Significance plot

Figure 3.4. Simple volcano plot. For each gene, difference in expression is plotted on the x-axis as a log2 value [a value of f is a twofold difference (dotted line)] versus the statistical significance plotted on the y-axis as log(f/p) [a value of 2 represents a p-value of O.Of or a 1-in-iOO probabihty of occurring by chance (dashed line)]. Note that just because there is a large difference in expression, a gene may not be statistically significantly differently expressed (dotted areas) while small-fold differences can be significant (light gray area).

Fig. 8. Significance plot based on Set 2, for /= l, 2,..,/ (7=100000) using the data set in Table 1. The highlighted circle is equal to the actual value from Table 3. (Figure drawn using Po Correlation)...

The significance plot also shows an improved confidence compared to Fig. 8, as graphical displayed in Fig. 9. A more clear separation between the actual correlation (highlighted circle) and the cluster of points is seen. It is also seen in Fig. 9 that the actual correlation is placed in the centre of the cluster in the direction on the y-axis. This indicates absence of information within the sets, which is not reflected in the correlation between the two sets. The latter is also seen in Table 4, where the probability level for a higher e value has moved away from unity (0.980 in Table 3 down to 0.815 in Table 4). 

Fig. 9. Significance plot formed by random testing for the data set (7=100000), where the banned pesticides are neglected (Ids. 1, 2, 6, 7, 8). (Figure drawn using Po Correlation)...

In Fig. 13 a graphical display is made for a series of different variable combinations. The x and y axis is similar the axis in the significance plot (Fig. s 8 and 9). Six different correlation analyses are performed for the pesticides, which have not been banned in year 2000. 

The equilibrium and rate constants of Table I and a value of the Marcus work term for approach of the reagents to the reaction complex, uA of 1.5 kcal/mol (estimated following Albery and Kreevoy s method for water solution) can be used to calculate a number of reaction rates that can also be measured. Figure 1 shows a plot of calculated versus observed rates for cases with both equilibria and identity rates known. Figure 1 includes some experimental identity rates, which of course fit perfectly on the drawn line of slope 1, just to show how the experimental range of nonidentity reactions compares with that for the identity reactions. Not enough rate data on cationic cases are yet available to make a significant plot from the data of Table II. 

Fig. 2. Reconstructed images between 30-80 keV of (a) flight data during the Cygnus X-1 observation, and (b) simulated data of a noiseless source at the Cygnus X-1 position and flux. Images are significance plots with contours at Icr levels (dashed contours are at la and 2a).

Recognition of the type of production is done with the aid of plots of rjt or qjt, as shown in Fig. 5.42 for types I through III. The most significant plot is given with specific rate q-. ... 

Flence it can be seen that from the density of a fluid, the pressure gradient may be caloulated. Furthermore, the densities of water, oil and gas are so significantly different, that they will show quite different gradients on a pressure-depth plot. 

Figure 3 Feature relevance. The weight parameters for every component in the input vector multiplied with the standard deviation for that component are plotted. This is a measure of the significance of this feature (in this case, the logarithm of the power in a small frequency region.)...

When plotted according to the linear form of the BET equation, data for the adsorption of N2 on Graphon at 77 K give an intercept of 0.004 and a slope of 1.7 (both in cubic centimeters STP per gram). Calculate E assuming a molecular area of 16 for N2. Calculate also the heat of adsorption for the first layer (the heat of condensation of N2 is 1.3 kcal/mol). Would your answer for Vm be much different if the intercept were taken to be zero (and the slope the same) Comment briefly on the practical significance of your conclusion. 

Figure Bl.25.5. (a) XPS spectra at take-off angles of 0° and 60° as measured from the surface nonnal from a silicon crystal with a thin layer of Si02 on top. The relative intensity of the oxide signal increases significantly at higher take-off angles, illustrating that the surface sensitivity of XPS increases, (b) Plot of...

Figure B3.3.10. Contour plots of the free energy landscape associated with crystal niicleation for spherical particles with short-range attractions. The axes represent the number of atoms identifiable as belonging to a high-density cluster, and as being in a crystalline environment, respectively, (a) State point significantly below the metastable critical temperature. The niicleation pathway involves simple growth of a crystalline nucleus, (b) State point at the metastable critical temperature. The niicleation pathway is significantly curved, and the initial nucleus is liqiiidlike rather than crystalline. Thanks are due to D Frenkel and P R ten Wolde for this figure. For fiirther details see [189].

A somewhat different method of plotting the results will help the reader to appreciate the significance of the eutectic temperature. In Fig. 1,11, 2 melting points are plotted against composition. The curve AC portrays the decreasing melting point of a-naphthol as naphthalene is added up to a mol fraction of 0 605. The curve BG represents the... 

In addition to being able to plot simple instantaneous values of a quantity x along a trajectory and reporting the average, , HyperChem can also report information about the deviation of x from its average value. These RMS deviations may have particular significance in statistical mechanics or just represent the process of convergence of the trajectory values. 

Some measure of dispersion of the subgroup data should also be plotted as a parallel control chart. The most reliable measure of scatter is the standard deviation. For small groups, the range becomes increasingly significant as a measure of scatter, and it is usually a simple matter to plot the range as a vertical line and the mean as a point on this line for each group of observations. 

The significance of the various columns is explained in the notes below the table, which enable the calculations of 6v l6r to be followed through. Only the first few lines are reproduced, by way of illustration the pore size distribution curve resulting from the complete table is given in Fig. 3.18 (Curve A), as a plot of 6i j6r against f. 

More often, however, microporosity is associated with an appreciable external surface, or with mesoporosity, or with both. The effect of microporosity on the isotherm will be seen from Fig. 4.11(a) and Fig. 4.12(a). In Fig. 4.11(a) curve (i) refers to a powder made up of nonporous particles and curve (ii) to a solid which is wholly microporous. However, if the particles of the powder are microporous (the total micropore volume being given by the plateau of curve (ii)), the isotherm will assume the form of curve (iii), obtained by summing curves (i) and (ii). Like isotherm (i), the composite isotherm is of Type II, but because of the contribution from the Type 1 isotherm, it has a steep initial portion the relative enhancement of adsorption in the low-pressure region will be reflected in a significantly increased value of the BET c-constant and a shortened linear branch of the BET plot. 

Occasionally the DR plot falls into two straight lines (cf. Fig. 4.20), and the question again arises as to the significance of the different values of the uptake at p°jp = 1, derived by extrapolation of the respective branches, ( te often, the DR plot displays an upward turn as saturation pressure is approached (Fig. 4.18 and 4.21), a feature which can readily be understood in terms of multilayer adsorption and capillary condensation in mesopores. 

The results of a comparison between values of n estimated by the DRK and BET methods present a con. used picture. In a number of investigations linear DRK plots have been obtained over restricted ranges of the isotherm, and in some cases reasonable agreement has been reported between the DRK and BET values. Kiselev and his co-workers have pointed out, however, that since the DR and the DRK equations do not reduce to Henry s Law n = const x p) as n - 0, they are not readily susceptible of statistical-thermodynamic treatment. Moreover, it is not easy to see how exactly the same form of equation can apply to two quite diverse processes involving entirely diiferent mechanisms. We are obliged to conclude that the significance of the DRK plot is obscure, and its validity for surface area estimation very doubtful. 

---