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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
1
vote
Determining statistical significance of linear regression coefficient in the presence of mul...
I ran a few experiments on simulated data to see which method works best. Please read my findings below.
Lets look at two different scenarios - First where there is no direct relationship between DUI …
1
vote
Accepted
Need clarification on using Qualitative Predictors in the Regression Model
100000,80000,45000,60000,120000,140000,110000,55000,54000,53000,63000,74000)
Gender = c(rep(0,5),rep(1,7))
set.seed(101)
Balance = B0 + B1 * Income + B2 * Gender + rnorm(12)
Now, that we have some simulated data to work with, let us run a regression …
0
votes
Accepted
Variables in a regression which could be zero or intentionally missing
You should not include both the binary variables and the sales values in your regression model as there is a direct relationship between your binary variables and the sales of the respective products. …
2
votes
Compute MAPE with negative actual values
$ MAPE =\frac{100}{n}\sum_{i=0}^n |\frac{ACT_i - PRD_i}{ACT_i}| $
So you need to divide by $|ACT_i|$ and not $ACT_i$
Also, note that MAPE is quite unreliable especially when the actuals take values …