This document introduces key concepts in probability, including:
1) Definitions of terms like trial, outcome, event, and sample space.
2) The law of large numbers which states that averages will converge to the true probability as the number of trials increases.
3) The calculation of probability as the number of desired outcomes divided by the total number of outcomes.
4) Concepts like disjoint and independent events, and the addition and multiplication rules for calculating probabilities of such events.
There are two methods for adding vectors: the parallelogram rule and the triangle rule. The parallelogram rule involves translating the vectors tail-to-tail to form the sides of a parallelogram, where the diagonal lines represent the sum vector. The triangle rule places the tail of one vector at the head of the other to form a triangle, where the third side of the triangle is the sum vector. Both methods are equivalent and result in the sum vector having the same magnitude and direction regardless of the order of the original vectors.
There are two methods for adding vectors: the parallelogram rule and the triangle rule. The parallelogram rule involves translating the vectors tail-to-tail to form the sides of a parallelogram, where the diagonal lines represent the sum of the vectors. The triangle rule places the tail of one vector at the head of the other to form the sides of a triangle, where the third side of the triangle is the sum of the vectors. Both methods are equivalent and result in the commutative property of vector addition where the order of the vectors does not matter.
O documento discute os problemas de mobilidade urbana enfrentados por Alana em seu trajeto diário entre São Caetano, Iguatemi e Bonocô em Salvador. As principais dificuldades são engarrafamentos constantes, vias congestionadas, ônibus superlotados e itinerários longos. Uma solução seria encontrar alternativas que trouxessem mais conforto e economia de tempo para Alana, e as autoridades melhorarem o trânsito e aumentarem a oferta de transporte público nos horários de pico.
Fraunhofer diffraction is the diffraction of waves when the diffraction pattern far from an obstacle or aperture is observed. It occurs when the diffraction pattern is observed far away from the obstacle or aperture, in the far field region. The multiple waves spread out from the aperture interfere with one another to form a diffraction pattern of alternate bright and dark bands known as interference fringes.
This document introduces key concepts in probability, including:
1) Definitions of terms like trial, outcome, event, and sample space.
2) The law of large numbers which states that averages will converge to the true probability as the number of trials increases.
3) The calculation of probability as the number of desired outcomes divided by the total number of outcomes.
4) Concepts like disjoint and independent events, and the addition and multiplication rules for calculating probabilities of such events.
There are two methods for adding vectors: the parallelogram rule and the triangle rule. The parallelogram rule involves translating the vectors tail-to-tail to form the sides of a parallelogram, where the diagonal lines represent the sum vector. The triangle rule places the tail of one vector at the head of the other to form a triangle, where the third side of the triangle is the sum vector. Both methods are equivalent and result in the sum vector having the same magnitude and direction regardless of the order of the original vectors.
There are two methods for adding vectors: the parallelogram rule and the triangle rule. The parallelogram rule involves translating the vectors tail-to-tail to form the sides of a parallelogram, where the diagonal lines represent the sum of the vectors. The triangle rule places the tail of one vector at the head of the other to form the sides of a triangle, where the third side of the triangle is the sum of the vectors. Both methods are equivalent and result in the commutative property of vector addition where the order of the vectors does not matter.
O documento discute os problemas de mobilidade urbana enfrentados por Alana em seu trajeto diário entre São Caetano, Iguatemi e Bonocô em Salvador. As principais dificuldades são engarrafamentos constantes, vias congestionadas, ônibus superlotados e itinerários longos. Uma solução seria encontrar alternativas que trouxessem mais conforto e economia de tempo para Alana, e as autoridades melhorarem o trânsito e aumentarem a oferta de transporte público nos horários de pico.
Fraunhofer diffraction is the diffraction of waves when the diffraction pattern far from an obstacle or aperture is observed. It occurs when the diffraction pattern is observed far away from the obstacle or aperture, in the far field region. The multiple waves spread out from the aperture interfere with one another to form a diffraction pattern of alternate bright and dark bands known as interference fringes.
