The document summarizes the development of the education system in Sabah and Sarawak. It discusses how Christian missionaries established the first schools and used various local languages and English as the mediums of instruction. It also notes that indigenous groups traditionally received non-formal education teaching skills like farming. The first government-aided primary school in Sabah opened in 1920 using Malay as the medium.
Tamadun Mesir Purba memberikan sumbangan besar kepada peradaban manusia seperti pembinaan piramid yang menggambarkan kemahiran senibina, penciptaan kertas papirus untuk menyimpan rekod, dan sistem pendidikan untuk melahirkan tenaga terlatih.
" The GOOD, the BAD & the UGLY"
by Amirul HM & Group in January 2009
FOR & AGAINST Presentation for European Studies taught by Prof. Panos from Greece & Dr. Seidleman from Germany.
- Amirul HM, Malaysia ( the UGLY)
- Raf, Philippines ( the BAD )
- Fizah & Ai Yamada, Malaysia & Japan( the GOOD )
- Kurt, Switzerland ( Neutral cum Judge )
This document provides information about the human digestive system and nutrition:
1) It includes diagrams of the digestive system labeling parts like the pancreas, liver, and esophagus. An enzyme found in the pancreas and its function are discussed.
2) Other parts of the digestive system are labeled like the stomach, small intestine, and large intestine. The stomach stores and breaks down food and the small intestine is where digestion ends.
3) Food groups like carbohydrates, proteins, fats, vitamins, minerals, and fiber are outlined along with their functions in the body.
4) A diagram shows the average daily energy needs vary between groups like babies, children, and adults. The
This document provides basic conversational Malay phrases for introductions, greetings, asking for help and directions, solving misunderstandings, commonly used phrases, and other cultural information about the Malay language. It includes numbers, pronouns, colors, common objects, body parts, people, verbs and questions. Phrases are provided in both English and Malay to help with basic communication in Malay. Information is also given on singular vs plural forms, levels of formality in pronouns, addressing others appropriately, and the predominantly Muslim religion in Malaysia.
Bab 7 membahas perjuangan rakyat tempatan mempertahankan kedaulatan negara-negara mereka dari penjajahan asing. Termasuk perjuangan Dol Said melawan penjajahan di Naning, Rentap melawan Brooke di Sarawak, Dato' Maharaja Lela melawan Inggris di Perak, dan Haji Abdul Rahman Limbong melawan peraturan tanah baru di Terengganu.
This document provides an introduction to basic chemistry concepts related to cells, focusing on water and macromolecules. It discusses how water makes up 60-95% of living organisms, and its important properties including polarity, hydrogen bonding, high heat capacity, heat of vaporization, and surface tension. It also summarizes the three main types of macromolecules - polysaccharides, proteins, and nucleic acids - and provides details on carbohydrates including monosaccharides like glucose and their ring structures.
Tunku Abdul Rahman was the first Prime Minister of Malaya and Malaysia. He played a pivotal role in leading Malaya to independence from British rule in 1957 and the formation of Malaysia in 1963. As Chief Minister of the Federation of Malaya from 1955-1957, he established the multi-racial Alliance Party and led them to victory in the 1955 election, paving the way for independence negotiations with Britain. In 1956, he led a mission to London and successfully negotiated for Malaya's independence, which was achieved on August 31, 1957 with Tunku Abdul Rahman becoming the first Prime Minister. He would go on to serve as Prime Minister of unified Malaysia from 1963-1970. Tunku Abdul Rahman
This document provides statistical information and calculations for 5 questions regarding different data sets. For each question, it lists the data, calculates order statistics like median and quartiles, and provides measures of center, spread, and variation for both the population and a sample, including range, variance, standard deviation, and coefficient of variation. It also calculates the mean absolute deviation for each data set.
This document discusses various measures of central tendency including arithmetic mean, geometric mean, and harmonic mean. It provides formulas to calculate each measure and examples worked out step-by-step. For arithmetic mean, the sum of all values is divided by the total number of values. Geometric mean is calculated by taking the nth root of the product of all values. Harmonic mean is calculated as the reciprocal of the arithmetic mean of the reciprocals. In all examples shown, the relationship between the measures holds such that the arithmetic mean is greater than the geometric mean, which is greater than the harmonic mean.
