Introduction to Statistics - Basic concepts
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Introduction to Statistics - Basic Statistical Termssheisirenebkm
This is a presentation which focuses on the basic concepts of statistics. It includes the branches of statistics, population and sample, qualitative and quantitative data, and discrete and continuous variable.
Statistics is the science of dealing with numbers.
It is used for collection, summarization, presentation and analysis of data.
Statistics provides a way of organizing data to get information on a wider and more formal (objective) basis than relying on personal experience (subjective).
This presentation includes an introduction to statistics, introduction to sampling methods, collection of data, classification and tabulation, frequency distribution, graphs and measures of central tendency.
Introduction to Statistics - Basic concepts
- How to be a good doctor - A step in Health promotion
- By Ibrahim A. Abdelhaleem - Zagazig Medical Research Society (ZMRS)
Introduction to Statistics - Basic Statistical Termssheisirenebkm
This is a presentation which focuses on the basic concepts of statistics. It includes the branches of statistics, population and sample, qualitative and quantitative data, and discrete and continuous variable.
Statistics is the science of dealing with numbers.
It is used for collection, summarization, presentation and analysis of data.
Statistics provides a way of organizing data to get information on a wider and more formal (objective) basis than relying on personal experience (subjective).
This presentation includes an introduction to statistics, introduction to sampling methods, collection of data, classification and tabulation, frequency distribution, graphs and measures of central tendency.
Statistical methods and analyses are used to communicate research findings and give credibility to research methodology and conclusions. It is important for researchers and also consumers of research to understand statistics so that they can be informed, evaluate the credibility and usefulness of information, and make appropriate decisions.
Statistical inference: Probability and DistributionEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 1 (probability) and week 2 (distribution).
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
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kelan nyo isubmit yung assignment no. 7 and 8 nyo nasa slides yun ng stats. isubmit nyo sa akin sa lunes during electromagnetism kasi kukulangin yung class participation nyo sa stats.
Business statistics for NET-JRF SLET according to updated syllabusSundar B N
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I am Mrs. G. Sreelatha, Assistant Professor, CMR College Of Pharmacy, Hyderabad.
I will be uploading notes on Biostatistics And Research Methodology (BRM) of B.Pharmacy, 4th year II sem based on PCI syllabus - JNTUH.
Topic included in this PPT are Origin and History of Statistics.
Hope it will be useful for your studies and will clear your all the doubts.
For the last few centuries, statistics has remained a part of mathematics as the original
work was done by mathematicians like Pascal (1623-1662), James Bernoulli (1654-1705),
De Moivre (1667-1754), Laplace (1749-1827), Gauss (1777-1855), Lagrange, Bayes,
Markoff, Euler etc. These mathematicians were mainly interested in the development of
the theory of probability as applied to the theory of games and other chance phenomena.
Till early nineteenth century, statistics was mainly concerned with official statistics needed
for the collection of information on revenue, population and area of land under cultivation
etc. of a state or kingdom.
The science of statistics developed gradually and its field of application widened day
by day. Hence, it is difficult to give an exact definition of statistics. The definition changed
from time to time depending upon its use and application. Numerous definitions have
been coined by different people. These definitions reflect the statistical angle and field of
activity.
What is the major power linking statistics & data miningIJDKP
In the recent years, numerous scientific research studies which stand for the intersecting disciplines
between statistics and data mining (DM) are obtained [17, 18, 19, 24, 27, 30, 35]. This paper is devoted to answer
the titled suggested question which is based on five reply trends, the 1st trend based on an updated
historical vision for each of statistics and DM. The 2nd trend is concerned with modern theoretical
significant reply between statistics and DM. The major power linking statistics and DM is established in
the 3rd trend. Lastly, the 4th trend represents a significant comparison between statistics & DM. A
conceptual classification about Statistical Data Mining (SDM) process in Egypt will be represented in the
5th reply trend. Finally, the conclusion and the future work are represented.
