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Assume the following relation:
Z = X^2 + Y^2 + C

We select Z as top goal (after providing a dimension to Z, like [-]) and give values to X, Y and C.
X=1, Y=1, C=1

Now there is a single result for Z (=3). We restart this solution and provide ranges for X, Y and C (in our example 1(1)5 for all parameters). When Quaestor asks whether it should be a case matrix we confirm. The result is a table (matrix) of X, Y, Z and C values  (below a cut out of the result as TeLiTab: in the solution do All to Clipboard and choose Preview).

0
4 "C" "X" "Y" "Z"
"1" 1 1 1 3
"2" 1 1 2 10
... ... ... ... ...
"124" 5 5 4 94
"125" 5 5 5 155

When we go to the solution and right click in the gray area, you see that the option Make Polynome is available. When you select this option, Quaestor will first ask you the number of terms to use for the polynome. The maximum number of terms indicated by Quaestor is based on the dataset you have selected. More terms means a better fit for values close to the datapoints. Because the polynome will be come more "flexible" deviation for values between datapoint may increase (so higher is not always better).

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The result for our example:

Solution/Object: Z

Relation:
Z = POL(1, 4, "A", "B", "C", "D", X, Y, C)

Polynomial coefficients:
|POL1|
0
4 "A" "B" "C" "D"
"1" -8.56273235830528E-14 0 0 0
"2" 1.00000000000002 0 0 1
"3" -3.87168071041632E-16 0 0 3
"4" 4.03169945720986E-15 0 2 0
"5" 1 0 3 0
"6" -9.73589332852376E-18 1 2 3
"7" 1 2 0 0
"8" 7.11044502677828E-19 2 3 3
"9" -4.29795269088716E-18 3 3 0
"10" -4.06607359374704E-19 3 3 2|

