Multiple Regression
回归分析（一元或多元）
直接从excel或记事本拷贝各列数居（因变量y放最右边，自变量x放左边）到左边的数据框，
然后删除最后一个回车键，让光标紧跟着第2列的最后一个数据，
否则这种直接拷贝会添加(0,0)这个数据。
然后直接按计算按钮即可
Linear Correlation and Regression
直接从excel或记事本拷贝2列数居到左边的数据框，
然后删除最后一个回车键，让光标紧跟着第2列的最后一个数据，
否则这种直接拷贝会添加(0,0)这个数据。然后直接按计算按钮即可
Contingency table
A contingency table is input to this routine. Rows represent the different states of one nominal variable, columns represent the states of another nominal variable, and cells contain the counts of occurrences of that specific state (row, column) of the two variables. A measure and probability of association of the two variables (based on Chi-square) is then given.
For example, rows may represent taxa and columns samples as usual (with specimen counts in the cells). The contingency table analysis then gives information on whether the two variables of taxon and locality are associated. If not, the data matrix is not very informative. For details, see Press et al. (1992).
Reference
Press, W.H., S.A. Teukolsky, W.T. Vetterling & B.P. Flannery. 1992. Numerical Recipes in C. Cambridge University Press.
Example:
R = 0.7096, p <= 0.03635 (t = 2.665, DF = 7)
y = 0.7919 * x + 132.4
Chi-Square “Goodness of Fit” Test
Analysis of varianceIn statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which the observed variance is partitioned into components due to different explanatory variables. The initial techniques of the analysis of variance were developed by the statistician and geneticist R. A. Fisher in the 1920s and 1930s, and is sometimes known as Fisher’s ANOVA or Fisher’s analysis of variance, due to the use of Fisher’s F-distribution as part of the test of statistical significance.cted.
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