1) The document discusses probability concepts and their application to archaeological problems. It introduces frequentist and Bayesian approaches to probability.
2) It uses examples from artifact sampling to show how binomial probability can help evaluate whether the absence of a type in a sample suggests it was truly absent in the population.
3) The document demonstrates using cumulative density functions to determine the likelihood of observing differences between samples merely by chance, rather than reflecting real population differences. This helps assess whether observed patterns provide meaningful evidence.
Probability - Question Bank for Class/Grade 10 maths.Let's Tute
Probability - Question Bank for Class/Grade 10 maths.
Watch videos on our youtube channel -
www.youtube.com/letstute.
And find related study material on our website -
www.letstute.com.
Probability - Question Bank for Class/Grade 10 maths.Let's Tute
Probability - Question Bank for Class/Grade 10 maths.
Watch videos on our youtube channel -
www.youtube.com/letstute.
And find related study material on our website -
www.letstute.com.
Basic statistics for algorithmic tradingQuantInsti
In this presentation we try to understand the core basics of statistics and its application in algorithmic trading.
We start by defining what statistics is. Collecting data is the root of statistics. We need data to analyse and take quantitative decisions.
While analyzing, there are certain parameters for statistics, this branches statistics into two - descriptive statistics & inferential statistics.
This data that we have collected can be classified into uni-variate and bi-variate. It also tries to explain the fundamental difference.
Going Further we also cover topics like regression line, Coefficient of Determination, Homoscedasticity and Heteroscedasticity.
In this way the presentation look at various aspects of statistics which are used for algorithmic trading.
To learn the advanced applications of statistics for HFT & Quantitative Trading connect with us one our website: www.quantinsti.com.
➽=ALL False flag-War Machine-War profiteering-Energy (oil/Gas) Iraq, Iran,…oil and gas
USA invades other countries just to own their natural resources and to place them in the hands of American corporations. Facebook doesn’t call that terrorism. They call it democracy. BBC, CNN, FOX NEWS, FR 24, ITV/CH 4, SKY, EURO NEWS, ITV trash Sun paper,… Facebook all are protector and preserver of the propaganda classifying IR Iran as a dangerous terrorist organization. But FB, BBC, CNN, FOX NEWS, FR 24, ITV/CH 4-SKY, EURO NEWS, ITV do know well, that USA is the biggest terrorist country in the world.
‘terrorism’ the unlawful use of violence and intimidation, especially against civilians, in the pursuit of political aims.
"the fight against terrorism" is the fight against the unlawful use of violence and intimidation and carpet bombing.
Ever since the beginning of the 19th century, the West has been sucking on the jugular vein of the Moslem body politic like a veritable vampire whose thirst for Moslem blood is never sated and who refused to let go. Since 1979, Iran, which has always played the role of the intellectual leader of the Islamic world, has risen up to put a stop to this outrage against God’s law and will, and against all decency.
MY NEWS PUNCH DR F DEJAHANG 28/12/2019
PART 1 (IN TOTAL 12 PARTS)
NEWS YOU WON’T FIND ON BBC-CNN-FOX NEWS, FR 24, EURO NEWS, ITV…
ALL In My Documents: https://www.edocr.com/user/drdejahang02
Also in https://www.edocr.com/v/jqmplrpj/drdejahang02/LINKS-08-12-2019-PROJECT-ONE Click on Social Websites of mine >60
Articles for Political Science, Mathematics and Productivity the Student Room BSc, MSc & PhD Project Mangers etc
PPTs in SLIDESHARE International Studies Research Degrees (MPhilPhD) ➽➜R⇢➤=RESEARCH ➽=ALL
PPTs https://www.slideshare.net/DrFereidounDejahang/16-fd-my-news-punch-rev-16122019
Basic statistics for algorithmic tradingQuantInsti
In this presentation we try to understand the core basics of statistics and its application in algorithmic trading.
We start by defining what statistics is. Collecting data is the root of statistics. We need data to analyse and take quantitative decisions.
