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Statistics for Molecular Biology and Bioinformatics
Instructor: Ron S. KenettEmail: [email protected]
Course Website: www.kpa.co.il/biostatCourse textbook: MODERN INDUSTRIAL STATISTICS,
Kenett and Zacks, Duxbury Press, 1998
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Course SyllabusCourse Syllabus•Understanding Variability•Variability in Several Dimensions•Basic Models of Probability•Sampling for Estimation of Population Quantities•Parametric Statistical Inference•Computer Intensive Techniques - Bootstrapping•Multivariate Analysis - Multiple Linear Regression•Sequential Methods - Statistical Process Control•Design of Experiments
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Course EmphasisCourse Emphasis•Interpretation of Statistical tools and methods•Reliance on Statistical software (MINITAB)•“Learning by doing”•Interactive classroom environment•Responsibility for the course is shared by:
•The instructor•The students•The researchers behind the mini-projects
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Grading PolicyGrading Policy
•A mini-project: 2-3 students per project•An exam at the end of the course
•Final grade split: 50-50
•Difficulty level of final exam will depend on level of efforts put into project
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The mini-project The mini-project
• Defined in collaboration with a researcher
•Has to be completed at the end of the semester
•Has to be interesting/useful
•Should provide opportunity to apply one (or more)Statistical tool taught in the course
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The mini-project - 1The mini-project - 1
Date of Review:
Student Name: Student ID:Student Name: Student ID:Student Name: Student ID:
Project Name: Research sponsor:email:
room/building:phone:
Problem Background:
Data Characteristics:
Assumptions:
Questions to investigate:
Mini Project Description
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The mini-project - 2The mini-project - 2Project Name:
Student Name: Student ID: Exam grade:Student Name: Student ID: Exam grade:Student Name: Student ID: Exam grade:
Sub-Totals:10 09 1 1 1 1 1 1 1 638 1 1 1 247 1 1 146 1 65 04 03 02 01 0
Des
crip
tive
Stat
istic
s
Mea
sure
s of
loc
atio
n
Mea
sure
s of
dis
pert
ion
Nea
sure
s of
ass
ocia
tion
Ran
dom
vari
able
s
Prob
abili
ty d
istr
ibut
ions
Boo
tstr
appi
ng
Poin
t est
imat
ion
Con
fiden
ce in
terv
als
Hyp
othe
sis
test
ing
AN
OV
A
Des
ign
of E
xper
imen
ts
Mul
tiple
reg
ress
ion
Sim
ple
regr
essi
on
7.6
Total:Statitical Tools
Leve
l of U
nder
stan
ding
/ Dem
onst
ratio
n of
Stat
istic
al T
ools
in m
ini p
roje
ct
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The mini-project - 3The mini-project - 3Date of Review:
Student Name: Student Name: Student Name:
Project Name:
Research sponsor:
5 04 03 02 01 0
App
lied
Sta
titi
cal
Tool
s
Ach
ieve
d M
eani
ngfu
ll R
esul
ts
Scie
ntif
ic E
valu
atio
n0
Leve
l of A
chie
vem
ent
/ Dem
onst
ratio
n of
min
i pro
ject
res
ults
Mini project results
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The Process of Solving Problems with StatisticsThe Process of Solving Problems with Statistics
PLAN• Obje ctive s • Que s tions • Assumptions • S cope s • Approa ches • S tra te gy
COLLECT
• Obse rve • Ga ther • Code • Edit • Trans form ANALYZE
• Plot • Look • Es tima te • Dia gnose • Conclude PRESENT
• Interpre t • De scribe • Answe r • Re comme nd
INPUT OUTPUT
The mini-project - 4The mini-project - 4
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Basic concepts and notationBasic concepts and notation
N
n X
S
Population
Sample
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Statistical InferenceStatistical Inference
N
n X
S
Population
Sample
DescriptiveDescriptiveStatisticsStatistics
ProbabilityProbability
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Statistical Issues in Life SciencesStatistical Issues in Life Sciences
