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Thursday, July 26, 2012

Basics of exponential functions



An exponential function is a function of the form y = a^x where a belongs to positive real numbers and x is any real number. We shall first try to understand such numbers with the help of graphs.

Exponential function graph:
Let us try to graph exponential function y = 2^x. So here we see that a = 2 (which is a positive real number and x is any real number). To obtain certain number of points on the graph we construct the following table:




Note that both the above functions are not inverse of each other. With this understanding, let us now define an exponential function.

Definition: Let a belongs to R+. Then the function f: R ->R+, f(x) = a^x is called an exponential function. a is the base of the function. The corresponding exponential function equation would be: y = a^x
For example:
f(x) = 3^x, g(x) = (1/4)^x (where x belongs to R), h(x) = 1^x, (where x belongs to R), are all exponential functions.

Natural exponential function:
We are familiar with the irrational number pi which we come across in connection with the area and circumference of a circle. There is another important irrational number, which is denoted by e and which lies between 2 and 3. Its approximate value is 2.71828. Exact value of e is given by the sequence: e = 1/0! + 1/1! + 1/2! + 1/3! + 1/4! + 1/5! + 1/6! + ....An exponential function to the base e, f:R->R+, f(x) = e^x is called the natural exponential function. This function is very often used in study of various branches of science and math.

Inverse of exponential function:
Inverse of an exponential function is a logarithmic function. In other words, the exponential function and the logarithmic function are inverses of each other. Thus, if f:R->R+, f(x) = a^x, a belongs to R+ -{1}, then f^(-1):R+->R, f^(-1)(x) = log(a)x [read that as log of x base a]

Derivative of exponential function:
Based on limit definition of derivatives, the derivative of an exponential function can be shown as follows:
If y= a^x, then dy/dx = (a^x)Ln(a)

Wednesday, July 18, 2012

Trigonometry Made Simple



Introduction to Trigonometry:
Trigonometry is a derived from a Greed word ‘tri’ (meaning three) and ‘gon’ (meaning sides and ‘metron’ (meaning measure). Trigonometry is the study of relationships between the sides and angles of a triangle. The earliest known work on Trigonometry was recorded in Egypt and Babylon. Early Astronomers used it to find out the distances of the stars and planets from the Earth. Even today, most of the technologically advanced methods used in Engineering and Physical Sciences are based on Trigonometric concepts.

The Trigonometric Ratios of the angle A in right triangle ABC are defined as:
Sine of angle A = (side opposite to angle A)/hypotenuse; cosec = 1/Sine
Cosine of angle A = (side adjacent to angle A)/hypotenuse; sec = 1/cosine
Tangent of angle A = (side opposite to angle A)/(side opposite to angle A); cot =1/tan
The trigonometric ratios of an acute angle in a right triangle express the relationship between the angle and the lengths of its sides

Trigonometry Problems and Answers:
Problem: Given angle A=51 degrees, Adjacent side length = x and opposite side length = 10. Find x and H, hypotenuse of the triangle
Answer: tan(A) = opposite side/adjacent side
tan(51)= 10/x
X = 10/(tan 51) = 8.1 (two significant digits)
Sin(A) = opposite side/hypotenuse
Sin(51) = 10/H
H = 10/ Sin(51) = 13 (two significant digits)
x=8.1 and H=13

Problem: If sin 3A = cos (A- 26 degrees), where 3A is an acute angle, find the value of A
Answer:  sin 3A can be written as cos (90-3A)
      So, we get            cos (90-3A) = cos(A-26degrees)
Since both 90-3A and A-26 are both acute angles,
90 – 3A = A- 26
4A = 116
A = 29 degrees

Problem:  An observer 1.5m tall is 28.5 m away from a chimney. The angle of elevation of the top of the chimney from his eyes is 45 degrees. Calculate the height of the chimney.
Answer: Let us draw a rough triangle ABC with the right angle at B. let us draw a line DE parallel to BC such that AB (AE+EB) will be the height of the chimney,  CD (equal to BE) the observer and Angle ADE, the angle of elevation.  Here, ADE is the right triangle, right-angled at E
We have, AB = AE +EB = AE +1.5 DE = CB = 28.5 (distance from the chimney)
Let us use the tangent of the angle of elevation
tan(45degrees) = AE/DE
1 = AE/28.5
AE= 28.5
Height of the chimney = AE +EB =28.5 +1.5 = 30 m

Parallelogram Definition


Let us learn about the Parallelogram Definition general, the diagonals of a parallelogram are having different lengths. The two diagonals in the figure which intersects at a particular point and lie in the interior part of parallelogram. When two pairs of the sides are opposite and they are parallel to each other.Then it is called as parallelogram .Now let us see about the parallelograms sides introduction.In parallelograms introduction, we can draw a pair of parallel lines. Draw another pair of parallel lines intersecting the former.Thus the parallelogram can be formed.Thus we can say that the pair of opposite sides of parallelogram is of equal length. Similarly we can also learn about other topics such as types of lines.Hope you like the above example of Parallelogram Definition.Please leave your comments, if you have any doubts.