While analyzing, there are certain parameters for statistics, this branches statistics into two - descriptive statistics & inferential statistics.
This data that we have collected can be classified into uni-variate and bi-variate. It also tries to explain the fundamental difference.
Going Further we also cover topics like regression line, Coefficient of Determination, Homoscedasticity and Heteroscedasticity.
In this way the presentation look at various aspects of statistics which are used for algorithmic trading.
To learn the advanced applications of statistics for HFT & Quantitative Trading connect with us one our website: www.quantinsti.com.
➽=ALL False flag-War Machine-War profiteering-Energy (oil/Gas) Iraq, Iran,…oil and gas
USA invades other countries just to own their natural resources and to place them in the hands of American corporations. Facebook doesn’t call that terrorism. They call it democracy. BBC, CNN, FOX NEWS, FR 24, ITV/CH 4, SKY, EURO NEWS, ITV trash Sun paper,… Facebook all are protector and preserver of the propaganda classifying IR Iran as a dangerous terrorist organization. But FB, BBC, CNN, FOX NEWS, FR 24, ITV/CH 4-SKY, EURO NEWS, ITV do know well, that USA is the biggest terrorist country in the world.
‘terrorism’ the unlawful use of violence and intimidation, especially against civilians, in the pursuit of political aims.
"the fight against terrorism" is the fight against the unlawful use of violence and intimidation and carpet bombing.
Ever since the beginning of the 19th century, the West has been sucking on the jugular vein of the Moslem body politic like a veritable vampire whose thirst for Moslem blood is never sated and who refused to let go. Since 1979, Iran, which has always played the role of the intellectual leader of the Islamic world, has risen up to put a stop to this outrage against God’s law and will, and against all decency.
MY NEWS PUNCH DR F DEJAHANG 28/12/2019
PART 1 (IN TOTAL 12 PARTS)
NEWS YOU WON’T FIND ON BBC-CNN-FOX NEWS, FR 24, EURO NEWS, ITV…
ALL In My Documents: https://www.edocr.com/user/drdejahang02
Also in https://www.edocr.com/v/jqmplrpj/drdejahang02/LINKS-08-12-2019-PROJECT-ONE Click on Social Websites of mine >60
Articles for Political Science, Mathematics and Productivity the Student Room BSc, MSc & PhD Project Mangers etc
PPTs in SLIDESHARE International Studies Research Degrees (MPhilPhD) ➽➜R⇢➤=RESEARCH ➽=ALL
PPTs https://www.slideshare.net/DrFereidounDejahang/16-fd-my-news-punch-rev-16122019
MY NEWS PUNCH 16-12-2019
NEWS YOU WON’T FIND ON BBC-CNN-FOX NEWS, FRNACE 24, EURO NEWS
Articles for Political Science, Mathematics and Productivity the Student Room BSc, MSc & PhD Project Mangers etc
PPTs in SLIDESHARE International Studies Research Degrees (MPhilPhD)
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
2. Questions
• what is a good general size for artifact
samples?
• what proportion of populations of interest
should we be attempting to sample?
• how do we evaluate the absence of an
artifact type in our collections?
3. “frequentist” approach
• probability should be assessed in purely
objective terms
• no room for subjectivity on the part of
individual researchers
• knowledge about probabilities comes from
the relative frequency of a large number of
trials
– this is a good model for coin tossing
– not so useful for archaeology, where many of
the events that interest us are unique…
4. Bayesian approach
• Bayes Theorem
– Thomas Bayes
– 18th
century English clergyman
• concerned with integrating “prior knowledge” into
calculations of probability
• problematic for frequentists
– prior knowledge = bias, subjectivity…
5. basic concepts
• probability of event = p
0 <= p <= 1
0 = certain non-occurrence
1 = certain occurrence
• .5 = even odds
• .1 = 1 chance out of 10
6. • if A and B are mutually exclusive events:
P(A or B) = P(A) + P(B)
ex., die roll: P(1 or 6) = 1/6 + 1/6 = .33
• possibility set:
sum of all possible outcomes
~A = anything other than A
P(A or ~A) = P(A) + P(~A) = 1
basic concepts (cont.)
