It includes various cases and practice problems related to Binomial, Poisson & Normal Distributions. Detailed information on where tp use which probability.
It includes various cases and practice problems related to Binomial, Poisson & Normal Distributions. Detailed information on where tp use which probability.
According to Wikipedia point estimation involves the use of sample data to calculate a single value (known as a point estimate since it identifies a point in some parameter space) which is to serve as a "best guess" or "best estimate" of an unknown population parameter (for example, the population means).
Chapter 5 part1- The Sampling Distribution of a Sample Meannszakir
Mathematics, Statistics, Population Distribution vs. Sampling Distribution, The Mean and Standard Deviation of the Sample Mean, Sampling Distribution of a Sample Mean, Central Limit Theorem
A basic task in numerous statistical analyses is to characterize the position and variability of a data set. Another characterization of the data includes skewness and kurtosis.
Skewness is a measure of balance, or more precisely, the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the left and right of the centre point.
Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution.
INFERENTIAL STATISTICS: AN INTRODUCTIONJohn Labrador
For instance, we use inferential statistics to try to infer from the sample data what the population might think. Or, we use inferential statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study.
The ppt gives an idea about basic concept of Estimation. point and interval. Properties of good estimate is also covered. Confidence interval for single means, difference between two means, proportion and difference of two proportion for different sample sizes are included along with case studies.
Topic: Frequency Distribution
Student Name: Abdul Hafeez
Class: B.Ed. (Hons) Elementary
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
According to Wikipedia point estimation involves the use of sample data to calculate a single value (known as a point estimate since it identifies a point in some parameter space) which is to serve as a "best guess" or "best estimate" of an unknown population parameter (for example, the population means).
Chapter 5 part1- The Sampling Distribution of a Sample Meannszakir
Mathematics, Statistics, Population Distribution vs. Sampling Distribution, The Mean and Standard Deviation of the Sample Mean, Sampling Distribution of a Sample Mean, Central Limit Theorem
A basic task in numerous statistical analyses is to characterize the position and variability of a data set. Another characterization of the data includes skewness and kurtosis.
Skewness is a measure of balance, or more precisely, the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the left and right of the centre point.
Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution.
INFERENTIAL STATISTICS: AN INTRODUCTIONJohn Labrador
For instance, we use inferential statistics to try to infer from the sample data what the population might think. Or, we use inferential statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study.
The ppt gives an idea about basic concept of Estimation. point and interval. Properties of good estimate is also covered. Confidence interval for single means, difference between two means, proportion and difference of two proportion for different sample sizes are included along with case studies.
Topic: Frequency Distribution
Student Name: Abdul Hafeez
Class: B.Ed. (Hons) Elementary
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
The PPT covered the distinguish between discrete and continuous distribution. Detailed explanation of the types of discrete distributions such as binomial distribution, Poisson distribution & Hyper-geometric distribution.
Capital structure theories - NI Approach, NOI approach & MM ApproachSundar B N
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Application of Univariate, Bivariate and Multivariate Variables in Business R...Sundar B N
In this ppt you can find the materials relating to Application of Univariate, Bivariate and Multivariate Variables in Business Research. Also What is Variable, Types of Variables, Examples of Independent Variables, Examples of Dependent Variables, Common techniques used in univariate analysis include, Common techniques used in bivariate analysis include, Common techniques used in Multivariate analysis include, Difference B/w Univariate, Bivariate & Multivariate Analysis
NABARD
Functions of NABARD
Long term refinance
Interest rates
Developmental functions
Supervisory functions
Government sponsered schemes
NABARAD'S initiatives
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
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.
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
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.
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!
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
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.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Introduction to AI for Nonprofits with Tapp Network
Probability distribution 10
1.
2. Probability Distribution
There are two types of Probability Distribution;
1) Discrete Probability Distribution- the set of all
possible values is at most a finite or a countable
infinite number of possible values
Poisson Distribution
Binomial Distribution
1) Continuous Probability Distribution- takes on
values at every point over a given interval
Normal (Gaussian) Distribution
3. Normal (Gaussian) Distribution
• The normal distribution is a descriptive model
that describes real world situations.
• It is defined as a continuous frequency distribution of infinite range (can take any
values not just integers as in the case of binomial and Poisson distribution).
• This is the most important probability distribution in statistics and important tool
in analysis of epidemiological data and management science.
Characteristics of Normal Distribution
• It links frequency distribution to probability distribution
• Has a Bell Shape Curve and is Symmetric
• It is Symmetric around the mean:
Two halves of the curve are the same (mirror images)
• Hence Mean = Median
• The total area under the curve is 1 (or 100%)
• Normal Distribution has the same shape as Standard Normal Distribution.
• In a Standard Normal Distribution:
The mean (μ ) = 0 and
Standard deviation (σ) =1
4. Normal (Gaussian) Distribution(2)
Z Score (Standard Score)
• Z = X - μ
• Z indicates how many standard deviations away
from the mean the point x lies.
• Z score is calculated to 2 decimal places.
Tables
Areas under the standard normal curve
6. Normal (Gaussian) Distribution(4)
Distinguishing Features
• The mean ± 1 standard deviation covers 66.7% of the area under the
curve
• The mean ± 2 standard deviation covers 95% of the area under the
curve
• The mean ± 3 standard deviation covers 99.7% of the area under the
curve
Application/Uses of Normal Distribution
• It’s application goes beyond describing distributions
• It is used by researchers and modelers.
• The major use of normal distribution is the role it plays in statistical
inference.
• The z score along with the t –score, chi-square and F-statistics is
important in hypothesis testing.
• It helps managers/management make decisions.
7. Binomial Distribution
A widely known discrete distribution constructed by determining the probabilities of X
successes in n trials.
Assumptions of the Binomial Distribution
• The experiment involves n identical trials
• Each trial has only two possible outcomes: success and failure
• Each trial is independent of the previous trials
• The terms p and q remain constant throughout the experiment
– p is the probability of a success on any one trial
– q = (1-p) is the probability of a failure on any one trial
• In the n trials X is the number of successes possible where X is a whole number
between 0 and n.
• Applications
– Sampling with replacement
– Sampling without replacement causes p to change but if the sample size n < 5%
N, the independence assumption is not a great concern.
8. Binomial Distribution Formula
• Probability
function
• Mean
value
• Variance and
standard
deviation
P X
n
X n X
X n
X n X
p q( )
!
! !
for 0
n p
2
2
n p q
n p q
9. Poisson Distribution
French mathematician Siméon Denis Poisson proposed Poisson
DistributionThe Poisson distribution is popular for modelling
the number of times an event occurs in an interval of time or space. It
is a discrete probability distribution that expresses the probability of
a given number of events occurring in a fixed interval of time or
space if these events occur with a known constant rate
and independently of the time since the last event.
The Poisson distribution may be useful to model events such as
• The number of meteorites greater than 1 meter diameter that strike
Earth in a year
• The number of patients arriving in an emergency room between 10
and 11 pm
• The number of photons hitting a detector in a particular time interval
• The number of mistakes committed per pages
10. Poisson Distribution
Assumptions of the Poisson Distribution
• Describes discrete occurrences over a continuum or
interval
• A discrete distribution
• Describes rare events
• Each occurrence is independent any other
occurrences.
• The number of occurrences in each interval can vary
from zero to infinity.
• The expected number of occurrences must hold
constant throughout the experiment.