DE LA SALLE UNIVERSITY
College of Science
Department of Mathematics
BIOSTAT – Statistics for Biologists
Prerequisite: MATH111 Prerequisite to:
Instructor:_______________________ Contact details:__________________
Consultation Hours:_______________ Class Schedule and Room:________
Course Description
BIOSTAT (Statistics for Biologists) is an introductory course on the basic concepts of descriptive and
inferential statistics designed for Biology students. Topics include descriptive and inferential statistics,
probability distributions, estimation of parameters, tests of hypotheses, regression and correlation
analyses, analysis of variance, and chi-square tests.
Learning Outcomes
On completion of this course, the student is expected to present the following learning outcomes in line with
the Expected Lasallian Graduate Attributes (ELGA)
ELGA Learning Outcome
Critical and Creative Thinker At the end of the course, the students will be able to
Effective Communicator apply appropriate statistical concepts, methodologies
Lifelong Learner and technologies in organizing, analyzing and
Service-Driven Citizen interpreting various real-world situations and in coming
up with relevant decisions.
Final Course Output
As evidence of attaining the above learning outcomes, the student is required to submit the following during
the indicated dates of the term.
Learning Outcome Required Output Due Date
At the end of the course, the students will be Statistical analysis of real-life data in Week 13
able to apply appropriate statistical concepts, biology / health sciences
methodologies and technologies in organizing,
analyzing and interpreting various real-world
situations and in coming up with relevant
decisions.
Rubric for assessment
CRITERIA EXEMPLARY SATISFACTORY DEVELOPING BEGINNING
4 3 2 1
Formulation of Research problem and Research Research Research
the Research objectives are clearly problem and problem is clearly problem and
Problem and defined and significant; objectives are defined but some objectives are
Objectives Demonstrates evidence clearly defined objectives are vague and
(10%) that the research and significant. insignificant. insignificant.
problem was researched
and designed well.
Appropriatene Data are presented Data are Some data are Data are
ss and accurately using all presented using presented using presented using
Extensiveness appropriate appropriate inappropriate inappropriate
of Descriptive tables/graphs/numerical tables/graphs/ tables/graphs/ tables/graphs/n
Statistics measures with proper numerical numerical umerical
(20%) labels/titles and correct measures. measures. measures.
interpretations.
Applications Statistical analyses are Statistical Some statistical Statistical
of Inferential appropriate, necessary, analyses are analyses are analyses are
Statistics and sufficient which appropriate and inappropriate and inappropriate
(30%) completely lead to the necessary which do not lead to the and do not lead
solution of the research partially lead to solution of the to the solution
problem. the solution of the research of the research
research problem. problem. problem.
Depth of Interpretations and Interpretations Some Interpretations
Analysis (25%) conclusions are correct and conclusions interpretations and conclusions
and relevant with are correct and and conclusions are incorrect
meaningful implications. relevant are incorrect and and irrelevant
irrelevant
Clarity and Report is organized Report is Report is Report is not
Organization logically and presented organized organized and organized.
of Report clearly with effective logically and some discussions
(15%) transitions. presented clearly. are not clear.
Additional Requirements
Inquiry Plans \ Activities
Skills Check
Computer Output
Portfolio
Reflection \ Reaction Paper
Mid Term Exam
Final Exam
Grading System
Scale:
FOR FOR STUDENTS with 95-100% 4.0
EXEMPTED FINAL EXAM 89-94% 3.5
STUDENTS with with 83-88% 3.0
(w/out Final no one missed 78-82% 2.5
Exam) missed quiz 72-77% 2.0
quiz 66-71% 1.5
Average of quizzes 85% 55% 45% 60-65% 1.0
(at least 4) <60% 0.0
Class Activities and 5% 5% 5%
Computer Outputs
Learning Output 10% 10% 10%
Final Examination -- 30% 40%
Learning Plan
Culminating Topics Time Frame Learning Activities
At the end of the I. INTRODUCTION Weeks 1-2 Eliciting Prior Knowledge
course, the students 1.1 The Meaning of Statistics Inquiry Approach: Variations in
will be able to apply 1.2 The Uses of Statistics Real Life
appropriate 1.3 Descriptive and
statistical concepts, Inferential Newspaper /Journal Clippings
methodologies and Statistics on Applications of Statistics
technologies in 1.4 Sources of Data Critiques on Use and Misuse of
organizing, 1.4.1 Surveys and Statistics
analyzing and Experiments
interpreting various 1.4.2 Retrospective and Data Collection
real-world situations Prospective Sampling from Actual Data
and in coming up Studies
with relevant 1.4.3 Clinical Trials On-line Activity: Search on
decisions. 1.5 Population and Sample Government/Non-government
1.6 Qualitative and Surveys and their Results
Quantitative Data
1.7 Scales of Measurement Computer Laboratory Activity:
Working on Microsoft Excel
and PhStat2 in Generating
Tables and Graphs.