7. • discrete vs. continuous probabilities
• discrete
– finite number of outcomes
• continuous
– outcomes vary along continuous scale
basic concepts (cont.)
10. independent events
• one event has no influence on the outcome
of another event
• if events A & B are independent
then P(A&B) = P(A)*P(B)
• if P(A&B) = P(A)*P(B)
then events A & B are independent
• coin flipping
if P(H) = P(T) = .5 then
P(HTHTH) = P(HHHHH) =
.5*.5*.5*.5*.5 = .55
= .03
11. • if you are flipping a coin and it has already
come up heads 6 times in a row, what are
the odds of an 7th
head?
.5
• note that P(10H) < > P(4H,6T)
– lots of ways to achieve the 2nd
result (therefore
much more probable)
12. • mutually exclusive events are not
independent
• rather, the most dependent kinds of events
– if not heads, then tails
– joint probability of 2 mutually exclusive events
is 0
• P(A&B)=0
13. conditional probability
• concern the odds of one event occurring,
given that another event has occurred
• P(A|B)=Prob of A, given B
14. e.g.
• consider a temporally ambiguous, but
generally late, pottery type
• the probability that an actual example is
“late” increases if found with other types of
pottery that are unambiguously late…
• P = probability that the specimen is late:
isolated: P(Ta
) = .7
w/ late pottery (Tb): P(Ta
|Tb
) = .9
w/ early pottery (Tc): P(Ta
|Tc
) = .3
15. • P(B|A) = P(A&B)/P(A)
• if A and B are independent, then
P(B|A) = P(A)*P(B)/P(A)
P(B|A) = P(B)
conditional probability (cont.)
16. Bayes Theorem
• can be derived from the basic equation for
conditional probabilities
( ) ( ) ( )
( ) ( ) ( ) ( )BAPBPBAPBP
BAPBP
ABP
|~~|
|
|
+
=
17. application
• archaeological data about ceramic design
– bowls and jars, decorated and undecorated
• previous excavations show:
– 75% of assemblage are bowls, 25% jars
– of the bowls, about 50% are decorated
– of the jars, only about 20% are decorated
• we have a decorated sherd fragment, but it’s too
small to determine its form…
• what is the probability that it comes from a bowl?
18. • can solve for P(B|A)
• events:??
• events: B = “bowlness”; A = “decoratedness”
• P(B)=??; P(A|B)=??
• P(B)=.75; P(A|B)=.50
• P(~B)=.25; P(A|~B)=.20
• P(B|A)=.75*.50 / ((.75*50)+(.25*.20))
• P(B|A)=.88
bowl jar
dec. ?? 50% of bowls
20% of jars
undec. 50% of bowls
80% of jars
75% 25%
( ) ( ) ( )
( ) ( ) ( ) ( )BAPBPBAPBP
BAPBP
ABP
|~~|
|
|
+
=
19. Binomial theorem
• P(n,k,p)
– probability of k successes in n trials
where the probability of success on any one
trial is p
– “success” = some specific event or outcome
– k specified outcomes
– n trials
– p probability of the specified outcome in 1 trial
20. ( ) ( ) ( ) knk
ppknCpknP
−
−= 1,,,
( )
( )!!
!
,
knk
n
knC
−
=
where
n! = n*(n-1)*(n-2)…*1 (where n is an integer)
0!=1
21. binomial distribution
• binomial theorem describes a theoretical
distribution that can be plotted in two
different ways:
– probability density function (PDF)
– cumulative density function (CDF)
22. probability density function (PDF)
• summarizes how odds/probabilities are
distributed among the events that can arise
from a series of trials
23. ex: coin toss
• we toss a coin three times, defining the
outcome head as a “success”…
• what are the possible outcomes?
• how do we calculate their probabilities?
24. coin toss (cont.)
• how do we assign values to
P(n,k,p)?
