MOTE (version 1.0.2)

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

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

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

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.

Examples

# NOT RUN {
#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)
# }