Analyze Experiment - нук_1
Analysis of Variance for НУК_1
--------------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
--------------------------------------------------------------------------------
A:H202:АсОН_A 12,587 1 12,587 44,92 0,0000
B:Продолжительность_ 8,7723 1 8,7723 31,31 0,0001
AA 3,52814 1 3,52814 12,59 0,0036
blocks 0,355606 1 0,355606 1,27 0,2803
Total error 3,64278 13 0,280214
--------------------------------------------------------------------------------
Total (corr.) 28,8858 17
R-squared = 87,389 percent
R-squared (adjusted for d.f.) = 84,6867 percent
Standard Error of Est. = 0,529352
Mean absolute error = 0,334938
Durbin-Watson statistic = 1,59792 (P=0,1485)
Lag 1 residual autocorrelation = 0,188613
Cannot conduct lack-of-fit test.
No degrees of freedom for pure error.
The StatAdvisor
---------------
The ANOVA table partitions the variability in НУК_1 into separate
pieces for each of the effects. It then tests the statistical
significance of each effect by comparing the mean square against an
estimate of the experimental error. In this case, 3 effects have
P-values less than 0,05, indicating that they are significantly
different from zero at the 95,0% confidence level.
The lack of fit test is designed to determine whether the selected
model is adequate to describe the observed data, or whether a more
complicated model should be used. The test is performed by comparing
the variability of the current model residuals to the variability
between observations at replicate settings of the factors.
Unfortunately, the test can not be run in this case because there are
no replicate observations.
The R-Squared statistic indicates that the model as fitted explains
87,389% of the variability in НУК_1. The adjusted R-squared
statistic, which is more suitable for comparing models with different
numbers of independent variables, is 84,6867%. The standard error of
the estimate shows the standard deviation of the residuals to be
0,529352. The mean absolute error (MAE) of 0,334938 is the average
value of the residuals. The Durbin-Watson (DW) statistic tests the
residuals to determine if there is any significant correlation based
on the order in which they occur in your data file. Since the P-value
is greater than 0.05, there is no indication of serial autocorrelation
in the residuals.
Regression coeffs. for НУК_1
----------------------------------------------------------------------
constant = 5,89
A:H202:АсОН_A = 1,02417
B:Продолжительность_B = 0,855
AA = -0,939167
----------------------------------------------------------------------
The StatAdvisor
---------------
This pane displays the regression equation which has been fitted to
the data. The equation of the fitted model is
НУК_1 = 5,89 + 1,02417*H202:АсОН_A + 0,855*Продолжительность_B -
0,939167*H202:АсОН_A^2
where the values of the variables are specified in their original
units. To have STATGRAPHICS evaluate this function, select
Predictions from the list of Tabular Options. To plot the function,
select Response Plots from the list of Graphical Options.
Estimation Results for НУК_1
----------------------------------------------------------------------
Observed Fitted Lower 95,0% CL Upper 95,0% CL
Row Value Value for Mean for Mean
----------------------------------------------------------------------
1 2,66 2,93111 2,29896 3,56326
2 4,56 4,89444 4,2623 5,52659
3 4,94 4,97944 4,3473 5,61159
4 3,8 3,78611 3,24701 4,32521
5 6,08 5,74944 5,21035 6,28854
6 5,07 5,83444 5,29535 6,37354
7 4,56 4,64111 4,00896 5,27326
8 7,22 6,60444 5,9723 7,23659
9 7,22 6,68944 6,0573 7,32159
10 3,04 3,21222 2,58007 3,84437
11 5,32 5,17556 4,54341 5,8077
12 5,7 5,26056 4,62841 5,8927
13 4,56 4,06722 3,52812 4,60632
14 6,46 6,03056 5,49146 6,56965
15 6,08 6,11556 5,57646 6,65465
16 4,94 4,92222 4,29007 5,55437
17 5,7 6,88556 6,25341 7,5177
18 6,84 6,97056 6,33841 7,6027
----------------------------------------------------------------------
The StatAdvisor
---------------
This table contains information about values of НУК_1 generated
using the fitted model. The table includes:
(1) the observed value of НУК_1 (if any)
(2) the predicted value of НУК_1 using the fitted model
(3) 95,0% confidence limits for the mean response
Each item corresponds to the values of the experimental factors in a
specific row of your data file. To generate forecasts for additional
combinations of the factors, add additional rows to the bottom of your
data file. In each new row, enter values for the experimental factors
but leave the cell for the response empty. When you return to this
pane, forecasts will be added to the table for the new rows, but the
model will be unaffected.
Optimize Response
-----------------
Goal: maximize НУК_1
Optimum value = 7,02421
Factor Low High Optimum
-----------------------------------------------------------------------
H202:АсОН_A -1,0 1,0 0,54517
Продолжительность_B -1,0 1,0 1,0
The StatAdvisor
---------------
This table shows the combination of factor levels which maximizes
НУК_1 over the indicated region. Use the Analysis Options dialog box
to indicate the region over which the optimization is to be performed.
You may set the value of one or more factors to a constant by setting
the low and high limits to that value.