• 3 trials; n = 3
• even odds of success; p=.5
• P(3,k,.5)
• there are 4 possible values for ‘k’,
and we want to calculate P for
each of them
k
0 TTT
1 HTT (THT,TTH)
2 HHT (HTH, THH)
3 HHH
“probability of k successes in n trials
where the probability of success on any one trial is p”
26. practical applications
• how do we interpret the absence of key
types in artifact samples??
• does sample size matter??
• does anything else matter??
27. 1. we are interested in ceramic production in
southern Utah
2. we have surface collections from a
number of sites
are any of them ceramic workshops??
1. evidence: ceramic “wasters”
ethnoarchaeological data suggests that
wasters tend to make up about 5% of samples
at ceramic workshops
example
28. • one of our sites 15 sherds, none
identified as wasters…
• so, our evidence seems to suggest that this
site is not a workshop
• how strong is our conclusion??
29. • reverse the logic: assume that it is a ceramic
workshop
• new question:
– how likely is it to have missed collecting wasters in a
sample of 15 sherds from a real ceramic workshop??
• P(n,k,p)
[n trials, k successes, p prob. of success on 1 trial]
• P(15,0,.05)
[we may want to look at other values of k…]
31. • how large a sample do you need before you
can place some reasonable confidence in
the idea that no wasters = no workshop?
• how could we find out??
• we could plot P(n,0,.05) against different
values of n…
34. so, how big should samples be?
• depends on your research goals & interests
• need big samples to study rare items…
• “rules of thumb” are usually misguided (ex.
“200 pollen grains is a valid sample”)
• in general, sheer sample size is more
important that the actual proportion
• large samples that constitute a very small
proportion of a population may be highly
useful for inferential purposes
35. • the plots we have been using are probability
density functions (PDF)
• cumulative density functions (CDF) have a
special purpose
• example based on mortuary data…
36. Site 1
• 800 graves
• 160 exhibit body position and grave goods that mark
members of a distinct ethnicity (group A)
• relative frequency of 0.2
Site 2
• badly damaged; only 50 graves excavated
• 6 exhibit “group A” characteristics
• relative frequency of 0.12
Pre-Dynastic cemeteries in Upper Egypt
37. • expressed as a proportion, Site 1 has around
twice as many burials of individuals from
“group A” as Site 2
• how seriously should we take this
observation as evidence about social
differences between underlying
populations?
38. • assume for the moment that there is no
difference between these societies—they
represent samples from the same underlying
population
• how likely would it be to collect our Site 2
sample from this underlying population?
• we could use data merged from both sites as
a basis for characterizing this population
• but since the sample from Site 1 is so large,
lets just use it …
39. • Site 1 suggests that about 20% of our
society belong to this distinct social class…
• if so, we might have expected that 10 of the
50 sites excavated from site 2 would belong
to this class
• but we found only 6…
40. • how likely is it that this difference (10 vs. 6)
could arise just from random chance??
• to answer this question, we have to be
interested in more than just the probability
associated with the single observed
outcome “6”
• we are also interested in the total
probability associated with outcomes that
are more extreme than “6”…
41. • imagine a simulation of the
discovery/excavation process of graves at
Site 2:
• repeated drawing of 50 balls from a jar:
– ca. 800 balls
– 80% black, 20% white
• on average, samples will contain 10 white
balls, but individual samples will vary
42. • by keeping score on how many times we
draw a sample that is as, or more divergent
(relative to the mean sample) than what we
observed in our real-world sample…
• this means we have to tally all samples that
produce 6, 5, 4…0, white balls…
• a tally of just those samples with 6 white
balls eliminates crucial evidence…
43. • we can use the binomial theorem instead of
the drawing experiment, but the same logic
applies
• a cumulative density function (CDF)
displays probabilities associated with a
range of outcomes (such as 6 to 0 graves
with evidence for elite status)
46. • so, the odds are about 1 in 10 that the
differences we see could be attributed to
random effects—rather than social
differences
• you have to decide what this observation
really means, and other kinds of evidence
will probably play a role in your decision…