Constraints:
X => 1 AND X <= 5
Y => 1 AND Y <= 5
C => 1 AND C <= 5

Regression Analysis Report:
64 terms, Std. error:2.185911E-09 %
63 terms, Std. error:1.292262E-10 %
62 terms, Std. error:5.630967E-11 %
61 terms, Std. error:4.602376E-11 %
60 terms, Std. error:3.280098E-11 %
59 terms, Std. error:2.358838E-11 %
58 terms, Std. error:2.211161E-11 %
57 terms, Std. error:2.092984E-11 %
56 terms, Std. error:1.975320E-11 %
55 terms, Std. error:1.845993E-11 %
54 terms, Std. error:8.409166E-12 %
53 terms, Std. error:7.153771E-12 %
52 terms, Std. error:6.048751E-12 %
51 terms, Std. error:4.830633E-12 %
50 terms, Std. error:4.150604E-12 %
49 terms, Std. error:3.965235E-12 %
48 terms, Std. error:3.268687E-12 %
47 terms, Std. error:2.718620E-12 %
46 terms, Std. error:2.233231E-12 %
45 terms, Std. error:1.972990E-12 %
44 terms, Std. error:1.725768E-12 %
43 terms, Std. error:1.558727E-12 %
42 terms, Std. error:1.481934E-12 %
41 terms, Std. error:1.322706E-12 %
40 terms, Std. error:1.254161E-12 %
39 terms, Std. error:1.227896E-12 %
38 terms, Std. error:1.175588E-12 %
37 terms, Std. error:1.142533E-12 %
36 terms, Std. error:9.863930E-13 %
35 terms, Std. error:8.746619E-13 %
34 terms, Std. error:7.555309E-13 %
33 terms, Std. error:5.754245E-13 %
32 terms, Std. error:3.892598E-13 %
31 terms, Std. error:3.569178E-13 %
30 terms, Std. error:2.613110E-13 %
29 terms, Std. error:2.673237E-13 %
28 terms, Std. error:2.621992E-13 %
27 terms, Std. error:2.417525E-13 %
26 terms, Std. error:1.810973E-13 %
25 terms, Std. error:1.586212E-13 %
24 terms, Std. error:1.392517E-13 %
23 terms, Std. error:1.305220E-13 %
22 terms, Std. error:1.157469E-13 %
21 terms, Std. error:1.148749E-13 %
20 terms, Std. error:1.012362E-13 %
19 terms, Std. error:8.431851E-14 %
18 terms, Std. error:6.524708E-14 %
17 terms, Std. error:5.853444E-14 %
16 terms, Std. error:4.713122E-14 %
15 terms, Std. error:4.449740E-14 %
14 terms, Std. error:3.972974E-14 %
13 terms, Std. error:5.402428E-14 %
12 terms, Std. error:3.790702E-14 %
11 terms, Std. error:2.430670E-14 %
10 terms, Std. error:2.843318E-14 %
Standard error absolute = 2.134535E-14
Standard error percentage = 2.843318E-14 %
Original <-> Computed <-> Percentage
3.000000E+00 <-> 3.000000E+00 <-> 100.00
1.000000E+01 <-> 1.000000E+01 <-> 100.00
2.900000E+01 <-> 2.900000E+01 <-> 100.00
6.600000E+01 <-> 6.600000E+01 <-> 100.00
1.270000E+02 <-> 1.270000E+02 <-> 100.00
6.000000E+00 <-> 6.000000E+00 <-> 100.00
1.300000E+01 <-> 1.300000E+01 <-> 100.00
3.200000E+01 <-> 3.200000E+01 <-> 100.00
6.900000E+01 <-> 6.900000E+01 <-> 100.00
1.300000E+02 <-> 1.300000E+02 <-> 100.00
1.100000E+01 <-> 1.100000E+01 <-> 100.00
1.800000E+01 <-> 1.800000E+01 <-> 100.00
3.700000E+01 <-> 3.700000E+01 <-> 100.00
7.400000E+01 <-> 7.400000E+01 <-> 100.00
1.350000E+02 <-> 1.350000E+02 <-> 100.00
1.800000E+01 <-> 1.800000E+01 <-> 100.00
2.500000E+01 <-> 2.500000E+01 <-> 100.00
4.400000E+01 <-> 4.400000E+01 <-> 100.00
8.100000E+01 <-> 8.100000E+01 <-> 100.00
1.420000E+02 <-> 1.420000E+02 <-> 100.00
2.700000E+01 <-> 2.700000E+01 <-> 100.00
3.400000E+01 <-> 3.400000E+01 <-> 100.00
5.300000E+01 <-> 5.300000E+01 <-> 100.00
9.000000E+01 <-> 9.000000E+01 <-> 100.00
1.510000E+02 <-> 1.510000E+02 <-> 100.00
4.000000E+00 <-> 4.000000E+00 <-> 100.00
1.100000E+01 <-> 1.100000E+01 <-> 100.00
3.000000E+01 <-> 3.000000E+01 <-> 100.00
6.700000E+01 <-> 6.700000E+01 <-> 100.00
1.280000E+02 <-> 1.280000E+02 <-> 100.00
7.000000E+00 <-> 7.000000E+00 <-> 100.00
1.400000E+01 <-> 1.400000E+01 <-> 100.00
3.300000E+01 <-> 3.300000E+01 <-> 100.00
7.000000E+01 <-> 7.000000E+01 <-> 100.00
1.310000E+02 <-> 1.310000E+02 <-> 100.00
1.200000E+01 <-> 1.200000E+01 <-> 100.00
1.900000E+01 <-> 1.900000E+01 <-> 100.00
3.800000E+01 <-> 3.800000E+01 <-> 100.00
7.500000E+01 <-> 7.500000E+01 <-> 100.00
