- Thread starter alibina1997
- Start date
- Tags anova data analysis factorial design regerssion analysis

(velocity, time, depth, humidity of soil, humidity of environment)

Does this mean that you have high and low on each factor and that you in total have 2*2*2*2*2 =32 experimental conditions?

(If you had only velocity and time you would have 2*2 = 4 experimental conditions.)

Does it also means that for each experimental condition you have run the experiment 3 times, så that you have 32*3 = 96 experimental runs?

If you write an example of a few lines it will be much easier to understand.

Did you randomize the experiment?

try using a bayesian sampler to estimate the factorial hyper parameters.

It is a very good idea to do experiments as factorials.

If you choose to run the experiment with each factor on only two levels, high and low, then you can do the following:

If you choose 3 factors then you can run 2^3 = 8 experimental runs and evaluate it as a full factorial design (with linear regression).

If you choose 4 factors then you can run 2^4 = 16 experimental runs and evaluate it as a full factorial.

If you choose 5 factors then you can run 2^5 = 32 experimental runs and evaluate it as a full factorial.

If you choose 5 factors then you can run 2^(5-1) = 16 experimental runs and evaluate it as a fractional factorial.

But if the experimental variance is high then it might be that you need many more experimental runs to get good enough statistical precision.

again thank you, I attached my experiment below. no, I just have 3 samples. the main problem is instead of 243 I have 3 experiment conditions.

( my adviser said to use factorial after running the experiments)

( my adviser said to use factorial after running the experiments)