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GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
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https://arxiv.org/abs/2306.08302
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In a second workflow supporting the same use case, you’ll see:
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4. Demo
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Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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4. 1.) Data is any quantitative or qualitative information.
a.) Quantitative data refers to numerical information
obtained from counting or measuring that which be
manipulated by any fundamental operation.
Examples:
age, I.Q. scores, height, weight, income
5. b.) Qualitative data refers to descriptive attributes that
cannot be subjected to mathematical operations.
Examples:
gender, citizenship, educational attainment, religion
6. 2.) Population refers to the totality of all the elements or
persons for which one has an interest at a particular
time.
7. For example, the members of the faculty of a school, the
graduating class, the Visayan-speaking employees of a
company, the male students, etc. A particular variable of
a population can be associated to the population.
8. A researcher may associate a population to the ages of
graduating students,, the I.Q. scores of the employees,
the income of single parent, and so on. The usual notation
for population is N.
9. 3.) Sample is a part of population determined by
sampling procedures. It is usually denoted by n.
10. 4.) Parameter is any statistical information or attribute
taken from a population. It is a true value or actual
statistics since its source is the population itself.
11. 5.) Statistic is any estimate of statistical attributes taken
from a sample.
12. 6.) Variable is a specific factor, property, or characteristic
of a population or a sample which differentiates a sample
or group of samples from another group.
13. For example, the score obtained from a coeducation class
may differ by gender. Hence, gender is considered
variable. In a catholic congregation, religion cannot be
considered a variable since every member the population
is Catholic.
14. a.) Discrete variable is a variable that can be obtained by
counting. Examples: the number of cellphone users in a
company, the number of computers in the laboratory.
15. b.) Continues variable is a variable that can be obtained
by measuring objects or attributes. Examples: the weight
of students, the temperature in a city over a period of
time, the area of classrooms.
17. Statistics is a branch of Mathematics that deals with
the scientific collection, organization, presentation,
analysis, and interpretation of numerical data in order
to obtain useful and meaningful information.
19. Organization of data refers to the ascertaining
manner of presenting the data into tables,
graphs, or charts so that logical and statistical
conclusions can be drawn from the collected
measurements.
20. Analysis of data refers to the process of
extracting
from
the
given
data
relevant
information from which numerical description
can be formulated.
21. Interpretation of data refers to the task of
drawing conclusions from the analyzed data.
23. 1.) Descriptive Statistics
The branch of statistics that focuses on
collecting, summarizing, and presenting a set of
data.
24. Examples:
a.) The average age of citizens who voted for the
winning candidate in the last presidential
election.
b.) The average length of all books about
statistics.
26. Examples:
a.) For instance, suppose a survey group wants to know
the prevailing sentiments among Filipino people on a
certain issue. Asking every Filipino to answer a
questionnaire would be impossible. It is expensive, timeconsuming, and impractical. Instead, a small part of the
entire population is scientifically chosen. The data
gathered from this group is used to draw a general
opinion of the entire population.
27. b.) A survey that sampled 2001 full or part-time workers
ages 50 to 70, conducted by the American Association of
Retired Persons (AARP), discovered that 70% those
polled planned to work past the traditional mid-60s
retirement age. By using inferential statistics, this
statistics could be used to draw conclusions about the
population of all workers ages 50 to 70.
29. The processing of statistical information has a history
that extends back to the beginning of humanity.
* As early as 3800 B.C., there were records of population
in Babylonia and in China.
31. * In biblical times, the census was undertaken by Moses
in 1491 B.C. and by David in 1017 B.C..
* Indian literature dating back to the reign of the
northern Hindustan King Asoka (270-230 B.C.) also
described methods of taking census.
32. Reign
Coronation
268 BCE
Born
304 BCE,
Close to 7th
Aug
Birthplace
King Asoka of
Northern Hindustan
268–232 BCE
Pataliputra,
Patna
Died
232 BCE
(aged 72)
Place of
death
Pataliputra,
Patna
33. * The Athenians and other ancient Greeks conducted the
census in times of stress, counting the adult male
citizens in war time and the general populace every time
the food supply was endangered.
