BIOL 300: Biostatistics. Statistical quotations There are three kinds of lies: lies, damn lies, and...

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Transcript of BIOL 300: Biostatistics. Statistical quotations There are three kinds of lies: lies, damn lies, and...

BIOL 300: Biostatistics

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Statistical quotations

• There are three kinds of lies: lies, damn lies, and statistics.– Benjamin Disraeli / Mark Twain

Statistical quotations

• There are three kinds of lies: lies, damn lies, and statistics.– Benjamin Disraeli / Mark Twain

• It is easy to lie with statistics, but easier to lie without them.– Frederick Mosteller

Professor:Dr. Luke Harmon

Department of Zoology Office: 1370 Biosciences

Office Hours: 2 - 4 pm Mondays

(or after class)e-mail:

[email protected]

Course website

http://www.zoology.ubc.ca/~bio300/• Lecture notes• Textbook and Lab Manual• Assignments and answers• Contact information

Textbook

• Whitlock and Schluter, The analysis of biological data

• Available in two installments at CopieSmart, UBC Village

• Also available online

JMP• Optional statistical software

• Used in labs• Available in bookstore

• 60-day trial version on web:

• www.jmp.com

Evaluation

Final 50% Mid-term 30% Assignments (homework) 10% Lab exam (final week of term) 10%

Examinations

• Midterm: Thursday October 19 in class

• Final exam: TBA

• Old exams will be posted on the website

Assignments

• Available on course web-page, announced in class

• Due on Fridays at noon, at your TA’s office

(eight days after they are assigned)

• Bonus points for in-class quizzes and activities

Lab

• Begins third week of term (September 18- 22)

• Biol. Sci. room 2434• Lab exam during final week of classes

• Book available at Copiesmart in the village and online

Class Forum

• There will be a forum for discussion on the web

• Discussion of lectures, labs, and homework

• More details available next week

STATISTICS PAIRINGS

• Credit given for only one of BIOL 300, FRST 231, STAT 200, PSYC 218 or 366.

• These are paired with BIOL 300, but do not count as requirements for Biology majors and pre-reqs

Introduction to statistics

Statistics - technology used to describe and measure aspects of nature from samples

Statistics lets us quantify the uncertainty of these measures

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http://www.pbs.org/wgbh/evolution/library/01/5/image_pop/l_015_04.html

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http://www.rit.edu/~rhrsbi/GalapagosPages/DarwinFinch.html

The history of statistics has its roots in biology

Sir Francis Galton

Inventor of fingerprints, study of heredity of quantitative traits

Regression & correlation

Also: efficacy of prayer, attractiveness as function of

distance from London

Karl Pearson

Polymath-

Studied genetics

Correlation coefficient2 testStandard deviation

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Sir Ronald Fisher

The Genetical Theory of Natural Selection

Founder of population genetics

Analysis of variance likelihood P-valuerandomized experiments multiple regressionetc., etc., etc.

Goals of statistics

• Estimation – Infer an unknown quantity of a population using sample data

• Hypothesis testing– Differences among groups– Relationships among variables

Statistics is also about good scientific

practice

Introductory Puzzle

• How to protect bombers flying over enemy territory?

• British Air Ministry - WWII• Looked at distribution of bullet holes in airplanes returning from bombing runs

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http://digitalroam.typepad.com/digital_roam/2006/03/the_hole_story_.html

Results

• Where should more armor be added to the airplanes?

• Explain your conclusion

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Variable

• A variable is a characteristic measured on individuals drawn from a population under study.

• Data are measurements of one or more variables made on a collection of individuals.

Explanatory and response variables

We try to predict or explain a response variable from an explanatory variable.

Mortality on the Titanic, as predicted

by sex

Populations and samples

Populations <-> Parameters;

Samples <-> Estimates

Nomenclature

Population

Parameters

Sample

Statistics

Mean Variance s2

Standard Deviatio

n

s€

x

Precise Imprecise

Biased

Unbiased

Properties of a good sample

• Independent selection of individuals

• Random selection of individuals

• Sufficiently large

In a random sample, each member of a population has an

equal and independent chance of being

selected.

Bias is a systematic discrepancy between

estimates and the true population

characteristic.

A sample of convenience is a collection of

individuals that happen to be available

at the time.

Sampling error

• The difference between the estimate and average value of the estimate

Population parameters are constants whereas estimates are random variables, changing

from one random sample to the next from the

same population.

Larger samples on average will have

smaller sampling error

Read: Chapters 1 & 2