A short note on inverse trig functions

Introduction:
We know that not every function as an inverse. A function has an inverse if and only if it is one to one and onto. As all trigonometric functions are periodic, they are all many to one type of functions. So technically, inverse of trig functions do not exist. But if we can suitably restrict the domain of the trigonometric function , then it becomes one to one and onto. Therefore with this modified domain the trigonometric function can have an inverse. Let us look at the following examples:

Inverse trig functions examples:

1. Inverse of sine function:
The sine function defined as follows: sin = {(x,y) | y = sin(x), x belongs to R, y belongs to [-1,1]} is an onto function. It is a many to one function. It is a periodic function with at period of 2belongs tobelongs to. But instead of R, if the domain is restricted to say, [-pi/2,pi/2], or [pi/2,3*pi/2], or [3pi/2, 5pi/2] etc, then it becomes one to one and still remains onto. Thus now we can define the inverse of sin function using any one of the above domains as follows: sin^(-1) = [(y,x) | y = sin(x), x belongs to [-pi/2,pi/2], y belongs to [-1,1]}, where “sin^(-1)” is the symbol for inverse sine function.

2.  Inverse of cosine function:
Just like how we defined the inverse of sine function, we can define the inverse of cosine function by restricting its domain as well. The domain restrictions can be made to suite our purpose. Therefore, inverse cosine function can be defined as follows: cos^(-1) = [(y,x) | y = cos(x), x belongs to [0,pi], y belongs to [-1,1]}

The other trigonometric function inverses can also be defined similarly.

Interrelations between inverse trigonometric functions:
Sin^(-1) x = cosec^(-1)(1/x), or cosec^(-1)(x) = sin^(-1)(1/x). The inverse functions of cos and sec  and the inverse function of tan and cot are related the same way.

Integral of inverse trig functions:
To find integral of inverse trigonometric functions, we use the method of integration by parts. We know that we follow the order LIATE (Logarithmic, Inverse Trigonometric, Algebraic, Trigonometric, Exponential function) for integration by parts. When we integrate inverse trigonometric functions, the inverse function becomes the u of the integration by parts and since there is no other function it is multiplied to, we take v = 1. Thus for example, if we were to integrate the function like tan^(-1)x using the integration by parts rule, then here u = tan^(-1)x and v = 1 and then integrate using integration by parts.

Trigonometric Identities

A function is a mathematical statement relating the different variables. When we assign the values for a set of independent variables, we get the definite value for the dependent variable.
Identity is a mathematical expression, which is valid for all the values of the variables. When the identity has terms involving the algebraic expression we call it as algebraic identity and the function involving the trigonometric expressions are called trigonometric identities.
Verifying Trigonometric identities:
Identities are mathematical statements that are valid for all the values of the variables. For example
(a +b)^2 = a^2 +2ab +b^2

The above expression is valid for all the values of ‘a’ and ‘b’. Trigonometry is the field of study involving triangles’ sides and angles. If the identity has any of the trigonometric functions, then it is called trigonometric identity. As the trigonometric functions are related to the angles, we substitute the angles in the functions of identities. We adopt the following steps to verify an identity.
Step 1: Choose an angle from the defined domain.
Step 2: Replace the variable by the chosen value
Step 3: Evaluate the function and simplify
Example: Sin^2 (x) + cos 2(x) =1
Step 1: For the value of x = 90
Step 2: Sin^2 (90) + cos^2 (90)
Step 3: 1+ 0 =1. Hence verified

Fundamental Trigonometric Identities
Trigonometry, a field of study involving the sides and angles of a triangle has a set of fundamental definition of trigonometric functions. Using the theorem of Pythagoras, we have three fundamental trigonometric identities called as Pythagorean identities, which are as follows.

In a triangle ABC:
(1) 1 = sin^2 (A) +cos^2 (A)
(2) 1+ tan^2(A) = sec^2(A)
(3) 1+ cot^2(A) = cosec^2(A)

Simplifying Trigonometric Identities
To simplify a given trigonometric identity, we always rely on the algebraic methods. Especially, we adopt PEMDAS/ BOADMAS in simplifying the identities.  In addition to this, we use the above three identities in simplifying the given trigonometric identities. At the same time, we ensure that the defined trigonometric identity is a valid one in the defined domain of variables.

