Hi Gurus,

As I am new to this tool and data analytics in general, just want to understand how the factors work in R (or probably in more general sense).

For example, I have this set of data

```
"indicator" "countrycode" "distance"
0 US 0.1
0 US 0.18
0 US 0.21
0 US 0.19
1 US 0.2
1 US 0.21
0 GB 0.24
0 GB 0.23
0 GB 0.21
0 GB 0.22
1 GB 0.2
1 FR 0.1
```

and want to perform logistics regression model to predict the indicator.

myFullLRModel = glm(indicator ~ countrycode + distance, data=myraw.data, family=binomial)

So I got the result (as below) which it excludes the value for FR which I have expected.

```
Call:
glm(formula = indicator ~ countrycode + distance, family = binomial,
data = myraw.data)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.0474 -0.7889 -0.6405 0.3285 1.9414
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 15.97 3956.18 0.004 0.997
countrycodeGB -20.88 3956.18 -0.005 0.996
countrycodeUS -19.63 3956.18 -0.005 0.996
distance 15.92 28.81 0.552 0.581
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 15.276 on 11 degrees of freedom
Residual deviance: 12.256 on 8 degrees of freedom
AIC: 20.256
Number of Fisher Scoring iterations: 16
```

Now my question is, when I interchanged the values of the country from GB to FR and/or FR to GB, I expected that it will exclude the coefficients for GB, and it will show coefficients for country code â€śFRâ€ť. But results shows differently (as per below)

```
"indicator" "countrycode" "distance"
0 US 0.1
0 US 0.18
0 US 0.21
0 US 0.19
1 US 0.2
1 US 0.21
0 FR 0.24
0 FR 0.23
0 FR 0.21
0 FR 0.22
1 FR 0.2
1 GB 0.1
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -4.903 6.490 -0.755 0.450
countrycodeGB 20.877 3956.182 0.005 0.996
countrycodeUS 1.247 1.689 0.738 0.460
distance 15.916 28.809 0.552 0.581
```

Am I doing something wrong or if this is the expected result, would you be able to explain why is it so? This is just for my further understanding and reference. Thanks.