test.hypothesis: Summary Hypothesis Test
In ivanliu1989/RQuant: A collection of generic functions

Description Usage Arguments Value See Also Examples

This function runs an hypothesis test to compare the distribution indicators (e.g. proportions, means, ratios)of two samples. In addition it calculates the p-value, standard error and confidence interval

1 2	test.hypothesis(pm_ds, n_ds = NULL, r_ds = NULL, lower.tail = TRUE, std_dev = NULL, conf_lvl = 0.95, distr_ind = "proportion")

`pm_ds`	vector of distribution indicators of the populations to be compared
`n_ds`	vector of data sizes of the distribution indicators to be compared
`r_ds`	vector of ratios (in case the distribution indicator is a ratio)
`lower.tail`	whether the hypothesis test is a lower tail test
`std_dev`	standard deviation in case the distribution indicator is a mean
`conf_lvl`	confidence level
`distr_ind`	distribution indicator to be compared, e.g. proportion, mean or ratio

The function does not return any value. But it prints the outcome of the hypotesis test on screen

str, , head

#Proportions: fill the pm_ds and n_ds vectors with the 2 proportions and sample sizes respectively
test.hypothesis(pm_ds = c(0.0057, 0.0063), n_ds = c(6532, 58,774))

#Percentages: as above and set the distribution indicator: distr_ind = "percentage"
test.hypothesis(pm_ds = c(0.57, 0.63), n_ds = c(6532, 58,774), distr_ind = "percentage")

#Ratios: fill the pm_ds, n_ds and r_ds with the proportions, sample sizes and ratios respectively
test.hypothesis(pm_ds = c(0.0068, 0.0124, 0.0066, 0.0090), n_ds = c(6000, 54000, 6000, 54000), r_ds = c(1.82, 1.36), distr_ind = "ratio")

#Means: fill the n_ds with the sample size; fill the pm_ds vector with the means to be compared.
#provide the standard deviation of the sample by setting std_dev
test.hypothesis(pm_ds= c(68, 72), n_ds = c(100), std_dev = 10, distr_ind = "mean")

#Rates: fill the pm_ds with the weighted averages to be compared; set the distribution indicator
test.hypothesis(pm_ds= c(2.1, 1.8), distr_ind = "rate")