The Big M Method is used to solve linear programming problems with inequality constraints. It involves multiplying inequality constraints to make the right hand side positive, introducing surplus and slack variables, and adding a large penalty term M to the objective for any artificial variables. The example problem is solved using this method in multiple iterations of the simplex algorithm to find the optimal solution.
Department of MathematicsMTL107 Numerical Methods and Com.docxsalmonpybus
Department of Mathematics
MTL107: Numerical Methods and Computations
Exercise Set 8: Approximation-Linear Least Squares Polynomial approximation, Chebyshev
Polynomial approximation.
1. Compute the linear least square polynomial for the data:
i xi yi
1 0 1.0000
2 0.25 1.2840
3 0.50 1.6487
4 0.75 2.1170
5 1.00 2.7183
2. Find the least square polynomials of degrees 1,2 and 3 for the data in the following talbe.
Compute the error E in each case. Graph the data and the polynomials.
:
xi 1.0 1.1 1.3 1.5 1.9 2.1
yi 1.84 1.96 2.21 2.45 2.94 3.18
3. Given the data:
xi 4.0 4.2 4.5 4.7 5.1 5.5 5.9 6.3 6.8 7.1
yi 113.18 113.18 130.11 142.05 167.53 195.14 224.87 256.73 299.50 326.72
a. Construct the least squared polynomial of degree 1, and compute the error.
b. Construct the least squared polynomial of degree 2, and compute the error.
c. Construct the least squared polynomial of degree 3, and compute the error.
d. Construct the least squares approximation of the form beax, and compute the error.
e. Construct the least squares approximation of the form bxa, and compute the error.
4. The following table lists the college grade-point averages of 20 mathematics and computer
science majors, together with the scores that these students received on the mathematics
portion of the ACT (Americal College Testing Program) test while in high school. Plot
these data, and find the equation of the least squares line for this data:
:
ACT Grade-point ACT Grade-point
score average score average
28 3.84 29 3.75
25 3.21 28 3.65
28 3.23 27 3.87
27 3.63 29 3.75
28 3.75 21 1.66
33 3.20 28 3.12
28 3.41 28 2.96
29 3.38 26 2.92
23 3.53 30 3.10
27 2.03 24 2.81
5. Find the linear least squares polynomial approximation to f(x) on the indicated interval
if
a. f(x) = x2 + 3x+ 2, [0, 1]; b. f(x) = x3, [0, 2];
c. f(x) = 1
x
, [1, 3]; d. f(x) = ex, [0, 2];
e. f(x) = 1
2
cosx+ 1
3
sin 2x, [0, 1]; f. f(x) = x lnx, [1, 3];
6. Find the least square polynomial approximation of degrees 2 to the functions and intervals
in Exercise 5.
7. Compute the error E for the approximations in Exercise 6.
8. Use the Gram-Schmidt process to construct φ0(x), φ1(x), φ2(x) and φ3(x) for the following
intervals.
a. [0,1] b. [0,2] c. [1,3]
9. Obtain the least square approximation polynomial of degree 3 for the functions in Exercise
5 using the results of Exercise 8.
10. Use the Gram-Schmidt procedure to calculate L1, L2, L3 where {L0(x), L1(x), L2(x), L3(x)}
is an orthogonal set of polynomials on (0,∞) with respect to the weight functions w(x) =
e−x and L0(x) = 1. The polynomials obtained from this procedure are called the La-
guerre polynomials.
11. Use the zeros of T̃3, to construct an interpolating polynomial of degree 2 for the following
functions on the interval [-1,1]:
a. f(x) = ex, b. f(x) = sinx, c. f(x) = ln(x+ 2), d. f(x) = x4.
12. Find a bound for the maximum error of the approximation in Exercise 1 on the interval
[-1,1].
13. Use the zer.
This document describes using dynamic programming to solve an optimization problem involving allocating crates of strawberries among three grocery stores. It presents the recursive equations to calculate the optimal profit from allocating various numbers of crates to each store. The optimal solution is to allocate 3 crates to store 1, 2 crates to store 2, and 0 crates to store 3, for a total maximum expected profit of 25.
The Big M Method is used to solve linear programming problems with inequality constraints. It involves (1) multiplying inequality constraints to make the right hand side positive, (2) introducing surplus and artificial variables for greater-than constraints, (3) adding a large penalty M to the objective for artificial variables, and (4) introducing slack variables to convert all constraints to equalities. The method is demonstrated on a sample minimization problem that is converted to standard form and solved using the simplex method.
