be substituted. The student must inform the
instructor in writing and submit the letter to the instructor
together with supporting documents (e.g., certification from a
medical doctor). Equivalent Grading Scale COURSE OUTLINE
Overview and Descriptive Statistics Lecture Date: January 26,
2015 Populations, Samples and Processes Pictorial and Tabular
Methods in Descriptive Statistics Measures of Location Measures of
Variability Probability Lecture Date: February 2 and 9, 2015 Sample
Spaces and Events Axioms, Interpretations, and Properties of
Probability Counting Techniques Conditional Probability Bayes
Theorem; Independence
FIRST LONG EXAM (February 14, 2015 Saturday 9-11 am)
Random Variables and Probability Distributions Lecture Date:
February 16 and 23, 2015 Concept of a Random Variable Discrete and
Continuous Random Variables Probability Distributions Independence
Mean, Variance, Covariance and Correlation Linear Combinations of
Random Variable Chebyshevs Theorem Joint Probability Distributions
Marginal Distributions Conditional Probability Distribution
Discrete Probability Distribution Lecture Date: March 2 and 9 2015
The Binomial Probability Distribution Hypergeometric, Geometric and
Negative Binomial Distributions The Poisson Probability
Distribution Continuous Probability Distribution Lecture Date:
March 16 and 23, 2015 Normal Distribution Lognormal Distribution
The Exponential and Gamma Distributions Other Continuous
Distributions Probability Plots Central Limit Theorem
SECOND LONG EXAM (March 28, 2015 Saturday 9-11 am)
Final Grade Equivalent Grade Final Grade Equivalent Grade92-100
1.00 72-below 76 2.25
88-below 92 1.25 68-below 72 2.5084-below 88 1.50 64-below 68
2.7580-below 84 1.75 60-below 64 3.0076-below 80 2.00 Below 60
5.00
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Point and Interval Estimation for a Single Sample Lecture Date:
March 30 and April 6, 2015 Point Estimation Large-Sample Confidence
Intervals for a Population Mean Confidence Intervals for
Proportions Small-Sample Confidence Intervals for a Population Mean
Prediction Intervals and Tolerance Intervals Hypothesis Tests for a
Single Sample Lecture Date: April 13 and 20, 2015 Large-Sample
Tests for a Population Mean Drawing Conclusions from the Results of
Hypothesis Tests Tests for a Population Proportion; Small-Sample
Tests for a Population Mean The Chi-Square Test Fixed-Level Testing
Power Multiple Tests
THIRD LONG EXAM (April 25, 2015 Saturday 9-11 am) Inferences for
Two Samples Lecture Date: April 27 and May 4, 2015 Large-Sample
Inferences on the Difference Between Two Population Means
Inferences on the Difference Between Two Proportions Small-Sample
Inferences on the Difference Between Two Means Inferences Using
Paired Data F Test for Equality of Variance Regression and
Correlation Lecture Date: May 11 and 18, 2015 The Simple Linear
Regression Model Estimating Model Parameters Correlation
FOURTH LONG EXAM (May 20, 2015 Wednesday 5-7 pm) FINAL EXAM
(Tentative: May 27, 2015 Wednesday 4-7 pm)