1.360000E+02 <-> 1.360000E+02 <-> 100.00
1.900000E+01 <-> 1.900000E+01 <-> 100.00
2.600000E+01 <-> 2.600000E+01 <-> 100.00
4.500000E+01 <-> 4.500000E+01 <-> 100.00
8.200000E+01 <-> 8.200000E+01 <-> 100.00
1.430000E+02 <-> 1.430000E+02 <-> 100.00
2.800000E+01 <-> 2.800000E+01 <-> 100.00
3.500000E+01 <-> 3.500000E+01 <-> 100.00
5.400000E+01 <-> 5.400000E+01 <-> 100.00
9.100000E+01 <-> 9.100000E+01 <-> 100.00
1.520000E+02 <-> 1.520000E+02 <-> 100.00
5.000000E+00 <-> 5.000000E+00 <-> 100.00
1.200000E+01 <-> 1.200000E+01 <-> 100.00
3.100000E+01 <-> 3.100000E+01 <-> 100.00
6.800000E+01 <-> 6.800000E+01 <-> 100.00
1.290000E+02 <-> 1.290000E+02 <-> 100.00
8.000000E+00 <-> 8.000000E+00 <-> 100.00
1.500000E+01 <-> 1.500000E+01 <-> 100.00
3.400000E+01 <-> 3.400000E+01 <-> 100.00
7.100000E+01 <-> 7.100000E+01 <-> 100.00
1.320000E+02 <-> 1.320000E+02 <-> 100.00
1.300000E+01 <-> 1.300000E+01 <-> 100.00
2.000000E+01 <-> 2.000000E+01 <-> 100.00
3.900000E+01 <-> 3.900000E+01 <-> 100.00
7.600000E+01 <-> 7.600000E+01 <-> 100.00
1.370000E+02 <-> 1.370000E+02 <-> 100.00
2.000000E+01 <-> 2.000000E+01 <-> 100.00
2.700000E+01 <-> 2.700000E+01 <-> 100.00
4.600000E+01 <-> 4.600000E+01 <-> 100.00
8.300000E+01 <-> 8.300000E+01 <-> 100.00
1.440000E+02 <-> 1.440000E+02 <-> 100.00
2.900000E+01 <-> 2.900000E+01 <-> 100.00
3.600000E+01 <-> 3.600000E+01 <-> 100.00
5.500000E+01 <-> 5.500000E+01 <-> 100.00
9.200000E+01 <-> 9.200000E+01 <-> 100.00
1.530000E+02 <-> 1.530000E+02 <-> 100.00
6.000000E+00 <-> 6.000000E+00 <-> 100.00
1.300000E+01 <-> 1.300000E+01 <-> 100.00
3.200000E+01 <-> 3.200000E+01 <-> 100.00
6.900000E+01 <-> 6.900000E+01 <-> 100.00
1.300000E+02 <-> 1.300000E+02 <-> 100.00
9.000000E+00 <-> 9.000000E+00 <-> 100.00
1.600000E+01 <-> 1.600000E+01 <-> 100.00
3.500000E+01 <-> 3.500000E+01 <-> 100.00
7.200000E+01 <-> 7.200000E+01 <-> 100.00
1.330000E+02 <-> 1.330000E+02 <-> 100.00
1.400000E+01 <-> 1.400000E+01 <-> 100.00
2.100000E+01 <-> 2.100000E+01 <-> 100.00
4.000000E+01 <-> 4.000000E+01 <-> 100.00
7.700000E+01 <-> 7.700000E+01 <-> 100.00
1.380000E+02 <-> 1.380000E+02 <-> 100.00
2.100000E+01 <-> 2.100000E+01 <-> 100.00
2.800000E+01 <-> 2.800000E+01 <-> 100.00
4.700000E+01 <-> 4.700000E+01 <-> 100.00
8.400000E+01 <-> 8.400000E+01 <-> 100.00
1.450000E+02 <-> 1.450000E+02 <-> 100.00
3.000000E+01 <-> 3.000000E+01 <-> 100.00
3.700000E+01 <-> 3.700000E+01 <-> 100.00
5.600000E+01 <-> 5.600000E+01 <-> 100.00
9.300000E+01 <-> 9.300000E+01 <-> 100.00
1.540000E+02 <-> 1.540000E+02 <-> 100.00
7.000000E+00 <-> 7.000000E+00 <-> 100.00
1.400000E+01 <-> 1.400000E+01 <-> 100.00
3.300000E+01 <-> 3.300000E+01 <-> 100.00
7.000000E+01 <-> 7.000000E+01 <-> 100.00
1.310000E+02 <-> 1.310000E+02 <-> 100.00
1.000000E+01 <-> 1.000000E+01 <-> 100.00
1.700000E+01 <-> 1.700000E+01 <-> 100.00
3.600000E+01 <-> 3.600000E+01 <-> 100.00
7.300000E+01 <-> 7.300000E+01 <-> 100.00
1.340000E+02 <-> 1.340000E+02 <-> 100.00
1.500000E+01 <-> 1.500000E+01 <-> 100.00
2.200000E+01 <-> 2.200000E+01 <-> 100.00
4.100000E+01 <-> 4.100000E+01 <-> 100.00
7.800000E+01 <-> 7.800000E+01 <-> 100.00
1.390000E+02 <-> 1.390000E+02 <-> 100.00
2.200000E+01 <-> 2.200000E+01 <-> 100.00
2.900000E+01 <-> 2.900000E+01 <-> 100.00
4.800000E+01 <-> 4.800000E+01 <-> 100.00
8.500000E+01 <-> 8.500000E+01 <-> 100.00
1.460000E+02 <-> 1.460000E+02 <-> 100.00
3.100000E+01 <-> 3.100000E+01 <-> 100.00
3.800000E+01 <-> 3.800000E+01 <-> 100.00
5.700000E+01 <-> 5.700000E+01 <-> 100.00
9.400000E+01 <-> 9.400000E+01 <-> 100.00
1.550000E+02 <-> 1.550000E+02 <-> 100.00

You can copy and past the function and data in new relation (copy the data in the dataset of this new relation). And put the constraints as minimum and maximum values in the Slots & Properties window.

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