The document discusses the geometric mean and how to calculate it from data. It provides examples of calculating the geometric mean from individual observations, discrete series, and continuous series. For individual observations, the geometric mean is calculated as the nth root of the product of the values. For series with frequencies, the geometric mean is calculated as the antilog of the sum of the logarithms of the values times their frequencies divided by the total number of values.
The document provides information about calculating the arithmetic mean. It defines the arithmetic mean as the sum of all values divided by the total number of items. It discusses simple arithmetic mean for individual observations, discrete series, and continuous series. Formulas and examples are provided for calculating the arithmetic mean using direct methods and a shortcut method. The shortcut method uses deviations from an assumed mean. The document also introduces the step deviation method, which divides deviations by a common factor to reduce numbers.
The document discusses analysis of economic data and calculation of arithmetic mean. It provides definitions and formulas for calculating the arithmetic mean for different types of data series, including individual series, discrete series, and continuous series. The key points are:
1) Economic data is usually analyzed using statistical methods to extract meaningful information from numerical data. The arithmetic mean is commonly used as a measure of central tendency.
2) The arithmetic mean is calculated by dividing the sum of all values by the total number of values. It provides a single representative value for a data set.
3) Arithmetic mean can be calculated for different types of data series using direct or shortcut methods, with appropriate modifications to the basic formula for calculating the mean.
The document discusses different methods to calculate arithmetic mean from various types of data series.
It explains the direct and shortcut methods to find the arithmetic mean for individual, discrete and continuous data series.
For individual series, the direct method sums all data points and divides by the total number of data points. The shortcut method assumes a mean, calculates the differences from the assumed mean, and finds the mean as the assumed mean plus the sum of the differences divided by the total number of data points.
This document provides basic conversational Malay phrases for introductions, greetings, asking for help and directions, solving misunderstandings, commonly used phrases, and other cultural information about the Malay language. It includes numbers, pronouns, colors, common objects, body parts, people, verbs and questions. Phrases are provided in both English and Malay to help with basic communication in Malay. Information is also given on singular vs plural forms, levels of formality in pronouns, addressing others appropriately, and the predominantly Muslim religion in Malaysia.
Bab 7 membahas perjuangan rakyat tempatan mempertahankan kedaulatan negara-negara mereka dari penjajahan asing. Termasuk perjuangan Dol Said melawan penjajahan di Naning, Rentap melawan Brooke di Sarawak, Dato' Maharaja Lela melawan Inggris di Perak, dan Haji Abdul Rahman Limbong melawan peraturan tanah baru di Terengganu.
This document provides an introduction to basic chemistry concepts related to cells, focusing on water and macromolecules. It discusses how water makes up 60-95% of living organisms, and its important properties including polarity, hydrogen bonding, high heat capacity, heat of vaporization, and surface tension. It also summarizes the three main types of macromolecules - polysaccharides, proteins, and nucleic acids - and provides details on carbohydrates including monosaccharides like glucose and their ring structures.
Tunku Abdul Rahman was the first Prime Minister of Malaya and Malaysia. He played a pivotal role in leading Malaya to independence from British rule in 1957 and the formation of Malaysia in 1963. As Chief Minister of the Federation of Malaya from 1955-1957, he established the multi-racial Alliance Party and led them to victory in the 1955 election, paving the way for independence negotiations with Britain. In 1956, he led a mission to London and successfully negotiated for Malaya's independence, which was achieved on August 31, 1957 with Tunku Abdul Rahman becoming the first Prime Minister. He would go on to serve as Prime Minister of unified Malaysia from 1963-1970. Tunku Abdul Rahman
This document provides statistical information and calculations for 5 questions regarding different data sets. For each question, it lists the data, calculates order statistics like median and quartiles, and provides measures of center, spread, and variation for both the population and a sample, including range, variance, standard deviation, and coefficient of variation. It also calculates the mean absolute deviation for each data set.
