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To begin with we have counting numbers. These numbers are also known as natural numbers and are denoted by a symbol 'N'. These numbers are obtained by adding one to the previous number. In other words once we know the first element we can obtain the elements following it by adding 1 to the successive elements. That is, we can have infinite (innumerable or a large number of them) number of them. Since natural numbers are infinite, we find it convenient to express them as a set. By set we mean a collection of any well-defined objects. Each individual object is also referred to as an element of that particular set. We should be clear that the concept of set can be used to represent infinite as well as finite number of elements. A simple example for finite number of elements would be that the vowels a, e, i, o and u can be expressed as a set. Generally the set of natural numbers is represented as:
N = {1, 2, 3,.............}.
Probability - Applications of integrals In this final application of integrals that we'll be looking at we are going to look at probability. Previous to actually getting into
what is the lowest term of 11/121
Liner Regression The calculations for our sample size n = 10 are described below. The linear regression model is y = a + bx Table: Distance x miles
A train covered a certain distance at a uniform speed. If the train would have been 6km/hr faster, it would have taken 4hours less than the scheduled time. And if the train were
sin30
Power Series and Functions We opened the previous section by saying that we were going to start thinking about applications of series and after that promptly spent the section
Parallel to the line specified by 10 y + 3x= -2 In this case the new line is to be parallel to the line given by 10 y ? 3x ? -2 and so it have to have the similar slope as this
Definition 1. Given any x 1 & x 2 from an interval I with x 1 2 if f ( x 1 ) 2 ) then f ( x ) is increasing on I. 2. Given any x 1 & x 2 from an interval
We have independent observations Xi, for i = 1, . . . , n, from a mixture of m Poisson distributions with component probabilities d c and rates l c, for c = 1, . . . ,m. We decid
The football boosters club had 80 T-shirts made to sell at football games. Through mid-October, they had only 12 left. What percent of the shirts had been sold? Denote the numb
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