svplots (version 0.1.0)

test2musm: Tests the hypothesis over two population means based on two samples summary statistics by Sv-plot2.

Description

Decision on hypothesis testing over two means is made by graphing two sample Sv-plot2s along with the threshold line. Intersecting Sv-plots on or above the horizontal line concludes the alternative hypothesis.

Usage

test2musm(n1=20,n2=25,xbar1=3,xbar2=4,s1=1,s2=1.5,
                 paired=FALSE,eqlvar=FALSE,unkwnsigmas=TRUE,
                 sigma1=NULL,sigma2=NULL,sdevdif=NULL,alpha=0.05,
                 xlab="x",title="Two means summary: Hypothesis testing by Sv-plot2",
                 sam1col="grey5",sam2col="grey45",thrcol="black",...)

Arguments

n1

sample1 size, n1=20 by default.

n2

sample2 size, n2=25 by default.

xbar1

sample1 average, xbar1=3 by default.

xbar2

sample2 average, xbar2=4 by default.

s1

sample1 standard deviation, s1=1 by default.

s2

sample2 standard deviation, s2=1.5 by default.

paired

for dependent samples TRUE, FALSE by default.

eqlvar

population variances are equal, FALSE by default.

unkwnsigmas

population standard deviations are unknown, TRUE by default.

sigma1

population1 standard deviation, NULL by default.

sigma2

population2 standard deviation, NULL by default.

sdevdif

standard deviation of the differences, NULL by default.

alpha

significance level, alpha=0.05 by default.

xlab

\(x\)-axis label, \(x\) by default.

title

title of the plot, Two means: Hypothesis testing by Sv-plot2 by default.

sam1col

sample1 Sv-plot2 color, grey5 by default.

sam2col

sample2 Sv-plot2 color, grey45 by default.

thrcol

threshold color, black by default.

...

other graphical parameter.

Value

Decision on testing hypotheses over two population means by Sv-plot2.

References

Wijesuriya, U. A. (2020). Sv-plots for identifying characteristics of the distribution and testing hypotheses. Communications in Statistics-Simulation and Computation, 10.1080/03610918.2020.1851716.

Examples

# NOT RUN {
 ## For summary data
test2musm(n1=20,n2=25,xbar1=3,xbar2=4,s1=1,s2=1.5,
         paired=FALSE,eqlvar=FALSE,unkwnsigmas=TRUE,
         sigma1=NULL,sigma2=NULL,sdevdif=NULL,alpha=0.05,
         xlab="x",title="Two means summary: Hypothesis testing by Sv-plot2",
         sam1col="grey5",sam2col="grey45",thrcol="black")

test2musm(n1=20,n2=25,xbar1=3,xbar2=4,s1=1.5,s2=1.5,
        paired=FALSE,eqlvar=TRUE,unkwnsigmas=TRUE,
        sigma1=NULL,sigma2=NULL,sdevdif=NULL,alpha=0.05,
        xlab="x",title="Two means summary: Hypothesis testing by Sv-plot2",
        sam1col="grey5",sam2col="grey45",thrcol="black")

test2musm(n1=50,n2=35,xbar1=3,xbar2=4,s1=1,s2=1.5,
         paired=FALSE,eqlvar=FALSE,unkwnsigmas=TRUE,
         sigma1=NULL,sigma2=NULL,sdevdif=NULL,alpha=0.05,
         xlab="x",title="Two means summary: Hypothesis testing by Sv-plot2",
         sam1col="grey5",sam2col="grey45",thrcol="black")

test2musm(n1=50,n2=35,xbar1=3,xbar2=4,s1=1,s2=1.5,
         paired=FALSE,eqlvar=FALSE,unkwnsigmas=FALSE,
         sigma1=2,sigma2=3,sdevdif=NULL,alpha=0.05,
         xlab="x",title="Two means summary: Hypothesis testing by Sv-plot2",
         sam1col="grey5",sam2col="grey45",thrcol="black")

test2musm(n1=20,n2=20,xbar1=3,xbar2=4,s1=1,s2=1.5,
         paired=TRUE,eqlvar=FALSE,unkwnsigmas=TRUE,
         sigma1=NULL,sigma2=NULL,sdevdif=2,alpha=0.05,
         xlab="x",title="Two means summary: Hypothesis testing by Sv-plot2",
         sam1col="grey45",sam2col="grey5",thrcol="black")
# }