This document discusses various measures of central tendency including arithmetic mean, geometric mean, and harmonic mean. It provides formulas to calculate each measure and examples worked out step-by-step. For arithmetic mean, the sum of all values is divided by the total number of values. Geometric mean is calculated by taking the nth root of the product of all values. Harmonic mean is calculated as the reciprocal of the arithmetic mean of the reciprocals. In all examples shown, the relationship between the measures holds such that the arithmetic mean is greater than the geometric mean, which is greater than the harmonic mean.
The Big M Method is used to solve linear programming problems with inequality constraints. It involves multiplying inequality constraints to make the right hand side positive, introducing surplus and slack variables, and adding a large penalty term M to the objective for any artificial variables. The example problem is solved using this method in multiple iterations of the simplex algorithm to find the optimal solution.
Department of MathematicsMTL107 Numerical Methods and Com.docxsalmonpybus
Department of Mathematics
MTL107: Numerical Methods and Computations
Exercise Set 8: Approximation-Linear Least Squares Polynomial approximation, Chebyshev
Polynomial approximation.
1. Compute the linear least square polynomial for the data:
i xi yi
1 0 1.0000
2 0.25 1.2840
3 0.50 1.6487
4 0.75 2.1170
5 1.00 2.7183
2. Find the least square polynomials of degrees 1,2 and 3 for the data in the following talbe.
Compute the error E in each case. Graph the data and the polynomials.
:
xi 1.0 1.1 1.3 1.5 1.9 2.1
yi 1.84 1.96 2.21 2.45 2.94 3.18
3. Given the data:
xi 4.0 4.2 4.5 4.7 5.1 5.5 5.9 6.3 6.8 7.1
yi 113.18 113.18 130.11 142.05 167.53 195.14 224.87 256.73 299.50 326.72
a. Construct the least squared polynomial of degree 1, and compute the error.
b. Construct the least squared polynomial of degree 2, and compute the error.
c. Construct the least squared polynomial of degree 3, and compute the error.
d. Construct the least squares approximation of the form beax, and compute the error.
e. Construct the least squares approximation of the form bxa, and compute the error.
4. The following table lists the college grade-point averages of 20 mathematics and computer
science majors, together with the scores that these students received on the mathematics
portion of the ACT (Americal College Testing Program) test while in high school. Plot
these data, and find the equation of the least squares line for this data:
:
ACT Grade-point ACT Grade-point
score average score average
28 3.84 29 3.75
25 3.21 28 3.65
28 3.23 27 3.87
27 3.63 29 3.75
28 3.75 21 1.66
33 3.20 28 3.12
28 3.41 28 2.96
29 3.38 26 2.92
23 3.53 30 3.10
27 2.03 24 2.81
5. Find the linear least squares polynomial approximation to f(x) on the indicated interval
if
a. f(x) = x2 + 3x+ 2, [0, 1]; b. f(x) = x3, [0, 2];
c. f(x) = 1
x
, [1, 3]; d. f(x) = ex, [0, 2];
e. f(x) = 1
2
cosx+ 1
3
sin 2x, [0, 1]; f. f(x) = x lnx, [1, 3];
6. Find the least square polynomial approximation of degrees 2 to the functions and intervals
in Exercise 5.
7. Compute the error E for the approximations in Exercise 6.
8. Use the Gram-Schmidt process to construct φ0(x), φ1(x), φ2(x) and φ3(x) for the following
intervals.
a. [0,1] b. [0,2] c. [1,3]
9. Obtain the least square approximation polynomial of degree 3 for the functions in Exercise
5 using the results of Exercise 8.
10. Use the Gram-Schmidt procedure to calculate L1, L2, L3 where {L0(x), L1(x), L2(x), L3(x)}
is an orthogonal set of polynomials on (0,∞) with respect to the weight functions w(x) =
e−x and L0(x) = 1. The polynomials obtained from this procedure are called the La-
guerre polynomials.
11. Use the zeros of T̃3, to construct an interpolating polynomial of degree 2 for the following
functions on the interval [-1,1]:
a. f(x) = ex, b. f(x) = sinx, c. f(x) = ln(x+ 2), d. f(x) = x4.
12. Find a bound for the maximum error of the approximation in Exercise 1 on the interval
[-1,1].
13. Use the zer.
This document describes using dynamic programming to solve an optimization problem involving allocating crates of strawberries among three grocery stores. It presents the recursive equations to calculate the optimal profit from allocating various numbers of crates to each store. The optimal solution is to allocate 3 crates to store 1, 2 crates to store 2, and 0 crates to store 3, for a total maximum expected profit of 25.
