d.single.t: d for Single t from Means

In MOTE: Effect Size and Confidence Interval Calculator

Description

This function displays d and non-central confidence interval for single t from means.

Usage

d.single.t(m, u, sd, n, a = 0.05)

Arguments

m	sample mean
u	population mean
sd	sample standard deviation
n	sample size
a	significance level

Details

To calculate d, the population is subtracted from the sample mean, which is then divided by the standard deviation.

d = (m - u) / sd

Learn more on our example page.

Value

d	effect size
dlow	lower level confidence interval d value
dhigh	upper level confidence interval d value
m	sample mean
sd	standard deviation of the sample
se	standard error of the sample
Mlow	lower level confidence interval of the sample mean
Mhigh	upper level confidence interval of the sample mean
u	population mean
n	sample size
df	degrees of freedom (n - 1)
t	t-statistic
p	p-value
estimate	the d statistic and confidence interval in APA style for markdown printing
statistic	the t-statistic in APA style for markdown printing

Examples

#The following example is derived from the "singt_data" dataset included
#in the MOTE library.

#A school has a gifted/honors program that they claim is
#significantly better than others in the country. The gifted/honors
#students in this school scored an average of 1370 on the SAT,
#with a standard deviation of 112.7, while the national average
#for gifted programs is a SAT score of 1080.

    gift = t.test(singt_data, mu = 1080, alternative = "two.sided")

#You can type in the numbers directly as shown below,
#or refer to your dataset within the function.

    d.single.t(m = 1370, u = 1080, sd = 112.7, n = 14, a = .05)

    d.single.t(1370, 1080, 112.7, 100, .05)

    d.single.t(gift$estimate, gift$null.value,
            sd(singt_data$SATscore),
        length(singt_data$SATscore), .05)

MOTE documentation built on May 2, 2019, 5:51 a.m.