Using Regression Analysis in Excel - Predicting a Value

neoth

Involved In Discussions
#1
hi all,

if i had a set of readings, does anyone knows how do i find the value in between?

x y
9 10
11 12
14 15
18 20
25 30

if i have a table like above, and i wan to find the value of y when x=20, what formulae should i use?

i tried using the regression in excel, but it does nt seem to work.

please help...
 
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S

statdoug

#2
Re: Predict a value

Are you assuming a linear model? if so, you can use the slope function and the intercept function to define the line formula. Then plug in your value for X. To get a predicted Y from a known X is simply Y=mX + b where m=the slope and b=the intercept. This does not give you an indication of the error that you would get with the regression function, but it will give the least squares fit for the data points given.
 

neoth

Involved In Discussions
#4
Re: Predict a value

Not sure why your Excel regression didn't work.

Linearly, Y = 1.2543X - 1.9169. Your R2 is over 99%. At X = 20, Y = 23.169.

Hi Pancho,

thanks for the reply,

but i tried to check back using my original data, when X=14,

Y=(1.25438*14)-1.9169, Y = 15.64,

but base on my original table, when X=14, Y should be = 15.

this is the problem i encounter. anyone knows where goes wrong?

please help.

thanks
 

Pancho

wikineer
Super Moderator
#5
Re: Predict a value

Neoth, this means is that there are other sources of variation on your Y values other than X. You will not get an exact fit from a linear regression unless you only have two points or the data is exactly linear.

You could get an exact fit by using a function (say a polynomial) with independent parameters equal to your number of data points, but that would probably be too contrived and would likely not explain the relationship between X and Y any better than a line does.
 
S

statdoug

#6
Re: Predict a value

Have you looked at a scatter plot? You will see what Pancho is talking about.
 

bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#7
You major error is that the data is not linear (see attached), so therefore using a linear regression will provide a result that is not accurate.
 

Attachments

neoth

Involved In Discussions
#8
ic, so my problem here is my data are not linear,

so in this case, what can i do with this type of non linear data?

regards
 
B

Bill Pflanz

#10
The use of the quadratic equation is overkill for the data analysis. The r square for the linear equation is 0.99384 which means that only 0.006 or 0.6%is unexplained variance and the regression would be considered valid enough to use for prediction.

There is a potential source of error due to the small number of data points used in the analysis. It is also important in regression analysis that there is a real relationship between the two values and not just two random sets of values that have no dependence on each other.

Bill Pflanz
 
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