Linear Regression?
Adele69
Registered Posts: 320
Any suggestions on a good online or book resource which covers this?
My Osbourne Financial Performance book skimmed over this  equation y = a + bx, a line on a graph, Line of Best Fit, Least Squares and mathematic formula not covered, and Budgeting just repeated the earlier content. I can calculate some of these but also get stuck on others. Usually the wording catches me out, so suggesting I don't really understand what is being asked.
My Osbourne Financial Performance book skimmed over this  equation y = a + bx, a line on a graph, Line of Best Fit, Least Squares and mathematic formula not covered, and Budgeting just repeated the earlier content. I can calculate some of these but also get stuck on others. Usually the wording catches me out, so suggesting I don't really understand what is being asked.
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Comments

Which is it you need help with? All mentioned?0

I can work out values of a and b for questions which give two examples for y and x using highlow, and other time series where a period is all but given. However a scenario with several months where highlow proves it isn't a regular variation is...? so my guess is either a line of best fit (never done a question on this) or least square (dont think I've done one of these either). There are no worked examples (Case Studies) for these so really don't know how to identify them.0

Ok, I'm not sure how this will look in a post 
Least squares regression 
To forecast sales make the dependant variable Y and the number of sales people the independent variable X.
So first, some data 
Sales units  Salespersons
236. 11
234. 12
298. 18
250. 15
246. 13
202. 10
So now you need to calculate the sum of, (I can't type the sum of character of sigma, so I'll use E to mean such, also 2 means power of)
So,
Ex 79
Ey 1466
Ex21083
Exy 19736
To calculate B,
n = number of data sets, in this case, 6.
B=nExy  (Ex)(Ey) / nEx2  (Ex)2 = 10.12
Now must find the average of X and Y
So, X = 13.17
Y = 244.33
A is therefore = mean of Y  B(Average of X)
A = 244.33  10.12(13.17) = 111.05
So the least squares of regression is
Y = 111.05 + 10.12x
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