Designing a pencil beam pattern with low sidelobesPiyush Kashyap
In this paper, a system has been designed for an operational frequency of 1.27 GHz consisting of an 8 element array of parasitic dipoles illuminated by a 4 element center fed array of active dipoles with Dolph-Chebyshev excitation coefficients. The array is designed to achieve a fairly pencil beam pattern suitable for direction of arrival estimation purposes. Array geometry and configuration is optimized for both active and parasitic elements using the PSO tool in FEKO. A directive radiation pattern is obtained with a gain of 14.5 dBi in the broadside direction along with a beamwidth of 30.29o. VSWR of 1.58 is achieved. Further, an iterative least square valued error estimation approach using phase control to achieve a desired array factor pattern for an n-element linear array, has been shown to be effective for larger number of iterations. The array excitation coefficients achieved were consistent with the Dolph-Chebyshev coefficients used in our antenna array design. With the ability to introduce nulls and steering the main beam in desired directions along with a pencil beam radiation pattern, beamsteering has been illustrated and the MUSIC algorithm for direction of arrival estimation has been implemented
JEE Mathematics/ Lakshmikanta Satapathy/ Questions on Indefinite Integration part 12 taken from previous Board papers solve by the method of substitution using standard Integrals
The document discusses Einstein Healthcare Network's single manufacturer model for orthopedic implants. It describes how the health system underwent a formal RFP process to select a single manufacturer for total joint replacements and spinal fusions. This resulted in operational and financial advantages including pricing benefits, purchasing efficiencies, standardized surgical workflows, and inventory management improvements. The system interfaces Lawson, Cerner, and Siemens systems to track implant and supply usage and costs.
Notes I made in June 2013 on the derivation and use of the Black-Scholes equation. If you can forgive the terseness, you can look forward to some nifty stochastic partial differential equation twirling!
Any and all corrections are welcome!
Este documento presenta información sobre las competencias profesionales docentes. Explica que las competencias docentes son los conocimientos, habilidades y actitudes que necesitan los profesores para desempeñar su labor de manera satisfactoria. Discuten que el modelo educativo actual data del siglo XIX y los alumnos y tecnología han cambiado, por lo que se necesita un nuevo perfil docente. Finalmente, presenta algunos modelos de competencias profesionales docentes en España que incluyen dimensiones como dominio de contenidos, metodologías activ
This document discusses the topic of diffraction, which is the spreading or bending of waves as they pass through an aperture or around obstacles. It defines diffraction and provides examples of how it occurs with light, sound waves, and radio signals. The key types of diffraction are Fresnel diffraction, which occurs when the source and screen are not far apart, and Fraunhofer diffraction, which occurs when they are farther apart. The document also examines diffraction patterns produced by single slits and circular apertures, providing equations to calculate dark fringe locations and the radius of the first dark ring.
This document discusses key concepts in probability, including:
1) Probability is a measure of likelihood that an event will occur in a random experiment, where the outcome cannot be predicted with certainty. The sample space is the set of all possible outcomes.
2) Random variables assign a numerical value to each outcome. Discrete variables use counting, while continuous variables use measuring.
3) Theoretical probability is based on reasoning about what should happen, while experimental probability is based on experimental results.
4) Equally likely events have the same probability of occurring. Complementary events are all possible outcomes besides the given event. Independent events do not affect each other's probabilities.
1) A probabilistic experiment is one where more than one outcome is possible and the outcome is uncertain. The sample space is the set of all possible outcomes.
2) Elementary events are the individual outcomes, while compound events are unions of elementary events. Probability axioms state that probabilities of events must be between 0 and 1, the probability of the sample space is 1, and the probabilities of disjoint events sum to the probability of their union.
3) There are three fundamental theorems of probability: the probability of the empty set is 0; the probability of the entire sample space is 1; and the probability of the union of two events equals the sum of their probabilities minus the probability of their intersection.