39. * Two thousand years ago, each male in the Roman
Empire had to return to the city of his birth to be counted
and taxed. Thus, the Bible gives an account of the return
of Joseph and Mary to Bethlehem for such purpose, (The
Holy Bible, Luke 2: 4-5).
41. * In the Middle Ages, registrations of land ownership and
manpower for wars were made.
* In the thirteenth century, tax lists of Paris included the
registration of those who were subjected to tax.
42. * In England, William the Conqueror
required the
compilation of information on population and resources.
The compilation “The Domesday Book” is the first
landmark in British statistics. Later on, the need to
register births, deaths, baptisms, and marriages was
reinforced as the population grew bigger.
43. Born: 1028, Château de
Falaise, Falaise, France
Died: September 9,
1087,
Rouen, France
the Bastard
William I
Flanders
Nickname: William
Full Name:
Spouse: Matilda of
Children:
of England
Henry I
William II of England
45. * It was Gottfried Achenwall who first introduced the
word statistiks in a preface to a statistical work. He was
a German philosopher, historian, economist, jurist and
statistician. He is counted among the inventors of
statistics.
48. Born: September 24,
1501
Pavia, Italy
Died: September 21, 1576
Rome, Italy
Cardano
Parents: Fazio
Books:
The Rules of Algebra
The book of my life
The rules of algebra
Education:
University of Padua
University of Pavia
Gerolamo Cardano
50. * Another gambler, Chevalier de Mere, made a proposal
to Blaise Pascal in the famous Problem of Points, a work
which marked the beginning of the mathematics of
probability. Marquis de Laplace’s Theorie Analytique des
Probabilities of 1812 stabilized and supported the said
theory.
51. He was a French writer born
in Poitou.
Although he was not a nobleman, he
adopted the title Chevalier for the
character in his dialogues who
represented his own views.
Born: 1607, Poitou
Died: December 29, 1684
Chevalier de Méré
52. He was a French
mathematician,
physicist, inventor, writer and
Christian philosopher. He was a
child prodigy who was educated by
his father, a tax collector in Rouen.
Born: June 19, 1623
Clermont-Ferrand, France
Died: August 19, 1662
Paris, France
Full name: Blaise Pascal
Parents: Antoinette Begon
Étienne Pascal
Blaise Pascal
Siblings:
Jacqueline Pascal
Gilberte Pasca
53. * Modern theories of Statistics were attributed to the
great names like Abraham De Moivre (1667-1754) who
discovered the equation of the normal curve.
54. He was a French mathematician
famous for de Moivre's formula,
which links complex numbers and
trigonometry, and for his work on
the normal distribution and
probability theory.
Born: May 26, 1667
Vitry-le-François, France
Died: November 27, 1754
London, United Kingdom
Education: Academy of Saumur
Books: The Doctrine of Chances,
Abraham de Moivre
A Method of Calculating
the Probabilities of Events
in Play
55. * Karl Pearson who made an extensive study on
correlation among several variables.
56. He was an influential English
mathematician who has been
credited with establishing the
discipline of mathematical
statistics. In 1911 he founded the
world's first university statistics
department at University College
London.
Born: March 27, 1857
Islington, United Kingdom
Died: April 27, 1936
Capel, United Kingdom
Children: Egon Pearson
Karl Pearson
Education: Ruprecht Karl University of
Heidelberg, University of Cambridge,
King's College, Cambridge
57. * Just right after the World War II, the need for a basic
understanding of statistics arose. Statistical literacy
became a necessity in today’s modern world.
58. * Nowadays, the use of Statistics has extended to such
things as theater attendance, sports results, car sales in
a certain period of time, heights, weights, birth rates,
death rates, and other things that can be expressed
numerically.