Table of Trigonometric Identities:
The fundamental trigonometric identities are as follows
Reciprocal Identities:
Sec(A) = 1/cos(A) Cosec (A) = 1/ Sin(A) tan(A) = sin(A)/cos(A),   cot(A) = 1/ Tan(A)= cos(A)/sin(A)

Pythagorean Identities
(1) 1 = sin^2 (A) +cos^2 (A) (2) 1+ tan^2(A) = sec^2(A) (3) 1+ cot^2(A) = cosec^2(A)

Even-Odd Identities
(1) Sin (-A) = -sin(A) (2) cos(-A) = cos (A) (3) tan(-A) = -tan (A)
(4) Cosec (-A)= -cosec(A) (5) sec(-A)= -sec A (6) cot(-A) = -cot(A)

Standard deviation is a Measure of Dispersion

When we are dealing with data sets experimenter is interested to know two things about data set. Those are Measures of Central Tendency and Measures of Dispersion. Measures of Central Tendency are Mean, Median and Mode. Measures of Dispersion are Inter Quartile Range, Range, Mean deviation, Standard deviation and Variance. Measures of Central Tendency give the measures for center of the data. Measures of Dispersion give the measure for the variation in the data.

That is, it explains how much the data spread. Range is one type of measure of dispersion and it is the difference between maximum and minimum value in the data. It depends only on the extreme values and it neglects remaining values this is the drawback for this method. Inter Quartile Range is the difference between first and third quartiles. It gives the percentage of observations in between first and third quartile. In this case also it depends only on the first and third quartile values and neglecting remaining values. To come over from this drawback we can use Mean Deviation which includes each and every observation.

Main drawback of Mean Deviation is dealing with mathematical operations like differentiations and integrations are quite difficult. To come over from this drawback we can use Standard Deviation and Variance. Variance is the average of squared differences of the observations from their mean. Standard Deviation is the square root of the Variance. When we do not know standard Deviation for the population (It is a collection of huge similar type of items) then we have to estimate it by sample standard deviation. Symbol for Standard Deviation is’ ’. Symbol for Sample Standard Deviation is‘s’ Sample Standard Deviation Formula is .

Where ‘n’ is the sample size. Standard Deviation of the constant variable is zero. Constant variable means a variable which takes a fixed and single value. For example, a variable which takes only value 5 is called as constant variable and standard deviation of such variable is zero. For clear understanding of standard deviation, Standard Deviation Examples are discussed below. When we are Adding Standard deviations we cannot add them simply. First we have to square each individual standard deviation to make them variances. Now add these variances and take square root of this to add standard deviations. For subtracting standard deviations also we have to do the same thing. Standard Deviation Problems are not solvable directly first we have to find out the variance and then by taking square root of it we can get standard deviation. Standard Deviation Example, for the data 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. Variance is 9.1667 and standard deviation is 3.02765. Mean of this data is 4.5 here the standard deviation value explains the average distance of the observations from its mean 4.5.


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Mode definition

Mode (statistics) is the value of the variable corresponding to the maximum of the ideal curve which gives the closest possible fit to the actual distribution of the frequency. It represents the value which is the most frequent or typical, the value which is, in fact, the fashion. The mode is sometimes denoted by writing the sign ? over the variants symbol, for example X? denotes the mode of the values X1,X2, …. Xn.

Mode formula:

It is evident that, mode is to be determined by inspection only. There is no stereotyped method listed for determination of the mode for a data set. It purely depends on the intuitions of the statistician or researcher. However there is an empirical relation between the mean, median and mode.
Mode = Mean – 3*(Mean – Median).
The above relation holds good with surprising closeness for moderately asymmetrical distributions.  Putting that in words, we say that the median lies one third of the distance mean to mode from the mean towards the mode.

Usually mode represents a single humped distribution unless specifically stated otherwise. When the distribution is of a complicated form, there may be more than one mode. Such distributions are therefore sometimes called multimodal. The mean and the median are still unique for such distributions.

What is mode for grouped frequency distribution:

Based on how we define mode, it is in fact difficult to determine the mode for grouped frequency distributions that are more common in practice. At max we can find the class with the maximum frequency. But beyond that it’s no use giving merely the mid value of the class interval into which the greatest frequency falls, for this is entirely dependent on the choice of the scale of the class intervals. It is again no use making the class interval very small to avoid error on that account, for the class frequencies will them become small and the distribution irregular. What we actually want to arrive is at the mid value of an interval for which the frequency would be a maximum, if the intervals could be made indefinitely small and at the same time the number of observations be so increased that the class frequencies should run smoothly. As the observations cannot, in a practical case, be indefinitely increased, it is evident that some process of smoothing out the irregularities that occur in the actual distribution must be adopted, in order to ascertain the approximate value of the mode.

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Simplifying exponents

To understand simplification of exponents we first need to establish the rules of exponents.