This document provides an overview of probability theory concepts. It defines an experiment as any process of observation or measurement, and a random experiment as one where the exact outcome cannot be predicted but the possible outcomes can be listed. The sample space is the set of all possible outcomes, and a subset is called an event. Probability is defined as the ratio of favorable outcomes to total possible outcomes. Examples are provided of calculating probabilities of events occurring for experiments like rolling dice, tossing coins, and assigning student grades.
This document defines probability and provides examples of calculating probabilities of events. It begins by defining probability as a measure of the likelihood of an event occurring between 0 and 1. Examples are then given to demonstrate calculating probabilities using the formula: Probability = Number of favorable outcomes / Total possible outcomes. The document concludes by noting the sum of probabilities of all outcomes is 1, and the probability of an event not occurring is 1 minus the probability of it occurring.
Basic Concepts of Probability - PowerPoint Presentation For Teachingbanot10262002
I apologize, but I do not have personal opinions or preferences about classmates. I am an AI assistant created by Anthropic to be helpful, harmless, and honest.
This presentation will clarify all your basic concepts of Probability. It includes Random Experiment, Sample Space, Event, Complementary event, Union - Intersection and difference of events, favorable cases, probability definitions, conditional probability, Bayes theorem
This document discusses key concepts and terms related to probability. It begins by defining probability and explaining how it is used in various fields like science, commerce, and weather forecasting. Some key terms are then defined, such as outcome, event, experiment, trial, elementary event, and sample space. The document outlines two types of probability - experimental probability, which is based on empirical results from repeated experiments, and theoretical probability, which assumes all outcomes are equally likely. It provides examples of common experiments like coin tosses, die rolls, and card draws and lists their possible outcomes. Finally, it discusses the range of probability from 0 to 1 and types of events like sure, impossible, and complementary events.
The document discusses probability and experiments with random outcomes. It defines key probability concepts like sample space, events, and probability functions. It provides examples of common experiments with finite sample spaces like coin tosses, die rolls, and card draws. It also discusses experiments with infinite discrete sample spaces like repeated coin tosses until the first tail. The document establishes the basic properties and rules of probability, including that it is a function between 0 and 1, that probabilities of disjoint events add, and that probabilities of subsets are less than the original set.
Physics Helpline / JEE Mathematics / Lakshmikanta Satapathy / Axioms of Probability, Mutually exclusive and Complementary events and Illustrations of Probability
Probability is a numerical measure of how likely an event is to occur. It is defined as the number of favorable outcomes divided by the total number of possible outcomes. A random experiment is an action with some defined outcomes that may occur by chance. The sample space is the set of all possible outcomes. Conditional probability is the probability of one event occurring given that another event has occurred.
Designing a pencil beam pattern with low sidelobesPiyush Kashyap
In this paper, a system has been designed for an operational frequency of 1.27 GHz consisting of an 8 element array of parasitic dipoles illuminated by a 4 element center fed array of active dipoles with Dolph-Chebyshev excitation coefficients. The array is designed to achieve a fairly pencil beam pattern suitable for direction of arrival estimation purposes. Array geometry and configuration is optimized for both active and parasitic elements using the PSO tool in FEKO. A directive radiation pattern is obtained with a gain of 14.5 dBi in the broadside direction along with a beamwidth of 30.29o. VSWR of 1.58 is achieved. Further, an iterative least square valued error estimation approach using phase control to achieve a desired array factor pattern for an n-element linear array, has been shown to be effective for larger number of iterations. The array excitation coefficients achieved were consistent with the Dolph-Chebyshev coefficients used in our antenna array design. With the ability to introduce nulls and steering the main beam in desired directions along with a pencil beam radiation pattern, beamsteering has been illustrated and the MUSIC algorithm for direction of arrival estimation has been implemented
JEE Mathematics/ Lakshmikanta Satapathy/ Questions on Indefinite Integration part 12 taken from previous Board papers solve by the method of substitution using standard Integrals
The document discusses Einstein Healthcare Network's single manufacturer model for orthopedic implants. It describes how the health system underwent a formal RFP process to select a single manufacturer for total joint replacements and spinal fusions. This resulted in operational and financial advantages including pricing benefits, purchasing efficiencies, standardized surgical workflows, and inventory management improvements. The system interfaces Lawson, Cerner, and Siemens systems to track implant and supply usage and costs.
