integral of 1 / sqrt[4 + 3x - x² ] using completion of squares method
integrate after completing the square
to make the coefficient of x² (+1) , take -1 common , but it
remains inside the sqrt sign
to get sqrt [ - (
x² -3x - 4)] now take half the coefficient of x , that is half of
(-3)
to get [x- (3/2) ]² and then adjust the constant term and finally
re introduce the -1 taken out earlier
PAGE 1 BASIC INTEGRATION
PAGE 2 INTEGRATION BY SUBSTITUTION
PAGE 3 INTEGRATION BY COMPLETION OF SQUARES
PAGE 4 INTEGRATION BY PARTS
PAGE 5 INTEGRATION BY MANIPULATION OF NUMERATOR IN TERMS OF DENOMINATOR
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Monday, January 16, 2017
integral using completion of squares method
integral using completion of squares method
integral of 1 / [(x^2) - x +1 ]
completion of squares method is used if there is a (x^2) term and a x term
remember to make the coefficient of x² unity
take half the coefficient of x that is half of (-1)
so that you get [ x -(1/2) ]² , then adjust the constant term
PAGE 1 BASIC INTEGRATION
PAGE 2 INTEGRATION BY SUBSTITUTIONPAGE 3 INTEGRATION BY COMPLETION OF SQUARES
PAGE 4 INTEGRATION BY PARTS
PAGE 5 INTEGRATION BY MANIPULATION OF NUMERATOR IN TERMS OF DENOMINATOR
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There is no guarantee about the data/information on this site. You use the data/information at your own risk. You use the advertisements displayed on this page at your own risk.We are not responsible for the content of external internet sites. Some of the links may not work
integral of 1 / [(x^2) - x +1 ]
completion of squares method is used if there is a (x^2) term and a x term
remember to make the coefficient of x² unity
take half the coefficient of x that is half of (-1)
so that you get [ x -(1/2) ]² , then adjust the constant term
PAGE 1 BASIC INTEGRATION
PAGE 2 INTEGRATION BY SUBSTITUTIONPAGE 3 INTEGRATION BY COMPLETION OF SQUARES
PAGE 4 INTEGRATION BY PARTS
PAGE 5 INTEGRATION BY MANIPULATION OF NUMERATOR IN TERMS OF DENOMINATOR
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There is no guarantee about the data/information on this site. You use the data/information at your own risk. You use the advertisements displayed on this page at your own risk.We are not responsible for the content of external internet sites. Some of the links may not work
if z = xy / (x-y), show that x² (∂ ²z / ∂x²) + 2xy (∂ ²z / ∂x∂y) + y² (∂ ²z / ∂y²) = 0
.Let u be a function of x, y , z where x , y, z are independent variables and u depends on x, y ,z..When doing partial differentiation w.r.t x, we treat x alone as the independent variable and treat y and z as constants.
The partial derivative of u with respect to x is usually denoted by ∂u / ∂x
If ∂u / ∂x is again differentiated partially with respect to x we get the partial derivative denoted as ∂ ²u / ∂x²
If ∂u / ∂x is again differentiated partially with respect to y we get the partial derivative denoted as ∂ ²u /∂y ∂x
If ∂u / ∂y is again differentiated partially with respect to x we get the partial derivative denoted as ∂ ²u /∂x ∂y
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.Let u be a function of x, y , z where x , y, z are independent variables and u depends on x, y ,z..When doing partial differentiation w.r.t x, we treat x alone as the independent variable and treat y and z as constants.
The partial derivative of u with respect to x is usually denoted by ∂u / ∂x
If ∂u / ∂x is again differentiated partially with respect to x we get the partial derivative denoted as ∂ ²u / ∂x²
If ∂u / ∂x is again differentiated partially with respect to y we get the partial derivative denoted as ∂ ²u /∂y ∂x
If ∂u / ∂y is again differentiated partially with respect to x we get the partial derivative denoted as ∂ ²u /∂x ∂y
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index of math problems
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Wednesday, January 11, 2017
correlation and regression formulae
correlation and regression formula
karl pearson's correlation coefficient formula is usually used as a measure of the linear relationship between x and y.
The regression line of yon x is supposed to be a linear relation between y and x derived on the assumption that y depends on x and it is assumed that x is independent and the assumption is vice versa for the regression line of x on y
karl pearson's correlation coefficient formula is usually used as a measure of the linear relationship between x and y.
The regression line of yon x is supposed to be a linear relation between y and x derived on the assumption that y depends on x and it is assumed that x is independent and the assumption is vice versa for the regression line of x on y
correlation and regression formula , regression line of x on y, regression line of y on x, covariance formula , limits for the correlation coefficient
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There is no guarantee about the data/information on this site. You use the data/information at your own risk. You use the advertisements displayed on this page at your own risk.We are not responsible for the content of external internet sites. Some of the links may not work
Tuesday, January 10, 2017
power series for arc [ tan (x) ]
power series for arc [ tan (x) ] in powers of x
power series for inverse function of tan(x)
let y = arc [ tan (x) ]
differentiate y with respect to x once to get y' and find y'(0)
then expand the derivative [ 1 + x^2]^ (-1) using binomial series
now you can differentiate the series as many times as you want and replace x with 0 .
Use the values to substituted into Mc laurin's series or Taylor's series.
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power series for inverse function of tan(x)
let y = arc [ tan (x) ]
differentiate y with respect to x once to get y' and find y'(0)
then expand the derivative [ 1 + x^2]^ (-1) using binomial series
now you can differentiate the series as many times as you want and replace x with 0 .
Use the values to substituted into Mc laurin's series or Taylor's series.
mclaurin's power series for ln(1+x)
approximation of an integral using binomial series
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Wednesday, January 4, 2017
hyperbolic function , relation with ordinary trigonometric functions , identities
hyperbolic function , relation with ordinary trigonometric functions , identities
hyperbolic functions usually refers to relations involving the exponential functions e^x and e^(-x).
They are denoted by functions like sinh(x) pronounced something like shine(x), cosh(x), tanh(x) , cosech(x), sech(x), coth(x) etc. The relationship with ordinary trigonometric functions and some identities involving hyperbolic functions is given below.