The Big M Method is used to solve linear programming problems with inequality constraints. It involves (1) multiplying inequality constraints to make the right hand side positive, (2) introducing surplus and artificial variables for greater-than constraints, (3) adding a large penalty M to the objective for artificial variables, and (4) introducing slack variables to convert all constraints to equalities. The method is demonstrated on a sample minimization problem that is converted to standard form and solved using the simplex method.
The document discusses the geometric mean and how to calculate it from data. It provides examples of calculating the geometric mean from individual observations, discrete series, and continuous series. For individual observations, the geometric mean is calculated as the nth root of the product of the values. For series with frequencies, the geometric mean is calculated as the antilog of the sum of the logarithms of the values times their frequencies divided by the total number of values.
The document provides information about calculating the arithmetic mean. It defines the arithmetic mean as the sum of all values divided by the total number of items. It discusses simple arithmetic mean for individual observations, discrete series, and continuous series. Formulas and examples are provided for calculating the arithmetic mean using direct methods and a shortcut method. The shortcut method uses deviations from an assumed mean. The document also introduces the step deviation method, which divides deviations by a common factor to reduce numbers.
The document discusses analysis of economic data and calculation of arithmetic mean. It provides definitions and formulas for calculating the arithmetic mean for different types of data series, including individual series, discrete series, and continuous series. The key points are:
1) Economic data is usually analyzed using statistical methods to extract meaningful information from numerical data. The arithmetic mean is commonly used as a measure of central tendency.
2) The arithmetic mean is calculated by dividing the sum of all values by the total number of values. It provides a single representative value for a data set.
3) Arithmetic mean can be calculated for different types of data series using direct or shortcut methods, with appropriate modifications to the basic formula for calculating the mean.
The document discusses different methods to calculate arithmetic mean from various types of data series.
It explains the direct and shortcut methods to find the arithmetic mean for individual, discrete and continuous data series.
For individual series, the direct method sums all data points and divides by the total number of data points. The shortcut method assumes a mean, calculates the differences from the assumed mean, and finds the mean as the assumed mean plus the sum of the differences divided by the total number of data points.
Measures of central tendency are used to describe the center or typical value of a dataset. The three most common measures are:
1. The mean (average) is calculated by adding all values and dividing by the number of values. It is impacted by outliers.
2. The median is the middle value when data is arranged from lowest to highest. Half the values are above it and half below.
3. The mode is the value that occurs most frequently. Datasets can have multiple modes or no clear mode.
Other measures include weighted mean, quartiles, deciles and percentiles which divide the data into progressively more segments. The choice of measure depends on the characteristics of the data and purpose of
This document provides examples and exercises on working with indices. It introduces index notation for exponents, such as 52 = 5 × 5. The key rules for manipulating indices are presented: when multiplying terms with the same base, add the indices; when dividing terms, subtract the indices; and when raising a term to a power, multiply the indices. Negative indices produce fractional results, with the negative index representing the denominator. Worked examples demonstrate simplifying expressions using these index rules.
The document discusses measures of central tendency (mode, median, mean) and measures of dispersion (range, quartiles, interquartile range, variance, standard deviation) for both discrete and grouped data. It provides formulas and examples of calculating these statistics for different datasets including examples with raw data, frequency tables, histograms and ogives. It also discusses how to calculate the statistics from incomplete data by completing tables and calculating sums.
The document discusses various measures of central tendency including arithmetic mean, median, mode, geometric mean, and harmonic mean. It provides definitions and formulas for calculating each measure. Several examples are included to demonstrate calculating each measure for both grouped and ungrouped data sets. The arithmetic mean is demonstrated on two data sets involving family incomes. Median and mode are each demonstrated on a grouped data set involving weights. Geometric mean and harmonic mean are each demonstrated through one example involving family incomes.
The instructor's manual provides solutions to problems from Chapter 1 of the textbook "Introduction to Matlab 6 for Engineers". The solutions include MATLAB code sessions that demonstrate how to solve various problems involving matrices, polynomials, plotting functions, and solving systems of equations. Figures generated by some of the MATLAB plots are also included.