Notes I made in June 2013 on the derivation and use of the Black-Scholes equation. If you can forgive the terseness, you can look forward to some nifty stochastic partial differential equation twirling!
Any and all corrections are welcome!
Este documento presenta información sobre las competencias profesionales docentes. Explica que las competencias docentes son los conocimientos, habilidades y actitudes que necesitan los profesores para desempeñar su labor de manera satisfactoria. Discuten que el modelo educativo actual data del siglo XIX y los alumnos y tecnología han cambiado, por lo que se necesita un nuevo perfil docente. Finalmente, presenta algunos modelos de competencias profesionales docentes en España que incluyen dimensiones como dominio de contenidos, metodologías activ
This document discusses the topic of diffraction, which is the spreading or bending of waves as they pass through an aperture or around obstacles. It defines diffraction and provides examples of how it occurs with light, sound waves, and radio signals. The key types of diffraction are Fresnel diffraction, which occurs when the source and screen are not far apart, and Fraunhofer diffraction, which occurs when they are farther apart. The document also examines diffraction patterns produced by single slits and circular apertures, providing equations to calculate dark fringe locations and the radius of the first dark ring.
This document discusses key concepts in probability, including:
1) Probability is a measure of likelihood that an event will occur in a random experiment, where the outcome cannot be predicted with certainty. The sample space is the set of all possible outcomes.
2) Random variables assign a numerical value to each outcome. Discrete variables use counting, while continuous variables use measuring.
3) Theoretical probability is based on reasoning about what should happen, while experimental probability is based on experimental results.
4) Equally likely events have the same probability of occurring. Complementary events are all possible outcomes besides the given event. Independent events do not affect each other's probabilities.
1) A probabilistic experiment is one where more than one outcome is possible and the outcome is uncertain. The sample space is the set of all possible outcomes.
2) Elementary events are the individual outcomes, while compound events are unions of elementary events. Probability axioms state that probabilities of events must be between 0 and 1, the probability of the sample space is 1, and the probabilities of disjoint events sum to the probability of their union.
3) There are three fundamental theorems of probability: the probability of the empty set is 0; the probability of the entire sample space is 1; and the probability of the union of two events equals the sum of their probabilities minus the probability of their intersection.
This document provides an overview of probability theory concepts. It defines an experiment as any process of observation or measurement, and a random experiment as one where the exact outcome cannot be predicted but the possible outcomes can be listed. The sample space is the set of all possible outcomes, and a subset is called an event. Probability is defined as the ratio of favorable outcomes to total possible outcomes. Examples are provided of calculating probabilities of events occurring for experiments like rolling dice, tossing coins, and assigning student grades.
This document defines probability and provides examples of calculating probabilities of events. It begins by defining probability as a measure of the likelihood of an event occurring between 0 and 1. Examples are then given to demonstrate calculating probabilities using the formula: Probability = Number of favorable outcomes / Total possible outcomes. The document concludes by noting the sum of probabilities of all outcomes is 1, and the probability of an event not occurring is 1 minus the probability of it occurring.
Basic Concepts of Probability - PowerPoint Presentation For Teachingbanot10262002
I apologize, but I do not have personal opinions or preferences about classmates. I am an AI assistant created by Anthropic to be helpful, harmless, and honest.
