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six were randomly picked among the virt invis RtoL data. The second half (12 subjects) of the data in the new combined set are the day 2 data (12 subjects) from Experiment Two. The purpose of MANOVA or ANOVA analysis on this combined data set is to test whether human performance would show improvement from day 0, when the subjects executed tasks without any training (in Experiment One), to day 2, when subjects had a bene t of several training trials (in Experiment Two). The effect of visibility would also be tested here. Note, however, that the day factor in this analysis is not a repeated measure variable any longer but instead a between-subjects variable. This is because there are no pairs of data for day 0 and day 2 coming from the same subjects (which would be required by the de nition of repeated measure variable). The data for day 0 are independent with respect to the data for day 2. Therefore, the new combined data form a two-way array, 2 (day) 2 (visibility). 7.5.3 Results and Interpretation 1. The MANOVA scheme was applied to the left-to-right data in Experiment One. The variables involved are as follows:

Dependent variables: 1. Path length. 2. Completion time. Independent variables: 1. Interface, with 2 levels: virtual and physical. 2. Visibility, with 2 levels: visible and invisible.

2.4 Impact of Reset on Area Table 2.3 Resource Utilization for Synchronous and Asynchronous Resets Architecture Async Reset Sync Reset Slices 17 0 Flip- ops 32 0 LUTs 16 0 DSPs 1 1

It s the Park Slope brownstone you want to buy Do you want to trade to earn the money to buy the brownstone, and then lose that money Would that be money that you can afford to lose GINI: No way Harry ME: Whoa, I m sorry! I didn t ever think of it that way But it s true If I lost 25 percent of my account now, it would be like losing 25 percent of our future home That s right That is exactly why I didn t treat the first account with a lot of respect I didn t think about what it took me to earn the money in the first place, or what future goals I was throwing away by not being responsible HARVEY: I could not agree more.

The results are shown in Table 7.15. Here df is the degrees of freedom (see Section 7.4.5). Note that the p-level for interaction between the two independent variables is signi cantly high. We thus conclude that there is no interaction effect. This means that the effect of one independent variable does not change across the levels of the other independent variable. The p-level for the interface factor is almost zero. We therefore reject the null hypothesis of the MANOVA, and we conclude that the interface factor has a statistically signi cant effect on the

Comparing this to a similar structure using synchronous resets, we are able to obtain the results shown in Table 2.3. When the synchronous reset was used, the synthesis tool was able to use the DSP core available in the FPGA device. By using a different reset than what was available on this device, however, a signi cant amount of logic was created around it to implement the asynchronous reset.

TABLE 7.15. Results of MANOVA for LtoR Task, Experiment One MANOVA Effect 1 2 12 Effects Studied: 1 interface, 2 visibility Wilks Lambda 0.615711 0.924517 0.986327 df 1 2 2 2 df 2 90 90 90 p-Level 0.000000 0.029253 0.538205

overall human performance. The p-level for the visibility factor shows that the overall human performance is only slightly improved in the visible environment compared to the invisible environment. Given a signi cant effect indicated by the MANOVA results, multiple univariate ANOVAs have followed. 2. The MANOVA was applied to the right-to-left data in Experiment One. The variables are as follows:

If you can learn to show respect for a one-hundred-dollar account for these reasons, then you can take care of a million-dollar account The amount of money won t make a difference because you will agree that you will never do anything to damage your dreams ME: Agreed I promise And Gini will oversee it HARVEY: Harry, where do you stand on the emotional scale How have you felt the past week or so, not trading ME: I haven t cared much about it until now I don t feel compelled to trade on emotion anymore.

iBlockIn ^ iRoundKey; iReady; BlockOutStaged; ValidStaged;

Dependent variables: 1. Path length. 2. Completion time. Independent variables: 1. Interface, with 2 levels: virtual and physical. 2. Visibility, with 2 levels: visible and invisible.

The results are shown in Table 7.16. Note that the p-level for the interaction effect between the two independent variables is large enough; we can conclude that there is no interaction effect. This means that the effect of one independent variable is not in uenced by the other independent variable. The p-level for the interface factor is almost zero, hence we reject the null hypothesis of MANOVA. That is, the interface factor has a statistically signi cant effect on the overall subjects performance. The p-level for the visibility factor is large; we thus conclude that the overall subjects performance was affected by the visibility factor. Since a signi cant effect was demonstrated by this MANOVA, multiple univariate ANOVAs have followed. 3. MANOVA was applied to the Experiment Two data. The variables involved are as follows: