linear relation between two variables

Random Variables and Probability Distributions - It is often very important to allocate a numerical value to an outcome of a random experiment. For example, consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome HH HT TH TT No. of heads (x) ..

It is often very important to allocate a numerical value to an outcome of a random experiment. For example, consider an experiment of tossing a coin twice and note the number of heads (x) obtained. Outcome HH HT TH TT No. of heads (x) 2 1 1 0 x is called a random variable, which..

An inequation is said to be linear if each term of the algebraic expression (or expressions) of the inequation contains first degree variables (not the product of variables..

Types of linear systems Gauss-Jordan elimination, Gauss-Jordan method Vectors and vector addition Geometrical solution sets of systems of equations Rectangular matrices to row echelon form Matrix multiplication Inverse to a square matrix Determinants of 2 by 2..

Linear Expansion - Let the length of the rod increase to 'l 2 ' . Increase in length = (l 2 -l 1 ) = l Rise in temperature = (t 2 -t 1 ) 0 c = t. The ratio of increase in length to its original length per every degree rise in temperature is known as ' the coe..

Linear Programming..

The means of each group of a two-way analysis of variance for two independent variables are plotted as shown in the graph. What does the graph represent about the interaction of the variables? => Disordinal interaction or Ordinal interaction or No interaction..

So far we have learnt how to construct a mathematical model for a linear programming problem. If we can find the values of the decision variables x 1 , x 2 , x 3 , ..... x n , which can optimise (maximize or minimize) the objective function Z, then we say that these va..

Let X be a discrete random variable which can assume values x 1 , x 2 , x 3 ,x n with probabilities p 1 , p 2 , p 3 .. p n respectively then (a) Mean of X or expectation of X denoted by E(X) or m is given by (b) Variance of X denoted by s 2 is given ..

When a relation becomes a function ? => For every input, there are fixed number of outputs or For every input, there are two outputs or For two inputs, there is exactly one output or For every input, there is exactly one output..