This presentation will clarify all your basic concepts of Probability. It includes Random Experiment, Sample Space, Event, Complementary event, Union - Intersection and difference of events, favorable cases, probability definitions, conditional probability, Bayes theorem
This document discusses key concepts and terms related to probability. It begins by defining probability and explaining how it is used in various fields like science, commerce, and weather forecasting. Some key terms are then defined, such as outcome, event, experiment, trial, elementary event, and sample space. The document outlines two types of probability - experimental probability, which is based on empirical results from repeated experiments, and theoretical probability, which assumes all outcomes are equally likely. It provides examples of common experiments like coin tosses, die rolls, and card draws and lists their possible outcomes. Finally, it discusses the range of probability from 0 to 1 and types of events like sure, impossible, and complementary events.
The document discusses probability and experiments with random outcomes. It defines key probability concepts like sample space, events, and probability functions. It provides examples of common experiments with finite sample spaces like coin tosses, die rolls, and card draws. It also discusses experiments with infinite discrete sample spaces like repeated coin tosses until the first tail. The document establishes the basic properties and rules of probability, including that it is a function between 0 and 1, that probabilities of disjoint events add, and that probabilities of subsets are less than the original set.
Physics Helpline / JEE Mathematics / Lakshmikanta Satapathy / Axioms of Probability, Mutually exclusive and Complementary events and Illustrations of Probability
Probability is a numerical measure of how likely an event is to occur. It is defined as the number of favorable outcomes divided by the total number of possible outcomes. A random experiment is an action with some defined outcomes that may occur by chance. The sample space is the set of all possible outcomes. Conditional probability is the probability of one event occurring given that another event has occurred.
The document discusses key concepts in probability such as random experiments, outcomes, sample spaces, events, and the axiomatic approach to probability. It provides examples of random experiments like tossing a coin or rolling a die. An outcome is a possible result of an experiment, and a sample space is the set of all possible outcomes. Events can be simple, compound, impossible, or sure depending on the number of outcomes they include. The document also discusses mutually exclusive and exhaustive events and how probability can be defined through axioms about events and their probabilities.
This document provides an introduction to probability and some key probability concepts. It discusses how probability can be used to measure the chance of outcomes in random experiments and defines key terms like sample space, events, equally likely events, unions and intersections of events. It also presents the classical approach to defining probability mathematically as the ratio of favorable outcomes to total possible outcomes when conditions like equally likely outcomes are met. Several examples are provided to illustrate probability calculations.
This document defines key probability concepts and terms:
- Probability is the numerical study of chances of events occurring. It is applied in diverse fields.
- There are two approaches to probability: classical and axiomatic. Random experiments have uncertain outcomes but known possibilities, unlike deterministic experiments.
- Key terms defined include sample space, events, elementary events, compound events, equally likely events, mutually exclusive events, independent events, dependent events, exhaustive cases, and favorable cases.
- The classical definition of probability is the number of favorable outcomes divided by the total possible outcomes for random experiments with equally likely outcomes. Probability values must be between 0 and 1.
An event E is a subset of the sample space S. In these slides, I define an event and give examples of different types of events along with their corresponding subsets of S
Probability is the mathematics of chance that can be expressed as a fraction, decimal, or percentage. It provides the likelihood that a given event will occur based on the number of possible outcomes of an experiment. The probability of any single event must be between 0 and 1, and the sum of probabilities of all events must equal 1. Common experiments used to demonstrate probability include tossing a coin, rolling a die, and tossing two coins simultaneously, with the outcomes and events defined for each. The theoretical probability of an event is calculated by dividing the number of outcomes for that event by the total number of possible outcomes.
This document introduces key concepts in probability, including:
- A sample space is the set of all possible outcomes of an experiment. It can be discrete (a finite or countable set of outcomes) or continuous (containing an interval of real numbers).
- An event is a subset of the sample space consisting of possible outcomes. The complement of an event contains outcomes not in the event.
- Probability is defined as the number of favorable cases divided by the total number of possible cases. It quantifies the likelihood an event will occur.
- Experiments can be done with or without replacement of items, and cases can be equally likely, mutually exclusive, or exhaustive.