Project on Data Presentation of
Real-life Data
II. VITAL STATISTICS AND
DEMOGRAPHIC METHOD
2.1 Sources of Vital
Statistics
and Demographic Data
2.2 Vital Statistics Rates,
Ratios, and Proportions
2.3 Measures of Mortality,
Fertility, and Morbidity
III. DESCRIBING Weeks 2-3 Worksheets on Numerical
POPULATION Measures
AND SAMPLE DATA
Exploratory Comparison of Two
3.1 Tabular and Graphical Actual Data Sets
Descriptions
3.2 Numerical Measures
3.2.1 Parameter and Computer Laboratory Activity:
Statistics Generating and Interpreting
3.2.2 Measures of Summary Measures
Central
Tendency
3.2.3 Measures of
Variability
(including
Coefficient of
Variation)
3.2.4 Measures of
Relative
Standing
3.3 Box and Whiskers Plot
IV. PROBABILITY AND Week 4 Cooperative Learning:
PROBABILITY Statistical
DISTRIBUTIONS Experiments Using Coins,
4.1 Basic Probability Dice, Cards, and/or Balls
Concepts
4.2 Discrete Probability Monty Hall Problem/Dice
Distributions: Binomial Problems/Birthday
and Problem/Recreational
Poisson Probability
4.3 Normal Probability Problems
Distribution
Newspaper /Journal Clippings
on
Applications of Probability
Distributions
Computer Laboratory Activity:
probability
distributions to real-life prob
On-line active learning:
Simulating
normal distribution
Computer Laboratory Activity:
Applications of normal
distribution to
real-life problems
V. ESTIMATION OF Week 5 On-line active learning:
PARAMETERS Simulating
5.1 Sampling and Sampling sampling distribution of the
Distribution mean
5.2 Estimation of mean,
variance and proportion Inquiry Approach: Which is a
for a single population better estimate?
5.3 Error of estimation and
sample size Computer Laboratory Activity:
determination Estimation of proportion and
5.4 Estimation of the mean
difference between 2
means, ratio of 2
variances
and difference of 2
proportions for two
populations
VI. TEST OF HYPOTHESIS Weeks 6-8 Eliciting Prior Knowledge:
6.1 Tests of mean, variance Formulating Hypotheses
and proportion for a
single population Inquiry Approach: ‘Guilty’ or
6.2 Tests of the difference ‘Not Guilty’?
between 2 means,
ratio of 2 variances and Computer Laboratory data
difference of 2 analysis involving z-test and t-
proportions for two test
populations
6.3 Interpretation of p -
value
VII. REGRESSION AND Weeks 9-11 Computer Laboratory
CORRELATION ActivitActual
7.1 Correlation Analysis data analysis involving simple
7.2 Simple Linear linear
Regression Analysis regression and correlation
analysis;
ANOVA
VIII. ANALYSIS OF
VARIANCE
8.1 One - way ANOVA
8.2 Two - way ANOVA
8.3 Post-Hoc Test (Tukey-
Kramer Test)
XI. CHI – SQUARE TESTS Weeks 12 Computer Laboratory Activity:
9.1 Test for goodness of fit Actual data analysis involving
9.2 Test for Equality of chi-square tests
more than two proportions
9.3 Test for independence
LEARNING OUTCOME Week 13 Statistical analysis of real-life
data in biology / health
sciences
FINAL EXAMINATION Week 14
References
Albert (2007). Basics Statistics for the Tertiary level. Manila: Rex Publishing Company.
