Data, graphing

Now consider die experimental results shown in Figure 85. From these graphs data can be extracted and presented in tabular form. Table 8.4 presents some data extracted from Figure 85, along with other data (for carbon dioxide) that were not shown in die Figure. 

Graphing Data Make a graph of volume versus mass for each of the blocks. Be sure to label both axes with units and give your graph a title. 

Interpreting Data From the graphed data, what is your predicted boiling point for water How many degrees different is this from the actual boiling point of water ... 

Graphing Data On a sheet of graph paper, make a graph of temperature versus time, using the data from Part A. Then make a graph of concentration versus time, using the data from Part B. Were your hypotheses supported Explain. 

Cleveland, W.S. (1985). The Elements of Graphing Data. Wadsworth, Monterey, CA. 

Table I shows the results of several such studies. The pH s of the specific experimental runs used in Table I were chosen to facilitate comparison with natural (fresh) surface waters. Rates were taken directly from reported results, or were determined from the linear portions of tabulated or graphed data. Rates were normalized using either reported surface areas, or estimates of surface area based on reported particle size data. Results in Table 1 compare favorably with a similar compilation by Lasaga (50). Table I shows that feldspar dissolution rates in slightly acidic solutions vary by less than one order of magnitude, despite different experimental conditions and sample pretreatments.

Using your graphed data, predict the reaction rate for the reaction carried out at 40°C. Heat and equilibrate the water to 40°C and use the last piece of tablet to test your prediction. 

Graphing Data Graph the data from LI and L2. Use the graph from the graphing calculator as a guide. 

Graphing Data Make a copy of the graph from the graphing calculator. If you have TI GRAPH LINK and a computer, do a screen print. 

The concentration of carbon tetrachloride was measured in the expired air of a person who swallowed a large amount of carbon tetrachloride (Stewart et al. 1963). Excretion in expired air was found to decrease exponentially in a biphasic or multiphasic fashion, but no quantitative estimate of the elimination half-life of carbon tetrachloride or of the fraction of the dose excreted by this pathway was provided. Visual inspection of their graphed data suggests very approximate half-lives of less than several hours initially, 40 hours (75-150 hours post exposure), and 85 hours (300-400 hours post exposure). 

Kinetic analysis of tyrosinase and calculation of constants will be described using graphical analysis by the Michaelis-Menten equation, Lineweaver-Burk equation, or the direct linear curve. Procedures for preparing these graphs are described below. Alternatively, students may use available computer software to graph data and calculate kinetic constants. Recommended enzyme kinetic computer software packages include Enzyme... 

Figure 2.21 Relationship between lightness and reflectance. Achromatic papers are arranged on an equally spaced lightness scale by human observers. For each paper, the corresponding reflectance is shown in the graph (data from Land 1974).

Figure 4 Change in IOP of normotensive rabbits treated with 0.1% dexamethasone (Dex), 0.1% loteprednol etabonate (LE), and vehicle (50% w/w 2-hydroxypropyl- 3-cyclo-dextrin water solution). Twelve rabbits were investigated in crossover experiments drugs were administered in one eye (100 pL) every hour during the 8-h periods marked on the graph. (Data from Ref. 43 represent mean SE both for treated (T) and control (C) eyes.)...

It is frequently very helpful to plot data. The data is often easier to analyze when it is presented so as to obtain a linear relationship. One of the most useful forms of graphing data is to use the slope intercept equation for a straight line ... 

Worksheet Range Copy Move File Print Graph Data System Quit. 

Tel. 617-495-4018, fax 617-495-1792, e-mail karplus huchel.bitnet Molecular dynamics package using Chemistry at Harvard Macromolecular Mechanics force field. Extensive scripting language for molecular mechanics, simulations, solvation, electrostatics, crystal packing, vibrational analysis, free energy perturbation (FEP) calculations, quantum mechanics/molecular mechanics calculations, stochastic dynamics, and graphing data. 

The two most common ways of graphing data on solute uptake that fit Equation 3.28a are illustrated in Figure 3-16. Figure 3-16a shows that when the external concentration of species /, c°, is equal to K, 7jn then equals 5//max as we can see directly from Equation 3.28a ... 

Tabulate and graph data for numbers of acorns consumed after the observation periods (Data Sheet 5.1). 

Do male and female urine release different responses Tabulate and graph data. Use Data Sheet 20%. 

A correlation coefficient measures the strength of relationships but does not describe the relationship. These coefficients are expressed as a number between —1 and 1. A positive coefficient indicates a positive relationship while a negative coefficient indicates a negative relationship (Fig. 41.6). The nearer the coefficient is to — 1 or 1, the stronger the relationship between the variables, i.e. the less scatter there would be about a line of best fit (note that this does not imply that one variable is dependent on the other ). A coefficient of 0 implies that there is no relationship between the variables. The importance of graphing data is shown by the case illustrated in Fig. 41.6d. 

Lavallee (50) collected and graphed data from human experiments that Indicated that 302.668 at comparatively low doses (below 4 ug/fcg) approached 3-qulnuclldli l benzllate in activity In decreasing performance In the Number Facility Test, but at higher doses (above 9 ng/kg) was only slightly more active than scopolamine Extrapolation of Lavallee s graphs suggests chat the doses of 302.668 and of scopolamine that would be able to lower performance in the Number Facility Test to zero would be Identical. 

Before two-dimensional NMR experiments were invented, a set of discrete data points (chemical shifts) was usually assigned to a molecular structure with little or no knowledge of the correlations among the data points. There was no direct way to observe these correlations. Now multiple-dimensional NMR experiments have opened up opportunities for the analysis of the correlations between the atoms in a structure. The relationship of subspectra-substructure is no longer the relationship of the discrete data points and the substructure. Instead, it is the relationship of the graph (data points plus their correlations) and the substructure. Thus, multiple-dimensional NMR (nD-NMR) experiments offer a lot of advantages in solving spectral data overlap problems. 

The graphing calculator can run a program that graphs data such as atomic radius versus atomic number. Graphing the data within the different periods will allow you to discover trends. 

---