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One-way ANOVA Two-way ANOVA There must be three or more groups. If there are two groups only, you can use a 2-independent-sample t-test. There are two grouping factors.  The independent variable is called the grouping factor. The group is called the level. Unlike one-way ANOVA, in this design it is allowed to have fewer than three levels (groups) in each factor. In this example, there is one factor and three levels (Group 1-3). Group1 Group2 Group3 Mean 10 11 12 In this example, there are two factors: A and B. In each factor, there are two levels: 1 and 2. Thus, it is called a 2X2 ANOVA between-subject design. A1 A2 B1 10 11 B2 12 13

Formally, the P is the class of problems that solved by a Deterministic Turing machine in polynomial a time. NP is the class of problems that were resolved by a non-deterministic Turing machine a polynomial time, which means that it can be solved by brute force algorithm in exponential time. We know that every P problem is also an NP one . In fact, the fast algorithm that solves P problems can be quickly authentication algorithm. The question is, can we find an NP problem which did not decide on a fast algorithm solve it. If so then NP is different from P. If no then NP is identical to P. 3

Complexity theory attempts to define such differences through a formal criterion for what is meant by a mathematical problem feasibly be decidable ,   that is to say that this can be resolved by a conventional Turing machine with a number measures which are proportional to a polynomial function of the size of input. The category of problem with this property is known as P ( polynomial) - and among the first three of the above-described problems. P can be shown formally distinguished from several other classes, such as to be EXP ( exponential time).Third problem which is fitted from above. The second problem of the above is included in a complex class known as NP ( non-deterministic polynomial) - consists of problems that can certainly by a computation of a non-deterministic Turing machine in a number of steps that a polynomial function, determines the size of the input. P and NP are two different complexity classes defined in two different Turing Machine. P-class is an algor...

Introduction An algorithm is a mathematical method for calculating or computation (The computation of a function), and which can be carried out mechanically, without thinking. Algorithm complexity is concerned about how fast or slow performing specific algorithm. We define complexity as a numerical function T (n) - time in relation to the input size n. We want to specify a time in which there is no algorithm depends on implementation details. But you agree that T (n) is dependent on the performance! A specific algorithm is different amount of time to both inputs depending on factors such as processor speed; instruction set, disk speed, brand and compilers etc. The way around is to estimate the efficiency of each algorithm asymptotically. We will take time to measure T (n) the number of elementary "steps" (defined in any way), provided that each such step lasts for a constant time. Let us consider two classic examples: adding two numbers. We will add two integers digit ...