Exponent rules:
1. b^m * b^n = b^(m+n)
2. b^m/b^n = b^(m-n)
3.(b^m)^n = b^mn
4.v(n&b^m ) = b^(m/n)

Exponentiation:

We know that multiplication corresponds to repeated addition. In the same way, exponentiation corresponds to repeated multiplication. In other words, exponentiation refers to the process of repeated multiplication. For example we can write, 4*4*4 as 4^3 or 5*5*5*5 = 5^4 etc. In general terms, b*b*b*b…. n times = b^n. Here, b is the base and n is called the exponent or the index.

b^2 is usually read as b squared. b^3 is read as b cubed; where as b^4 is read as ‘b raised to power 4’. In the same way b^(any other number) is read as ‘b raised to the power ______’.

Properties of exponents:
1. Exponent can be any real number.
2. When exponent is zero, the value of the term becomes equal to 1. That is to say that b^0 = 1
3. Exponent of one results in the base itself. So, b^1 = b.
4. ?(b?^(n)m) is not the same as b^(n^m ). ?(b?^(n)m) = b^mn where as b^(n^m ) = b^n^m.
5. When exponent is negative it is same as the positive exponent of the reciprocal of base. So, b^(-n) = (1/b)^n.

Rational exponents:

We saw above that exponent can be any real number. But for now we shall look at rational exponents only. A rational exponent would be of the type m/n. Therefore the number with rational exponent would look like this : b^(m/n). Based on the rules of exponents that we saw earlier, we can say that, b^(m/n) = v(n&b^m ). In other words it’s the nth root of b raised to power m. A number with a rational exponent may or may not itself be a rational number. For example, 4^(8/4) = 4^2 = 16. However, 3^(5/2) can be written as v(2&3^5 ) = v(3^4 * 3^1) = 3^(4/2) * 3^(1/2) = 3^2 * 3^(1/2) = 9 * v(3) = 9v(3) is an irrational number.

Solved examples:

1. Simplify: x^6 * x^5
Solution: x^6 * x^5 = x^(6+5) = x^11

2. Simplify: t^10/t^8
Solution: t^10/t^8 = t^(10-8) = t^2

3. Simplify: 5x^3/3x^5
Solution: 5x^3/3x^5 = (5/3)*(x^3/x^5) = (5/3) * (x^(3-5)) = (5/3) * x^(-2) = 5/3x^2

4. Simplify: (125x^2y^3z^2)^0
Solution: (125x^2y^3z^2)^0  = 1. That is because when exponent is zero, the term becomes = 1

What is a ratio

What is a ratio? A ratio is a comparison of two quantities by division. A ratio actually compares one thing happening to another. Ratios compares two or more amounts and are often expressed as fractions in simplest form or as decimals. Ratio can be written in three different ways:-

Example of a ratio

1. Using a colon like 3:2
2. Using a fraction like 3/2
3. Using the word “ to” like 3 to 2

Ratio Example: - Sam has 4 apples and 9 bananas. What is the ratio of his apples to bananas?
Solution: - Total numbers of apples are 4 and bananas are 9. SO the ratio will be 4:9.

Multiplying and dividing any ratio by same non- zero number makes no difference to the ratio. For example, the ratio 3:9 is equal to 1:3.
Two ratios that name the same number are equivalent ratios.  Equivalent ratios can be calculated by multiplying or dividing each term of the ratio by the same non - zero number.

For example: - If we have a ratio 2:7, multiplying both terms by 3 gives a new ratio 6:21
Hence, 2:7 and 6:21 are equivalent ratios.
If we have 12:3, if we reduce this fraction, we get 4:1
Hence 12:3 and 4:1 are equivalent ratios.
Now let us learn about ratio and rates. A rate is a ratio involving two quantities in different units. The rate 225 heartbeat/ 3minutes compare heartbeat to minutes. If the denominator is 1 then it is known as the unit rate. Therefore,
225 heartbeat/3 minutes = 75 heartbeat / 1 minute.
Hence, the unit rate is 75 heartbeats per minute.

Equivalent rates have the same value but use different measurements. We use equivalent rates to help us with unit conversions.

For example: - A jet flies 540 miles per hour. What is the rate in miles per minute?
Solution: - 540 miles/ 1 hour = 1hour/60 min
After simplifying, we get 9 miles per minute.

Bias

Let's learn about bias statistics in today's post.

There are four different types of bias in statistics:

• Spectrum bias
• Omitted variable bias
• Systematic bias
• Cognitive bias

Next time i will help you with the concept of statistics formulas.

Also you can avail help from expert online tutors. Not just in statistics but from an algebra tutor as well.

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