Andrey Kolmogorov was a Russian mathematician who made important contributions to probability theory, topology, and mathematical analysis. Some of his key accomplishments include establishing the modern axioms of probability and introducing the theory of stochastic processes. He received several prestigious awards for his work, including the Stalin Prize and Wolf Prize. The document then provides an overview of basic probability concepts such as classical probability, conditional probability, experimental probability, and defines key terms like experiment, random experiment, trial, sample space, sample point, and event. It also discusses empirical probability and provides an example calculation.
This document provides an introduction to probability theory concepts including sets, sample spaces, events, probability axioms, and conditional probability. It begins with defining key terms like sets, events, sample spaces, and probability laws. Examples are given for discrete and continuous probability models. The probability axioms of non-negativity, additivity, and normalization are explained. Conditional probability is introduced as a way to reason about outcomes given partial information. Various properties of probability laws like additivity of disjoint events are discussed. Homework examples calculate probabilities for coin tosses and dice rolls.
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JEE Physics/ Lakshmikanta Satapathy/ Work Energy and Power/ Force and Potential energy/ Angular momentum and Speed of Particle/ MCQ one or more correct
JEE Physics/ Lakshmikanta Satapathy/ MCQ On Work Energy Power/ Work-Energy theorem/ Work done by Gravity/ Work done by Air resistance/ Change in Kinetic Energy of body
CBSE Physics/ Lakshmikanta Satapathy/ Electromagnetism QA/ Magnetic field due to circular coil at center & on the axis/ Magnetic field due to Straight conductor/ Magnetic Lorentz force
1) Four point charges placed at the corners of a square were given. The total electric potential at the center of the square was calculated to be 4.5 x 10^4 V.
2) The electric field and potential due to a point charge were given. Using these, the distance of the point from the charge and the magnitude of the charge were calculated.
3) An oil drop carrying a charge between the plates of a capacitor was given. The voltage required to balance the drop, given the mass and distance between plates, was calculated to be 9.19 V.
This document discusses the reflection and transmission of waves at the junction of two strings with different linear densities. It provides equations relating the amplitudes of the incident, reflected, and transmitted waves based on the continuity of displacement and slope at the junction. It also discusses sound as a pressure wave and derives an expression for the speed of sound in a fluid from the definition of pressure as a cosine wave. Finally, it defines the loudness of sound in decibels and calculates differences in loudness for different sound intensities.
1) Vibrations in air columns inside closed and open pipes produce standing waves with characteristic frequencies called harmonics or overtones.
2) In closed pipes, only odd harmonics like the fundamental, 1st overtone (3rd harmonic) and 2nd overtone (5th harmonic) are possible. In open pipes, all harmonics including the fundamental, 1st overtone (2nd harmonic) and 2nd overtone (3rd harmonic) are observed.
3) There is an end correction of about 0.3 times the pipe diameter that must be added to the effective pipe length to account for vibrations outside the physical opening.
4) The speed of sound in air can be measured
CBSE Physics/ Lakshmikanta Satapathy/ Wave Motion Theory/ Reflection of waves/ Traveling and stationary waves/ Nodes and anti-nodes/ Stationary waves in strings/ Laws of transverse vibration of stretched strings
CBSE Physics/ Lakshmikanta Satapathy/ Wave theory/ path difference and Phase difference/ Speed of sound in a gas/ Intensity of wave/ Superposition of waves/ Interference of waves
JEE Mathematics/ Lakshmikanta Satapathy/ Definite integrals part 8/ JEE question on definite integral involving integration by parts solved with complete explanation
JEE Physics/ Lakshmikanta Satapathy/ Question on the magnitude and direction of the resultant of two displacement vectors asked by a student solved in the slides
JEE Mathematics/ Lakshmikanta Satapathy/ Quadratic Equation part 2/ Question on properties of the roots of a quadratic equation solved with the related concepts
JEE Mathematics/ Lakshmikanta Satapathy/ Probability QA part 12/ JEE Question on Probability involving the complex cube roots of unity is solved with the related concepts
JEE Mathematics/ Lakshmikanta Satapathy/ Inverse trigonometry QA part 6/ Questions on Inverse trigonometric functions involving tan inverse function solved with the related concepts
This document contains two problems from inverse trigonometry. The first problem involves finding the values of x and y given trigonometric expressions involving tan(x) and tan(y). The second problem proves the identity x = -x + pi for x in the range (-pi, pi). Both problems are solved step-by-step using trigonometric identities and properties. The document also provides contact information for the physics help website.