Arcilla, R., Co, F., Ocampo, S. & Trevalles, R. (2011). Statistical Literacy for Lifelong Learning. Manila:
ABIVA Publishing House, Inc
Downie and Heath (1984). Basic Statistical Methods (5th Edition). Manila: National Bookstore.
Glover, T. and Mitchell, K. (2008). An Introduction to Biostatistics. NY: McGraw Hill (Asia).
Kuzma, J.W. and Bohnenblust, S.E. (2005). Basic Statistics for the Health Sciences (5th edition).
McGraw Hill International.
Levine, Berenson & Stephan (2002). Statistics for Managers Using Microsoft Excel (3rd edition). Upper
Saddle River, NJ: Prentice Hall
Mann. (2011). Introductory Statistics (7th edition). Hoboken, NJ: Wiley.
Mendenhall, Beaver & Beaver (2009). Introduction to Probability and Statistics (13th edition). Belmont, CA:
Thomson/Brooke/Cole.
Rao, P.V. (1997). Statistical Research Methods in the Life Sciences. CA: Duxbury Press.
Walpole, Myers, Myers & Ye (2005). Probability and Statistics for Engineers and Scientists (7 th edition).
Singapore: Pearson Education (Asia).
Online Resources
National Statistics Office Accessed October 22, 2012 from: http://census.gov.ph
Math Goodies. Accessed October 15, 2012 from: http://www/mathgoodies.com
http://www.ruf.rice.edu~lane/statsim/samplingdist/
Big Data Analytics, Enterprise Analytics, Data Mining Software, Statistical Analysis, Predictive Analtyics.
Accessed October 15, 2012 from:http://www/statsoft.com
Chung, B.C. (2012) Betty C. Chung’s Web Site. Accessed October 22, 2012 from
http://www.bettycjung.net/Statsites.htm
Class Policies
1. The required minimum number of quizzes for a 3-unit course is 3, and 4 for 4-unit course. No part of the
final exam may be considered as one quiz.
2. Cancellation of the lowest quiz is not allowed even if the number of quizzes exceeds the required
minimum number of quizzes.
3. As a general policy, no special or make-up tests for missed exams other than the final examination will
be given. However, a faculty member may give special exams for
A. approved absences (where the student concerned officially represented the University at some
function or activity).
B. absences due to serious illness which require hospitalization, death in the family and other reasons
which the faculty member deems meritorious.
4. If a student missed two (2) examinations, then he/she will be required to take a make up for the second
missed examination.
5. If the student has no valid reason for missing an exam (for example, the student was not prepared to
take the exam) then the student receives 0% for the missed quiz.
6. Students who get at least 89% in every quiz are exempted from taking the final examination. Their final
grade will be based on the average of their quizzes and other prefinal course requirements. The final
grade of exempted students who opt to take the final examination will be based on the prescribed
computation of final grades inclusive of a final examination. Students who missed and/or took any
special/make-up quiz will not be eligible for exemption.
7. Learning outputs are required and not optional to pass the course.
8. Mobile phones and other forms of communication devices should be on silent mode or turned off during
class.
9. Students are expected to be attentive and exhibit the behavior of a mature and responsible individual
during class. They are also expected to come to class on time and prepared.
10. Sleeping, bringing in food and drinks, and wearing a cap and sunglasses in class are not allowed.
11. Students who wish to go to the washroom must politely ask permission and, if given such, they should
be back in class within 5 minutes. Only one student at a time may be allowed to leave the classroom
for this purpose.
12. Students who are absent from the class for more than 5 meetings will get a final grade of 0.0 in the
course.
13. Only students who are officially enrolled in the course are allowed to attend the class meetings.
Approved by:
DR. ARTURO Y. PACIFICADOR, JR.
Chair, Department of Mathematics
______________________________________________________________________________________________________________________
February 2013 /AMAlberto/SROcampo/MGTan
