Hello, I was asked to do a MANOVA with a set of data. The question is this:

"A researcher randomly assigns 33 subjects to one of three groups. Group 1 receives technical dietary information interactively from an online website. Group 2 receives the same information from a nurse practitioner, while Group 3 receives the information from a video made by the same nurse practitioner.

The researcher looked at three different ratings of the presentation: difficulty, usefulness, and importance to determine if there is a difference in the modes of presentation. In particular, the researcher is interested in whether the interactive website is superior because that is the most cost-effective way of delivering the information."

I ran the MANOVA, and my Wilks' Lamda is not statistically significant.

Tests of Between-Subjects Effects Dependent Type III Sum of Partial Eta gment. Observed Source Variable Squares df Mean Square F Sig. Squared Parameter Pang\" Corrected usefulness 27.676a 2 13.838 .630 .540 .040 1.259 .145 Model difficulty 2.539b 2 1.270 .130 .879 .009 .259 .068 importance 354.688c 2 177.344 3.707 .036 .198 7.413 .635 Intercept usefulness 15749.852 1 15749.852 716.669 .000 .960 716.669 1.000 difficulty 2944.186 1 2944.186 300.731 .000 .909 300.731 1.000 importance 3971.669 1 3971.669 83.013 .000 .735 83.013 1.000 group usefulness 27.676 2 13.838 .630 .540 .040 1.259 .145 difficulty 2.539 2 1.270 .130 .879 .009 .259 .068 importance 354.688 2 177.344 3.707 .036 .198 7.413 .635 Error usefulness 659.294 30 21.976 difficulty 293.703 30 9.790 importance 1435.312 30 47.844 Total usefulness 16615.000 33 difficulty 3265.000 33 importance 5783.000 33 Corrected usefulness 686.970 32 Total difficulty 296.242 32 importance 1790.000 32 a. R Squared = .040 (Adjusted R Squared = -.024) b. R Squared = .009 (Adjusted R Squared = -.058) c. R Squared = .198 (Adjusted R Squared = .145} d. Computed using alpha = .05 Multivariate Testsa Hypothesis Partial Eta Noncent. Observed Effect Value F df Error df Sig. Squared Parameter Powerd Intercept Pillai's Trace 971 313.177b 3.000 28.000 000 971 939.531 1.000 Wilks' Lambda 029 313.177b 3.000 28.000 .000 .971 939.531 1.000 Hotelling's 33.555 313.177b 3.000 28.000 000 971 939.531 1.000 Trace Roy's Largest 33.555 313.177b 3.000 28.000 000 971 939.531 1.000 Root group Pillai's Trace 265 1.478 6.000 58.000 .202 .133 8.866 529 Wilks' Lambda .743 1.495b 6.000 56.000 197 .138 8.972 .533 Hotelling's 335 1.509 6.000 54.000 193 .144 9.051 .536 Trace Roy's Largest 299 2.889c 3.000 29.000 052 .230 8.666 628 Root a. Design: Intercept + group b. Exact statistic c. The statistic is an upper bound on F that yields a lower bound on the significance level. d. Computed using alpha = .05