MOTE (version 1.0.2)

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

Description

This function displays d and non-central confidence interval for single t estimated from the t-statistic.

Usage

d.single.t.t(t, n, a = 0.05)

Arguments

t

t-test value

n

sample size

a

significance level

Value

The effect size (Cohen's d) with associated confidence intervals and relevant statistics.

d

effect size

dlow

lower level confidence interval d value

dhigh

upper level confidence interval d value

n

sample size

df

degrees of freedom (sample size - 1)

t

sig stats

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 t-statistic is divided by the square root of the sample size.

d = t / sqrt(n)

Learn more on our example page.

Examples

# NOT RUN {
#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")

#According to a single-sample t-test, the scores of the students
#from the program were significantly higher than the national
#average, t(14) = 9.97, p < .001.

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

    d.single.t.t(t = 9.968, n = 15, a = .05)

    d.single.t.t(9.968, 15, .05)

    d.single.t.t(gift$statistic, length(singt_data$SATscore), .05)
# }