Testing Method of the Second Hypothesis

3.3.6. Testing Method of the Second Hypothesis

Barreteau et al. 2001 described the use of simulation models as learning and research tools. As a research tool, a simulation model is often used to test a hypothesis Barreteau et al. 2001; Grant et al. 1997. Some indicators were observed through the developed model during the simulation period. These indicators were determined by considering the sustainability aspect, stakeholders’ interests and what was measurable through simulation. Testing the second hypothesis involved comparing outcomes of the current forest management system and examining a scenario of collaborative forest management. Firstly, a scenario of collaborative management was developed using the model. Secondly, to compare the simulation outputs of a current and a developed scenario of forest management, the hypothesis was formulated formally as follows: H : m ci = m H 1 : m ci ≠ m The “ci” represents collaborative management indicators and the “ ”, non- collaborative indicators. A non-parametric statistical test was used to test the hypothesis. While there is only one baseline simulation for deterministic models, the baseline for stochastic models actually consists of a set of replicate simulations. The formula for calculating the number of samples needed to detect a given true difference between sample means assuming that we have an estimate of variability within samples is Sokal and Rolf 1969 in Grant et al. 1977: n ≥ 2 σ δ 2 [t α , γ + t 21-P, γ ] 2 where n = Number of samples α = True standard deviation, which we estimate as the square root of the estimated variance within samples δ = Smallest true difference that we desire to detect γ = Degrees of freedom of the sample standard deviation with b group of samples and n samples per group or γ = bn-1 α = Significance level P = Desired probability that a difference will be found to be significant if it is as small as δ t α , γ + t 21-P, γ = Two-tailed values of students-t.

IV. RESULTS AND DISCUSSIONS