Description of Report Window Elements 

Element	Reference
Mean diamonds are added to the Oneway plot	See Display Options and Mean Diamonds and X-Axis Proportional.
Reports	See The Summary of Fit Report.
	See The Analysis of Variance Report.
	See The Means for Oneway Anova Report.
	See The t-test Report. Note: This report appears only if the Means/Anova/Pooled t option is selected.
	See The Block Means Report. Note: This report appears only if you have specified a Block variable in the launch window.

Description of the Summary of Fit Report 

Rsquare	Measures the proportion of the variation accounted for by fitting means to each factor level. The remaining variation is attributed to random error. The R2 value is 1 if fitting the group means accounts for all the variation with no error. An R2 of 0 indicates that the fit serves no better as a prediction model than the overall response mean. For more information, see Statistical Details for the Summary of Fit Report. R2 is also called the coefficient of determination.
Adj Rsquare	Adjusts R2 to make it more comparable over models with different numbers of parameters by using the degrees of freedom in its computation. For more information, see Statistical Details for the Summary of Fit Report.
Root Mean Square Error	Estimates the standard deviation of the random error. It is the square root of the mean square for Error found in the Analysis of Variance report.
Mean of Response	Overall mean (arithmetic average) of the response variable.
Observations (or Sum Wgts)	Number of observations used in estimating the fit. If weights are used, this is the sum of the weights. See Statistical Details for the Summary of Fit Report.

Description of the t-Test Report 

t Test plot	Shows the sampling distribution of the difference in the means, assuming the null hypothesis is true. The vertical red line is the actual difference in the means. The shaded areas correspond to the p-values.
Difference	Shows the estimated difference between the two X levels. In the plots, the Difference value appears as a red line that compares the two levels.
Std Err Dif	Shows the standard error of the difference.
Upper CL Dif	Shows the upper confidence limit for the difference.
Lower CL Dif	Shows the lower confidence limit for the difference.
Confidence	Shows the level of confidence (1-alpha). To change the level of confidence, select a new alpha level from the Set α Level command from the platform red triangle menu.
t Ratio	Value of the t-statistic.
DF	The degrees of freedom used in the t-test.
Prob > |t|	The p-value associated with a two-tailed test.
Prob > t	The p-value associated with a lower-tailed test.
Prob < t	The p-value associated with an upper-tailed test.

Description of the Analysis of Variance Report 

Source	Lists the three sources of variation, which are the model source, Error, and C. Total (corrected total).
DF	Records an associated degrees of freedom (DF for short) for each source of variation: • The degrees of freedom for C. Total are N - 1, where N is the total number of observations used in the analysis. • If the X factor has k levels, then the model has k - 1 degrees of freedom. The Error degrees of freedom is the difference between the C. Total degrees of freedom and the Model degrees of freedom (in other words, N - k).
Sum of Squares	Records a sum of squares (SS for short) for each source of variation: • The total (C. Total) sum of squares of each response from the overall response mean. The C. Total sum of squares is the base model used for comparison with all other models. • The sum of squared distances from each point to its respective group mean. This is the remaining unexplained Error (residual) SS after fitting the analysis of variance model. The total SS minus the error SS gives the sum of squares attributed to the model. This tells you how much of the total variation is explained by the model.
Mean Square	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.
F Ratio	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.
Prob>F	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.

Description of the Means for Oneway Anova Report 

Level	Lists the levels of the X variable.
Number	Lists the number of observations in each group.
Mean	Lists the mean of each group.
Std Error	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.
Lower 95% and Upper 95%	Lists the lower and upper 95% confidence interval for the group means.