Equivalent Fractions have the same value, even though they may look different.
You can make equivalent fractions by multiplying or dividing both top and bottom by the same amount.
You only multiply or divide, never add or subtract, to get an equivalent fraction.
Only divide when the top and bottom stay as whole numbers.
Equivalent Fractions have the same value, even though they may look different.
You can make equivalent fractions by multiplying or dividing both top and bottom by the same amount.
You only multiply or divide, never add or subtract, to get an equivalent fraction.
Only divide when the top and bottom stay as whole numbers.
Math for Intelligent Systems - 01 Linear Algebra 01 Vector SpacesAndres Mendez-Vazquez
These are the initial notes for a class I am preparing for this summer in the Mathematics of Intelligent Systems. we will start with the vectors spaces, their basis and dimensions. The, we will look at one the basic applications the linear regression.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
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.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
2. In the theory of vector spaces,
a set of vectors is said to be linearly
dependent if at least one of the vectors in the
set can be defined as a linear combination of
the others; if no vector in the set can be written
in this way, then the vectors are said to
be linearly independent.
3. Let V = Rn and consider the following
elements in V, known as the standard
basis vectors:
e1=(1,0,0….0), e2 =(0,1,0,…0) …..
en=(0,0,0,….1)
e1,e2,23,….en are linearly independent
4. In linear algebra, the linear span of
a set S of vectors in a vector space is the
smallest linear subspace that contains the
set. It can be characterized either as
the intersection of all linear subspaces that
contain S, or as the set of linear
combinations of elements of S. The linear
span of a set of vectors is therefore a vector
space.
5. The real vector space R3 has {(-1,0,0), (0,1,0),
(0,0,1)} as a spanning set. This particular
spanning set is also a basis. If (-1,0,0) were
replaced by (1,0,0), it would also form
the canonical basis of R3.
6. Another spanning set for the same space is
given by {(1,2,3), (0,1,2), (−1,1/2,3), (1,1,1)},
but this set is not a basis, because it
is linearly dependent.
The set {(1,0,0), (0,1,0), (1,1,0)} is not a
spanning set of R3; instead its span is the
space of all vectors in R3 whose last
component is zero.
7. Theorem 1: The subspace spanned by a non-
empty subset S of a vector space V is the set
of all linear combinations of vectors in S.
Theorem 2: Every spanning set S of a vector
space V must contain at least as many
elements as any linearly independent set of
vectors from V.
Theorem 3: Let V be a finite-dimensional
vector space. Any set of vectors that
spans V can be reduced to a basis for V by
discarding vectors if necessary
8. A basis of a vector space is any linearly
independent subset of it that spans the whole
vector space. In other words, each vector in
the vector space can be written exactly in one
way as a linear combination of
the basis vectors. The dimension of a vector
space is the number of vectors in any of
its bases.
9. Let V be a vector space. A minimal set of
vectors in V that spans V is called
a basis for V.
Equivalently, a basis for V is a set of vectors
that
is linearly independent;
Spans V.
10. The number of vectors in a basis for V is
called the dimension of V, denoted by dim(V).
For example, the dimension of Rn is n. The
dimension of the vector space of polynomials
in x with real coefficients having degree at
most two is 3. A vector space that consists of
only the zero vector has dimension zero.
