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Dave in naigeria

how to use multiple regression
 
Please can anyone help me solve this problem.

Use linest function to estimate what A,B,C & D will be, Compare them.

Y= a+bx+cx^2+dx^3

assum x=0, x=1, .................. x= 100

Calculate the corresponding value of Y. Choose any coefficient for the
constant.

Thanks and regards,
Dave

Conrad Carlberg

how to use multiple regression
 
As written, your post is a little puzzling.

To use LINEST() you're going to need to start with both a series of X values
and a series of Y values. So you won't "Calculate the corresponding value of
Y," but you can use the regression coefficients and the constant to get
estimates of Y. If what you're really after is the Y estimates, the TREND()
function is more straightforward than LINEST() because it calculates the
equation and applies it to your X values to return the Y estimates. But if
you use LINEST(), and assuming you have Y in column A, X in column B, X^2 in
column C and X^3 in column D, start by selecting a blank range four columns
wide and five rows high, type this formula:

=LINEST(A1:A100,B1:D100,,TRUE)

and array-enter it with CTRL-SHIFT-ENTER instead of just ENTER. You can also
square and cube X in the arguments:

=LINEST(A1:A100,B1:B100^{1,2,3},,TRUE)

What do you want to compare A,B,C & D to? Zero? Something else? Use the
standard errors.

You can force the constant to zero using LINEST's third argument but in
general it's a bad idea.

--
C^2
Conrad Carlberg

Excel Sales Forecasting for Dummies, Wiley, 2005


"Dave in naigeria" <Dave in wrote in
message ...
Please can anyone help me solve this problem.

Use linest function to estimate what A,B,C & D will be, Compare them.

Y= a+bx+cx^2+dx^3

assum x=0, x=1, .................. x= 100

Calculate the corresponding value of Y. Choose any coefficient for the
constant.

Thanks and regards,
Dave




Dave in naigeria

how to use multiple regression
 
Thanks Conrad.
The equation is actually not written well x^2 means x squared and x^3 means
x cube.so the equation is

Y= a + bx + cxsquared + dxcube

"Conrad Carlberg" wrote:

As written, your post is a little puzzling.

To use LINEST() you're going to need to start with both a series of X values
and a series of Y values. So you won't "Calculate the corresponding value of
Y," but you can use the regression coefficients and the constant to get
estimates of Y. If what you're really after is the Y estimates, the TREND()
function is more straightforward than LINEST() because it calculates the
equation and applies it to your X values to return the Y estimates. But if
you use LINEST(), and assuming you have Y in column A, X in column B, X^2 in
column C and X^3 in column D, start by selecting a blank range four columns
wide and five rows high, type this formula:

=LINEST(A1:A100,B1:D100,,TRUE)

and array-enter it with CTRL-SHIFT-ENTER instead of just ENTER. You can also
square and cube X in the arguments:

=LINEST(A1:A100,B1:B100^{1,2,3},,TRUE)

What do you want to compare A,B,C & D to? Zero? Something else? Use the
standard errors.

You can force the constant to zero using LINEST's third argument but in
general it's a bad idea.

--
C^2
Conrad Carlberg

Excel Sales Forecasting for Dummies, Wiley, 2005


"Dave in naigeria" <Dave in wrote in
message ...
Please can anyone help me solve this problem.

Use linest function to estimate what A,B,C & D will be, Compare them.

Y= a+bx+cx^2+dx^3

assum x=0, x=1, .................. x= 100

Calculate the corresponding value of Y. Choose any coefficient for the
constant.

Thanks and regards,
Dave





Conrad Carlberg

how to use multiple regression
 
The equation is actually not written well x^2 means x squared and x^3 means
x cube.so the equation is

Y= a + bx + cxsquared + dxcube


That much was clear.
--
C^2
Conrad Carlberg

Excel Sales Forecasting for Dummies, Wiley, 2005


"Dave in naigeria" wrote in
message ...
Thanks Conrad.
The equation is actually not written well x^2 means x squared and x^3

means
x cube.so the equation is

Y= a + bx + cxsquared + dxcube

"Conrad Carlberg" wrote:

As written, your post is a little puzzling.

To use LINEST() you're going to need to start with both a series of X

values
and a series of Y values. So you won't "Calculate the corresponding

value of
Y," but you can use the regression coefficients and the constant to get
estimates of Y. If what you're really after is the Y estimates, the

TREND()
function is more straightforward than LINEST() because it calculates the
equation and applies it to your X values to return the Y estimates. But

if
you use LINEST(), and assuming you have Y in column A, X in column B,

X^2 in
column C and X^3 in column D, start by selecting a blank range four

columns
wide and five rows high, type this formula:

=LINEST(A1:A100,B1:D100,,TRUE)

and array-enter it with CTRL-SHIFT-ENTER instead of just ENTER. You can

also
square and cube X in the arguments:

=LINEST(A1:A100,B1:B100^{1,2,3},,TRUE)

What do you want to compare A,B,C & D to? Zero? Something else? Use the
standard errors.

You can force the constant to zero using LINEST's third argument but in
general it's a bad idea.

--
C^2
Conrad Carlberg

Excel Sales Forecasting for Dummies, Wiley, 2005


"Dave in naigeria" <Dave in wrote in
message ...
Please can anyone help me solve this problem.

Use linest function to estimate what A,B,C & D will be, Compare them.

Y= a+bx+cx^2+dx^3

assum x=0, x=1, .................. x= 100

Calculate the corresponding value of Y. Choose any coefficient for the
constant.

Thanks and regards,
Dave







Jerry W. Lewis

how to use multiple regression
 
Conrad already explained how to fit a cubic polynomial with LINEST. An
alternative to using the LINEST coefficients to predict y values at 1 to
100 would be

=TREND(known_ys,known_xs^{1,2,3},ROW(A1:A100))

array entered.

Jerry

Dave in naigeria wrote:

Please can anyone help me solve this problem.

Use linest function to estimate what A,B,C & D will be, Compare them.

Y= a+bx+cx^2+dx^3

assum x=0, x=1, .................. x= 100

Calculate the corresponding value of Y. Choose any coefficient for the
constant.

Thanks and regards,
Dave




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