Basic Analysis and Graphing - SAS

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142 Performing Oneway Analysis Chapter 5 Means/Anova and Means/Anova/Pooled t Table 5.7 Description of the Analysis of Variance Report (Continued) Mean Square F Ratio Prob>F Is a sum of squares divided by its associated degrees of freedom: • The Model mean square estimates the variance of the error, but only under the hypothesis that the group means are equal. • The Error mean square estimates the variance of the error term independently of the model mean square and is unconditioned by any model hypothesis. Model mean square divided by the error mean square. If the hypothesis that the group means are equal (there is no real difference between them) is true, then both the mean square for error and the mean square for model estimate the error variance. Their ratio has an F distribution. If the analysis of variance model results in a significant reduction of variation from the total, the F ratio is higher than expected. Probability of obtaining (by chance alone) an F value greater than the one calculated if, in reality, there is no difference in the population group means. Observed significance probabilities of 0.05 or less are often considered evidence that there are differences in the group means. The Means for Oneway Anova Report The Means for Oneway Anova report summarizes response information for each level of the nominal or ordinal factor. The Means for Oneway Anova report shows the following information: Table 5.8 Description of the Means for Oneway Anova Report Level Number Mean Std Error Lower 95% and Upper 95% Lists the levels of the X variable. Lists the number of observations in each group. Lists the mean of each group. Lists the estimates of the standard deviations for the group means. This standard error is estimated assuming that the variance of the response is the same in each level. It is the root mean square error found in the Summary of Fit report divided by the square root of the number of values used to compute the group mean. Lists the lower and upper 95% confidence interval for the group means.
Chapter 5 Performing Oneway Analysis 143 Means/Anova and Means/Anova/Pooled t The Block Means Report If you have specified a Block variable on the launch window, the Means/Anova and Means/Anova/Pooled t commands produce a Block Means report. This report shows the means for each block and the number of observations in each block. Mean Diamonds and X-Axis Proportional A mean diamond illustrates a sample mean and confidence interval. Figure 5.9 Examples of Mean Diamonds and X-Axis Proportional Options overlap marks 95% confidence interval group mean x-axis proportional x-axis not proportional Note the following observations: • The top and bottom of each diamond represent the (1-alpha)x100 confidence interval for each group. The confidence interval computation assumes that the variances are equal across observations. Therefore, the height of the diamond is proportional to the reciprocal of the square root of the number of observations in the group. • If the X-Axis proportional option is selected, the horizontal extent of each group along the x-axis (the horizontal size of the diamond) is proportional to the sample size for each level of the X variable. Therefore, the narrower diamonds are usually taller, because fewer data points results in a wider confidence interval. • The mean line across the middle of each diamond represents the group mean. • Overlap marks appear as lines above and below the group mean. For groups with equal sample sizes, overlapping marks indicate that the two group means are not significantly different at the given confidence level. Overlap marks are computed as group mean ± ( 2) ⁄ 2 × CI ⁄ 2 . Overlap marks in one diamond that are closer to the mean of another diamond than that diamond’s overlap marks indicate that those two groups are not different at the given confidence level. • The mean diamonds automatically appear when you select the Means/Anova/Pooled t or Means/ Anova option from the platform menu. However, you can show or hide them at any time by selecting Display Options > Mean Diamonds from the red triangle menu.
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Version 10 Basic Analysis and Graph
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USE, DATA OR PROFITS, WHETHER IN AN
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6 Options for Categorical Variables
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8 Nonparametric Bivariate Density R
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10 Example of the Power Option . .
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12 Statistical Details for the Logi
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14 Use Categorical Variables . . .
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16 Control Animation for Dynamic Bu
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18 Launch the Scatterplot Matrix Pl
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Contents Book Conventions. . . . .
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22 Learn about JMP Chapter 1 Book C
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24 Learn about JMP Chapter 1 Book C
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26 Learn about JMP Chapter 1 Additi
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28 Learn about JMP Chapter 1 Additi
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Contents Overview of the Distributi
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32 Performing Univariate Analysis C
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Contents Overview of the Fit Y by X
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90 Introduction to the Fit Y by X P
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192 Performing Contingency Analysis
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Contents Overview of Logistic Regre
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218 Performing Simple Logistic Regr
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Contents Overview of the Matched Pa
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238 Comparing Paired Data Chapter 8
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Contents Example of Bootstrapping .
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250 Bootstrapping Chapter 9 Example
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252 Bootstrapping Chapter 9 Unstack
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254 Bootstrapping Chapter 9 Analysi
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Contents Overview of Graph Builder
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258 Interactive Data Visualization
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Contents Example of the Chart Platf
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314 Creating Summary Charts Chapter
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Contents Example of an Overlay Plot
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340 Creating Overlay Plots Chapter
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Contents Example of a 3D Scatterplo
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354 Creating Three-Dimensional Scat
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Contents Example of a Contour Plot
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374 Creating Contour Plots Chapter
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Contents Example of a Dynamic Bubbl
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384 Creating Bubble Plots Chapter 1
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Contents Overview of Mapping . . .
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406 Creating Maps Chapter 16 Exampl
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418 Creating Maps Chapter 16 Backgr
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Contents Example of a Parallel Plot
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450 Creating Parallel Plots Chapter
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Contents Example of a Cell Plot. .
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460 Creating Cell Plots Chapter 18
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Contents Example of Tree Maps . . .
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468 Creating Tree Maps Chapter 19 E
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470 Creating Tree Maps Chapter 19 E
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472 Creating Tree Maps Chapter 19 T
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474 Creating Tree Maps Chapter 19 A
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Contents Example of a Scatterplot M
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486 Creating Scatterplot Matrices C
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Contents Example of a Ternary Plot
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496 Creating Ternary Plots Chapter
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504 References Becker, R.A. and Cle
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506 References Dunnett, C.W. (1955)
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508 References Hosmer, D.W. and Lem
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510 References McLachlan, G.J. and
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512 References Robertson, T., Wrigh
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514 References Wadsworth, H. M., St
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516 Index examples 459, 463-464 lau
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518 Index Horizontal option 268, 32
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520 Index Proportion of Densities o
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522 Index examples 467-468, 473-482
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Basic Analysis and Graphing - SAS

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