sinh(0) = 0
cosh(0) =1
tanh(0) = 0
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hyperbolic functions usually refers to relations involving the exponential functions e^x and e^(-x).
They are denoted by functions like sinh(x) pronounced something like shine(x), cosh(x), tanh(x) , cosech(x), sech(x), coth(x) etc. The relationship with ordinary trigonometric functions and some identities involving hyperbolic functions is given below.

sinh(0) = 0
cosh(0) =1
tanh(0) = 0
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Monday, January 2, 2017
probability distribution and the mean number of the number of heads in the simultaneous tosses of three coins
Find the probability distribution of the number of heads in the simultaneous tosses of three coins (or number of heads in three tosses of a coin). Also find the mean number of heads.
Let X be the number of heads in simultaneous tosses of three coins.
X can take the values X = 0,1,2,3
Sample space = { HHH,HHT,HTH,THH,HTT,THT,TTH,TTT }
n(S) = 8
P[X=0] =P[no head] = P[{ TTT }] = ( 1/8 )
P[X=1] =P[one head] = P[{ HTT,THT,TTH }] = ( 3/8 )
P[X=2] =P[two heads ] = P[{ HHT,THH,HTH }] = ( 3/8 )
P[X=3] =P[three heads] = P[{ HHH}] = ( 1/8 )

Mean =E[X] = 0( 1/8 ) + 1(3/8 ) + 2 ( 3/8 ) + 3( 1/8 ) = (12/8) Mean = (3/2) = 1.5
=========================================================================
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Let X be the number of heads in simultaneous tosses of three coins.
X can take the values X = 0,1,2,3
Sample space = { HHH,HHT,HTH,THH,HTT,THT,TTH,TTT }
n(S) = 8
P[X=0] =P[no head] = P[{ TTT }] = ( 1/8 )
P[X=1] =P[one head] = P[{ HTT,THT,TTH }] = ( 3/8 )
P[X=2] =P[two heads ] = P[{ HHT,THH,HTH }] = ( 3/8 )
P[X=3] =P[three heads] = P[{ HHH}] = ( 1/8 )

Mean =E[X] = 0( 1/8 ) + 1(3/8 ) + 2 ( 3/8 ) + 3( 1/8 ) = (12/8) Mean = (3/2) = 1.5
=========================================================================
A
random variable X has the following probability distribution:
Find
(i) k (ii) P(X <
3)(iii) P(X > 6) (iv) P(0 < X < 3)
Sum
of all values of P[X] = 1
0
+ k + 2k
+ 2k + 3k
+ k2 + 2k2
+ 7k2+k
= 1
10k2
+ 9k = 1
10k2
+ 9k – 1=0
10k2
+ 10k - 1k – 1=0
10k(k+1)
-1 (k+1) = 0
(10k-1)
(k+1) = 0
k
= (1/10) or k = (-1)
Since
probability cannot be negative , we reject k = (-1)
therefore
k = (1/10)
==========================================================================
Two
numbers are selected at random (without replacement) from the first
six positive integers. Let X denote the larger of the two numbers
obtained. Find E(X).
Let
X be the larger of the two numbers.
X
can take the values 2,3,4,5,6
If
S is the sample space
S
= { (1,2), (1,3),(1,4),(1,5),(1,6),
(2,1),(2,3),(2,4),(2,5),(2,6),(3,1),
(3,1),(3,2),(3,4),(3,5),(3,6),(4,1),(4,1),(4,1),(4,2),(4,3),(4,5),(4,6),(5,1),(5,2),(5,3),(5,4),(5,6),(6,1),(6,1),(6,2),(6,3),(6,4),(6,5)}
n(S)
= 6*5 =30 [since replacement is not allowed]
P[X=2]
= n[{(1,2),(2,1)}] / 30 = (2/30)
P[X=3]
= n[{(1,3),(2,3),(3,1),(3,2)}] / 30 = (4/30)
P[X=4]
= n[{(1,4),(2,4),(3,4),(4,1),(4,1),(4,2),(4,3)}] / 30 = (6/30)
P[X=5]
= n[{(1,5),(2,5),(3,5),(4,5),(5,1),(5,2),(5,3),(5,4)}] / 30 = (8/30)
P[X=6]
=
n[{(6,1),(6,1),(6,2),(6,3),(6,4),(6,5),(1,6),(2,6),(3,6),(4,6),(5,6)}]
= (10/30)
Mean
= E[X] = 2 (2/30) + 3(4/30) + 4(6/30) + 5 (8/30) + 6 (10/30) =
Mean
= (140/30) = (14/3)
================================================
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