This document contains a mathematics packet from SMP Negeri 3 Kalibagor. It includes 10 pages of math problems and solutions on various topics like algebra, geometry, statistics, and probability. Alfa Kristanti's name appears on each page as the student completing the assignments. The problems cover calculating sums and differences, solving equations, working with fractions and percentages, finding areas and volumes of shapes, probability, and more.
Pembahasan mtk un 2013 paket 04 - PEMBIMBING IGW.SUDIARTA,S.PdWayan Sudiarta
This document contains a mathematics packet from SMP Negeri 3 Kalibagor. It includes 10 pages of math problems and solutions on various topics like algebra, geometry, statistics, and probability. Alfa Kristanti's name appears on each page as the student completing the assignments. The problems cover calculating sums, differences, percentages, averages, areas, volumes, probabilities, and more. Many include diagrams to illustrate the geometry concepts.
The document provides examples of calculating confidence intervals from sample data. It includes steps for finding 95%, 99%, and 90% confidence intervals using the t-distribution and z-distribution. Sample sizes, means, standard deviations and confidence levels are given for multiple data sets, and confidence intervals are calculated and interpreted for each example.
Management and Organization Behavior REPORT, MBAIshaq Ahmed
The document discusses problems facing an organization called RIMERS Tea Estate. It identifies several issues including lack of coordination among employees, a weak distribution channel, low sales margins and production, high competition, and lack of motivation and monitoring. It analyzes the root causes of these problems, such as rising living costs reducing employee satisfaction with salaries, fuel price increases raising transportation costs, competitor companies offering better pay luring away efficient managers, and management gaps emerging from lost managers. Solutions proposed include improving compensation packages to motivate employees.
Management and Organization Behavior PPT, MBAIshaq Ahmed
This document discusses a decision made by Rimers Tea Estate to implement significant changes in response to problems they were facing. The key issues they were facing included lack of coordination, weak distribution channels, low sales and production, and high labor turnover. Their decision was to maintain current employees but change their compensation package to increase pay across different levels by 6-12% and provide additional benefits and incentives. They created an action plan to implement this decision, estimate additional costs, set new sales targets, and monitor performance. The goal of the changes was to improve employee satisfaction, organizational performance, and profits.
Cocola Food Company Ltd. is a growing private food company in Bangladesh that was established in 1975. The report provides details about Cocola, including its mission, history, products, factory, organizational structure, functional departments, and SWOT analysis. It also analyzes the production efficiency of various Cocola products over time, noting seasonal impacts and identifying reasons for production gaps. Overall, the report finds that Cocola is meeting consumer demand through a wide range of quality food products and playing an important role in the Bangladeshi economy.
How to Create A Todo List In Todo of Odoo 18Celine George
In this slide, we’ll discuss on how to create a Todo List In Todo of Odoo 18. Odoo 18’s Todo module provides a simple yet powerful way to create and manage your to-do lists, ensuring that no task is overlooked.
A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 817 from Texas, New Mexico, Oklahoma, and Kansas. 97 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
CURRENT CASE COUNT: 817 (As of 05/3/2025)
• Texas: 688 (+20)(62% of these cases are in Gaines County).
• New Mexico: 67 (+1 )(92.4% of the cases are from Eddy County)
• Oklahoma: 16 (+1)
• Kansas: 46 (32% of the cases are from Gray County)
HOSPITALIZATIONS: 97 (+2)
• Texas: 89 (+2) - This is 13.02% of all TX cases.
• New Mexico: 7 - This is 10.6% of all NM cases.
• Kansas: 1 - This is 2.7% of all KS cases.
DEATHS: 3
• Texas: 2 – This is 0.31% of all cases
• New Mexico: 1 – This is 1.54% of all cases
US NATIONAL CASE COUNT: 967 (Confirmed and suspected):
INTERNATIONAL SPREAD (As of 4/2/2025)
• Mexico – 865 (+58)
‒Chihuahua, Mexico: 844 (+58) cases, 3 hospitalizations, 1 fatality
• Canada: 1531 (+270) (This reflects Ontario's Outbreak, which began 11/24)
‒Ontario, Canada – 1243 (+223) cases, 84 hospitalizations.
