# Calculate p-values from t-, z- or F-statistics.

### Description

Calculate p-values from t-, z- or F-statistics.

### Usage

 ```1 2 3``` ```pFromZ(z_value = 1.96, two.sided = FALSE) pFromT(t_value = 1.96, df = 10, two.sided = FALSE) pFromF(f_value = 1.96, df1 = 10, df2 = 10, two.sided = FALSE) ```

### Arguments

 `t_value, z_value, f_value` t-, z- or F-statistics to be converted into a p-Value `df, df1, df2` df: degree of freedom in t-statistics df1, df2: degrees of freedom in F-statistics `two.sided` shall the statistics be calculatede as two-sided (TURE) or one-sided (FALSE)

### Value

corresponding p-Value from the t-, z- or F-statistics

Roland Rapold

### Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, pFromT(t_value=1.96, df=10) pFromT(t_value=1.96, df=100) pFromT(t_value=1.96, df=1000) pFromT(t_value=1.96, df=1000, two.sided = TRUE) pFromZ(z_value=1.96) pFromZ(z_value=1.96, two.sided=TRUE) pFromF(f_value=35.68, df1=2, df2=5) pFromF(f_value=35.68, df1=2, df2=5, two.sided=TRUE) pFromF(f_value= 1.96, df1=10, df2=10) pFromF(f_value= 1.96, df1=10, df2=100) pFromF(f_value= 1.96, df1=10, df2=1000) pFromF(f_value= 1.96, df1=10, df2=1000, two.sided=TRUE) pFromF(f_value= 1.96, df1=10, df2=1000, two.sided=TRUE) x <- c(seq(0.0001, 0.6, 0.01), NA, seq(0.6001, 1.0, 0.01)) p_value <- pFromT(t_value=x, df=100) p_value formatPValue(p_value, digits=3) ```

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