Posts Tagged ‘element’
Thursday, December 31st, 2009
Overview of the Universe of Discourse
Description
A detailed tutorial on the universe of discourse. Step by step tutorial including several examples of the universe of discourse for reference.
Overview
The universe of discourse is normally just referred to simply as the universe of a set. The universe of discourse can also be the universe of a certain truth set. Basically, it is all possible considerations for a truth set. It is also a set itself, one where many different subsets are taken from. As you can tell, the universe of discourse has different meanings depending on the exact branch of math you are studying. However, all definitions have one thing in common: the universe is a set where many other sets are taken from. Normally it is easy to figure out what the universe of dicourse is based on the context of the problem you are trying to solve.
Tags: considerations, context, discourse, discrete math, element, problem, set, subset, truth, universe, value
Posted in Discrete Math | No Comments »
Tuesday, December 29th, 2009
Overview of the Trichotomy Property
Description
A detailed tutorial on the trichotomy property. Step by step tutorial including several examples of the trichotomy property for reference.
Overview
The trichotomy property is one of the ordering properties of natural numbers. It tells us what order you need to put the natural numbers in – in other words, it tells you the placement of each element of the set of natural numbers. The trichotomy property states that is there are two natural numbers m and n, that m must be either less than n, equal to n, or greater than n. The smaller number is to be placed first, with the larger number after it. If the numbers are equal, then only one number needs to be included as part of the set.
Tags: arithmetic, element, equal, greater, inequality, larger, less, natural, number, order, placement, property, set, smaller, than, trichotomy
Posted in Arithmetic | No Comments »
Thursday, December 10th, 2009
How to Join Tables and Charts
Description
A detailed tutorial on how to join tables and charts. Step by step tutorial including several examples on how to join tables and charts for reference.
Overview
A table, also referred to as a chart, is a way to record certain information so you can match it up quickly. They are very useful and are used in business all the time. It is possible to join certain tables. Provided that the tables share at least one common element, it is possible to combine them to form a new chart. Typically when you join tables you will either increase your columns and decrease your rows, or increase your rows and decrease your columns, depending on what way your graph is oriented and what elements are the same. Sometimes rows or columns may remain the same, but if both remain the same, then that means there is no join – it means you have the same exact chart.
Tags: algebra, business, chart, column, combine, common, decrease, element, graph, increase, information, join, record, row, table
Posted in Algebra | No Comments »
Thursday, November 5th, 2009
Linear Subspaces Explained
Description
A detailed tutorial on linear subspaces and how to identify linear subspaces. Step by step tutorial including several examples of linear subspaces for reference.
Overview
A linear subspace is usually referred to as simply a subspace, when it needs to be distinguished from other types of subspaces. Linear subspaces are also sometimes referred to as vector subspaces. In mathematical terms, to identify a linear subspace, we say that K is a field (or a set, like of real numbers), and V is a vector space over K. Elements of V are vectors and elements of K are scalars. W is said to be a subset of V. If W is a vector space itself, with the same vector space operations as V, then it has a subspace of V.
Tags: algebra, element, field, k, linear, number, operations, real, scalar, set, space, subset, subspace, v, vector, W
Posted in Algebra | No Comments »
Thursday, November 5th, 2009
Upper and Lower Triangular Matrices
Description
A detailed tutorial on upper and lower triangular matrices. Step by step tutorial including several examples of triangular matrices for reference.
Overview
A triangular matrix is a kind of square matrix where an element above or below the main diagonal is 0. This gives the true elements of the matrix a triangle shape, which is how it got its name. An upper triangular matrix is sometimes called a right triangular matrix. The matrix is up in the right upper corner, and the 0 element is in the lower left corner. A lower triangular matrix is sometimes called a left triangular matrix. The matrix is in the left bottom corner, and the 0 element is in the upper right corner.
Tags: 0, algebra, bottom, element, left, lower, matrices, matrix, right, square, top, triangle, triangular, upper, zero
Posted in Algebra | No Comments »
Thursday, November 5th, 2009
Transpose of a Matrix Explained
Description
A detailed tutorial on the transpose of a matrix. Step by step tutorial including several examples of the transpose of a matrix for reference.
Overview
When you transpose a matrix, it is simply a way of saying that you write the matrix in a different way – this creates a new matrix. There are three ways you can transpose a matrix. The first way is to write the rows of your matrix as columns instead. The second way is to write the columns of your matrix as rows instead. And the third way is to reflect your matrix by its main diagonal. All of these actions accomplish the same thing, so it does not matter which method you use. When people talk about transposing something, they are usually referring to matrices.
Tags: algebra, columns, diagonal, element, equivalent, main, matrices, matrix, method, reflect, rows, scalar, transpose
Posted in Algebra | No Comments »
Tuesday, November 3rd, 2009
How to Find the Trace
Description
A detailed tutorial on find the trace of a matrix. Step by step tutorial including several examples of how to find the trace for reference.
Overview
The trace of a square matrix is defined to be the sum of the elements on the main diagonal of the matrix. This can be mathematically expressed as:
Remember, the trace is only defined for square matrices – not any other kind of matrix.
Tags: algebra, diagonal, eigenvalue, element, invariant, linear, main, matrices, matrix, Spur, square, sum, trace
Posted in Algebra | No Comments »
Tuesday, November 3rd, 2009
Well-Ordering Principle Explained
Description
A detailed tutorial on the well-ordering principle. Step by step tutorial including several examples of the well-ordering principle for reference.
Overview
The well-ordering principle states that every nonempty subset of the set of all natural numbers has a smallest element. This is possible because the number zero is not included in the set of natural numbers, and therefore cannot appear in a subset of all natural numbers. The well-ordering principle is equivalant to the Principle of Mathematical Induction, but they are proved in different ways and have different sets. Sometimes it is a better idea to use the Well-Ordering Principle, and other times it is a better idea to use the Principle of Mathematical Induction.
Tags: discrete math, element, induction, mathematical, n!, natural, nonempty, number, ordering, PMI, principle, set, smallest, subset, well, well-ordering, WOP
Posted in Discrete Math | No Comments »
Thursday, October 29th, 2009
Introduction to Equivalence Relations
Description
A detailed tutorial on equivalence relations and how to find them. Step by step tutorial on finding equivalence relations for reference.
Overview
An equivalence relation is a relation that specifies how a set can be split into subsets. Relations can only be considered equivalence relations if they are reflexive, symmetric, or transitive. It is possible for an equivalence relation to be one of these, two of these, or all three of these, If the relation is none of them, then it is not an equivalence relation. An empty set is considered to be an equivalence relation, because it is both symmetric and transitive.
Tags: discrete math, element, empty, equivalence, reflexive, relation, set, subset, symmetric, transitive
Posted in Discrete Math | No Comments »