• Europe: 6,814
Lecture 2 CLASSIFICATION OF PHYLUM ARTHROPODA UPTO CLASSES & POSITION OF_1.pptxArshad Shaikh
*Phylum Arthropoda* includes animals with jointed appendages, segmented bodies, and exoskeletons. It's divided into subphyla like Chelicerata (spiders), Crustacea (crabs), Hexapoda (insects), and Myriapoda (millipedes, centipedes). This phylum is one of the most diverse groups of animals.
How to Create Kanban View in Odoo 18 - Odoo SlidesCeline George
The Kanban view in Odoo is a visual interface that organizes records into cards across columns, representing different stages of a process. It is used to manage tasks, workflows, or any categorized data, allowing users to easily track progress by moving cards between stages.
What is the Philosophy of Statistics? (and how I was drawn to it)jemille6
What is the Philosophy of Statistics? (and how I was drawn to it)
Deborah G Mayo
At Dept of Philosophy, Virginia Tech
April 30, 2025
ABSTRACT: I give an introductory discussion of two key philosophical controversies in statistics in relation to today’s "replication crisis" in science: the role of probability, and the nature of evidence, in error-prone inference. I begin with a simple principle: We don’t have evidence for a claim C if little, if anything, has been done that would have found C false (or specifically flawed), even if it is. Along the way, I’ll sprinkle in some autobiographical reflections.
How to Configure Public Holidays & Mandatory Days in Odoo 18Celine George
In this slide, we’ll explore the steps to set up and manage Public Holidays and Mandatory Days in Odoo 18 effectively. Managing Public Holidays and Mandatory Days is essential for maintaining an organized and compliant work schedule in any organization.
Computer crime and Legal issues Computer crime and Legal issuesAbhijit Bodhe
• Computer crime and Legal issues: Intellectual property.
• privacy issues.
• Criminal Justice system for forensic.
• audit/investigative.
• situations and digital crime procedure/standards for extraction,
preservation, and deposition of legal evidence in a court of law.
Form View Attributes in Odoo 18 - Odoo SlidesCeline George
Odoo is a versatile and powerful open-source business management software, allows users to customize their interfaces for an enhanced user experience. A key element of this customization is the utilization of Form View attributes.
Ancient Stone Sculptures of India: As a Source of Indian HistoryVirag Sontakke
This Presentation is prepared for Graduate Students. A presentation that provides basic information about the topic. Students should seek further information from the recommended books and articles. This presentation is only for students and purely for academic purposes. I took/copied the pictures/maps included in the presentation are from the internet. The presenter is thankful to them and herewith courtesy is given to all. This presentation is only for academic purposes.
Lecture 1 Introduction history and institutes of entomology_1.pptxArshad Shaikh
*Entomology* is the scientific study of insects, including their behavior, ecology, evolution, classification, and management.
Entomology continues to evolve, incorporating new technologies and approaches to understand and manage insect populations.
Happy May and Happy Weekend, My Guest Students.
Weekends seem more popular for Workshop Class Days lol.
These Presentations are timeless. Tune in anytime, any weekend.
<<I am Adult EDU Vocational, Ordained, Certified and Experienced. Course genres are personal development for holistic health, healing, and self care. I am also skilled in Health Sciences. However; I am not coaching at this time.>>
A 5th FREE WORKSHOP/ Daily Living.
Our Sponsor / Learning On Alison:
Sponsor: Learning On Alison:
— We believe that empowering yourself shouldn’t just be rewarding, but also really simple (and free). That’s why your journey from clicking on a course you want to take to completing it and getting a certificate takes only 6 steps.
Hopefully Before Summer, We can add our courses to the teacher/creator section. It's all within project management and preps right now. So wish us luck.
Check our Website for more info: https://ldmchapels.weebly.com
Get started for Free.
Currency is Euro. Courses can be free unlimited. Only pay for your diploma. See Website for xtra assistance.
Make sure to convert your cash. Online Wallets do vary. I keep my transactions safe as possible. I do prefer PayPal Biz. (See Site for more info.)
Understanding Vibrations
If not experienced, it may seem weird understanding vibes? We start small and by accident. Usually, we learn about vibrations within social. Examples are: That bad vibe you felt. Also, that good feeling you had. These are common situations we often have naturally. We chit chat about it then let it go. However; those are called vibes using your instincts. Then, your senses are called your intuition. We all can develop the gift of intuition and using energy awareness.