Wednesday, July 11, 2012

Absolute Measures of Dispersion


One can define dispersion and measure it in different ways. The common dispersion definition is: “way to measure variation of data”. In general, if the dispersion is large then the variation of variable values will be huge. If the dispersion is small, then the variation is close.

Different Measures of Dispersion
The measures of dispersion can be classified into two types namely Absolute measures of dispersion and Relative measures of dispersion. Rest of the article covers these two types in detail.

Absolute Measures of Dispersion
The statistical data observations will generally be specified in some units. If the dispersion values have to be specified in the same units as that of the statistical data, then you have to choose an absolute measure of dispersion. For example, if the statistical data is represented in grams then the measure of dispersion must also be in grams.

There are various absolute measures of dispersion. Commonly used absolute measures are:
Range
Mean Deviation
Variance and Standard Deviation

Here is an overview and example of one absolute measure called Range:

The Range is the simplest measure of dispersion. It is the difference between the top most value and the lowest value in the statistical set of data provided. For example, Jackson took 5 Mathematics tests in one period of time. The test marks are: 70, 60, 50, 80, and 90. What is the range of the marks? The range is calculated by subtracting the lowest value 50 from the highest value 90 and the result will be 40. Thus, the range is 40.

Relative Measures of Dispersion
If you have to compare dispersion of two or more statistical data sets which are of different units, then you have to opt for relative measures of dispersion. These dispersion measures are dimensionless and they are used to establish dispersion relation between any data sets. Common relative measures of dispersion are:
Coefficient of Range
Coefficient of Mean Deviation
Coefficient of Variation
Coefficient of Standard Deviation

Here is an overview and example of one absolute measure called Coefficient of Variation:

The coefficient of variation is the percentage of variation obtained by dividing standard deviation by mean. For example, a school has two sections for X standard. The average score of students in first section are 85 and the second section average scores are 80. The standard deviations of the two sections are 8 and 7 respectively. Which X standard section has large variation in its scores?

In this problem, the average score denotes the mean and the values of standard deviation are also specified. Now to find the variation of data by calculating coefficient of variation:

Coefficient of variance of section A is 9.4%, which is obtained by dividing standard deviation value 8 by the mean 85 and multiplying the result 0.2 by 100.

Coefficient of variance of section B is 8.75%, which is obtained by dividing 7 by 80 and multiplying the result by 100.

Comparing both the coefficients, section A is consistent when compared to section B. Hence, section B has large variation in its scores.

Monday, July 2, 2012

Harmonic Mean


Harmonic Mean
Harmonic Mean
Mean is an important concept in measures of central tendency. Measures of central tendency give the measure for the center of the data. We have different types of measures of central tendency those are Mean, Median and Mode. Mean is classified into three parts those are Arithmetic Mean, Geometric Mean and Harmonic Mean. Arithmetic Mean is simply the ratio of sum of observations and the number of observations. Geometric Mean is the nth root of the product of the observations, where ‘n’ is the number of observations. What is Harmonic Mean? Harmonic Mean Definition is the reciprocal of arithmetic mean of the reciprocal of the observations. Depends on the situation we have to know which mean is correct. We have relation among these three means, that is, Arithmetic Mean = Geometric Mean = Harmonic Mean. Harmonic Mean Formula can be described as

Weighted Mean is useful in some cases where each
observation do not have an equal importance. In general arithmetic mean we are giving equal importance to each observation but this is not always the case. When all the observations are not equally important then we have to use weighted arithmetic mean. In weighted arithmetic mean we do not take sum of the observation we multiply the observations with respect to their corresponding importance. In Weighted Harmonic Mean is the reciprocal of weighted arithmetic mean of the reciprocal of observations.

Harmonic Means may not applicable in all cases if zero value present in the observations then reciprocal of zero do not exist, hence harmonic mean also do not exist. Harmonic Mean is useful when there are extreme values present in the data then it gives true picture of the average of the data. The Harmonic Mean is better average when the numbers are defined in a relation to some unit.

 For example in case of averaging speed Harmonic Mean is better measure than Arithmetic Mean. Suppose we have to find the average speed of a person travelling from place A to place B. If the person travelling with 10kmph in first hour and 15kmph in second hour then the average speed is the arithmetic mean. If the person travels first half distance with the speed 10kmph and remaining distance with the speed 15kmph then Harmonic Mean is better measure then arithmetic mean. Harmonic Mean is also called as sub- contrary mean. Harmonic Mean is useful in case of finding averages involving rates and ratios.