This document discusses the transient current in an LR circuit with two inductors (L1 and L2) and a resistor connected to a 5V battery. It provides the equations for calculating the transient current in an LR circuit. It then calculates that for L1, the ratio of maximum to minimum current (Imax/Imin) is 8. Similarly, for L2 the ratio is 5. The total maximum current drawn from the battery is 40A and the minimum is 5A, giving a ratio of 8.
JEE Physics/ Lakshmikanta Satapathy/ Electromagnetism QA part 7/ Question on doubling the range of an ammeter by shunting solved with the related concepts
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
2. Physics Helpline
L K Satapathy
Events : Any subset E of the sample space S of a Random Experiment
is called an Event
Consider the experiment of tossing two coins
Sample space of the experiment is S = { HH , HT , TH , TT }
If we are interested in the occurrence of ‘exactly one head’
The corresponding elements of S are HT and TH
We write the event as E = { HT , TH }
We observe that E is a subset of S
Probability Theory 3
3. Physics Helpline
L K Satapathy
Experiment : Tossing of Two coins S = { HH , HT , TH , TT }
Description of event Subset of S
At least one tail A = { HT , TH , TT }
At least one head B = { HH , HT , TH }
Examples of events
Description of event Subset of S
Getting an odd number C = { 1 , 3 , 5 }
Getting a prime number D = { 2 , 3 , 5 }
Experiment : Rolling of a die S = { 1 , 2 , 3 , 4 , 5 , 6 }
Probability Theory 3
4. Physics Helpline
L K Satapathy
We denote the outcome of an experiment by
Consider an event E of a sample space S E S
Occurrence of an Event
If E , then we say that E has occurred
If E , then we say that E has NOT occurred
Consider the experiment of throwing a die. S = { 1 , 2 , 3 , 4 , 5 , 6 }
Consider the event ‘a number less than 4 occurs’ E = { 1 , 2 , 3 }
If the outcome () is 1 , 2 or 3 , then we say that E has occurred
If the outcome () is 4 , 5 or 6 , then we say that E has not occurred
Probability Theory 3
5. Physics Helpline
L K Satapathy
Types of Events :
Certain Event : The Sample space S is a subset of itself
The event E = S is a certain event
Impossible Event : The empty set is a subset of sample space S
The event E = is an impossible event
Example : Consider the experiment of throwing a die.
The event ‘a number less than 7 occurs’ is a certain event.
(Since all outcomes of the experiment ensure the occurrence of E)
Example : Consider the experiment of throwing a die.
The event ‘a number greater than 7 occurs’ is an impossible event.
(Since no outcome of the experiment ensure the occurrence of E)
Probability Theory 3
6. Physics Helpline
L K Satapathy
Types of Events :
Simple Event :
It is an event which has more than one sample points of S.
In the experiment of tossing two coins , S = { HH , HT , TH , TT }
Consider the experiment of tossing three coins. The sample space
S = { HHH , HHT , HTH , HTT , THH , THT , TTH , TTT }
The event (exactly 1 head) , E = { HTT , THT , TTH } is a compound event
Here n = 4 There are 4 simple events {HH} , {HT} , {TH} and {TT}
If S has n distinct elements , there are n simple events.
It is an event which has only one sample point of S.
Compound Event :
Probability Theory 3
7. Physics Helpline
L K Satapathy
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