Energy Healing
First, Energy healing is universal. This is also true for Reiki as an art and rehab resource. Within the Health Sciences, Rehab has changed dramatically. The term is now very flexible.
Reiki alone, expanded tremendously during the past 3 years. Distant healing is almost more popular than one-on-one sessions? It’s not a replacement by all means. However, its now easier access online vs local sessions. This does break limit barriers providing instant comfort.
Practice Poses
You can stand within mountain pose Tadasana to get started.
Also, you can start within a lotus Sitting Position to begin a session.
There’s no wrong or right way. Maybe if you are rushing, that’s incorrect lol. The key is being comfortable, calm, at peace. This begins any session.
Also using props like candles, incenses, even going outdoors for fresh air.
(See Presentation for all sections, THX)
Clearing Karma, Letting go.
Now, that you understand more about energies, vibrations, the practice fusions, let’s go deeper. I wanted to make sure you all were comfortable. These sessions are for all levels from beginner to review.
Again See the presentation slides, Thx.
pulse ppt.pptx Types of pulse , characteristics of pulse , Alteration of pulsesushreesangita003
what is pulse ?
Purpose
physiology and Regulation of pulse
Characteristics of pulse
factors affecting pulse
Sites of pulse
Alteration of pulse
for BSC Nursing 1st semester
for Gnm Nursing 1st year
Students .
vitalsign
Title: A Quick and Illustrated Guide to APA Style Referencing (7th Edition)
This visual and beginner-friendly guide simplifies the APA referencing style (7th edition) for academic writing. Designed especially for commerce students and research beginners, it includes:
✅ Real examples from original research papers
✅ Color-coded diagrams for clarity
✅ Key rules for in-text citation and reference list formatting
✅ Free citation tools like Mendeley & Zotero explained
Whether you're writing a college assignment, dissertation, or academic article, this guide will help you cite your sources correctly, confidently, and consistent.
Created by: Prof. Ishika Ghosh,
Faculty.
📩 For queries or feedback: ishikaghosh9@gmail.com
This slide is an exercise for the inquisitive students preparing for the competitive examinations of the undergraduate and postgraduate students. An attempt is being made to present the slide keeping in mind the New Education Policy (NEP). An attempt has been made to give the references of the facts at the end of the slide. If new facts are discovered in the near future, this slide will be revised.
This presentation is related to the brief History of Kashmir (Part-I) with special reference to Karkota Dynasty. In the seventh century a person named Durlabhvardhan founded the Karkot dynasty in Kashmir. He was a functionary of Baladitya, the last king of the Gonanda dynasty. This dynasty ruled Kashmir before the Karkot dynasty. He was a powerful king. Huansang tells us that in his time Taxila, Singhpur, Ursha, Punch and Rajputana were parts of the Kashmir state.
6. Business Statistics (BUS 505) Assignment I
6
5. Harmonic mean:
H =
n
1
....................
1 1
a a a1 2
n
=
1
...............
36
1
22
1
21
12
=25.75
6. Geometric mean:
= n a a
.....................
a1 2
n
=12 21 22 22 22 22 23 27 28 29 33 36 36
1
=(21 22 22 22 22 23 27 28 29 33 36
36)12
=26.23
7. Range:
= X
L X S
= 36-21
=18
7. Business Statistics (BUS 505) Assignment I
7
Question 3:
3.6, 3.1, 3.9, 3.7, 3.5, 3.7, 3.4, 3.0, 3.6
Arranging them in ascending order
3.0, 3.1, 3.4, 3.5, 3.6, 3.6, 3.7, 3.7, 3.9
1. Population mean:
X
=
Xi
1
N
N
i
=
33.13.4 3.4 3.53.63.63.7 3.9
10
=3.13
Sample data,
3 3.4 3.6 3.9
Sample mean:
X =
Xi
n
n
i
1
=
3 3.4 3.6 3.9
4
=3.475
9. Business Statistics (BUS 505) Assignment I
9
5. Hermonic mean:
H =
n
1
....................
1 1
a a a1 2
n
=
1
...............
3.9
1
3.1
1
3
10
=3.515
6. Geomatric mean:
= n a a
.....................
a1 2
n
=10 3*3.1*3.4*3.4*3.5*3.6*3.6*3.7*3.7*3.9
= 3.47
7. Range:
= X
L X S
=3.9
= 0.9