## Description

`stripChart`

is a modification of the R function `stripchart`

. It is a generic function used to produce one dimensional scatter plots (or dot plots) of the given data, along with text indicating sample size and estimates of location (mean or median) and scale (standard deviation or interquartile range), as well as confidence intervals for the population location parameter. One dimensional scatterplots are a good alternative to `boxplots`

when sample sizes are small or moderate. The function invokes particular `methods`

which depend on the `class`

of the first argument.

## Usage

`stripChart(x, ...)`# S3 method for formulastripChart(x, data = NULL, dlab = NULL, subset, na.action = NULL, ...)

# S3 method for defaultstripChart(x, method = ifelse(paired && paired.lines, "overplot", "stack"), seed = 47, jitter = 0.1 * cex, offset = 1/2, vertical = TRUE, group.names, group.names.cex = cex, drop.unused.levels = TRUE, add = FALSE, at = NULL, xlim = NULL, ylim = NULL, ylab = NULL, xlab = NULL, dlab = "", glab = "", log = "", pch = 1, col = par("fg"), cex = par("cex"), points.cex = cex, axes = TRUE, frame.plot = axes, show.ci = TRUE, location.pch = 16, location.cex = cex, conf.level = 0.95, min.n.for.ci = 2, ci.offset = 3/ifelse(n > 2, (n-1)^(1/3), 1), ci.bar.lwd = cex, ci.bar.ends = TRUE, ci.bar.ends.size = 0.5 * cex, ci.bar.gap = FALSE, n.text = "bottom", n.text.line = ifelse(n.text == "bottom", 2, 0), n.text.cex = cex, location.scale.text = "top", location.scale.digits = 1, nsmall = location.scale.digits, location.scale.text.line = ifelse(location.scale.text == "top", 0, 3.5), location.scale.text.cex = cex * 0.8 * ifelse(n > 6, max(0.4, 1 - (n-6) * 0.06), 1), p.value = FALSE, p.value.digits = 3, p.value.line = 2, p.value.cex = cex, group.difference.ci = p.value, group.difference.conf.level = 0.95, group.difference.digits = location.scale.digits, ci.and.test = "parametric", ci.arg.list = NULL, test.arg.list = NULL, alternative = "two.sided", plot.diff = FALSE, diff.col = col[1], diff.method = "stack", diff.pch = pch[1], paired = FALSE, paired.lines = paired, paired.lty = 1:6, paired.lwd = 1, paired.pch = 1:14, paired.col = NULL, diff.name = NULL, diff.name.cex = group.names.cex, sep.line = TRUE, sep.lty = 2, sep.lwd = cex, sep.col = "gray", diff.lim = NULL, diff.at = NULL, diff.axis.label = NULL, plot.diff.mar = c(5, 4, 4, 4) + 0.1, ...)

## Arguments

x

the data from which the plots are to be produced. In the default method the data can be specified as a list or data frame where each component is numeric, a numeric matrix, or a numeric vector. In the formula method, a symbolic specification of the form `y ~ g`

can be given, indicating the observations in the vector `y`

are to be grouped according to the levels of the factor `g`

(the form `y ~ 1`

indicates no grouping). `NA`

s are allowed in the data. NOTE: When the formula method is used and the argument `paired=TRUE`

(see below), the data in the vector `y`

must have the same number of observations for each level of the factor `g`

and for each level sorted in the same way according to the pairing variable.

data

for the formula method, a data.frame (or list) from which the variables in `x`

should be taken.

subset

for the formula method, an optional vector specifying a subset of observations to be used for plotting.

na.action

for the formula method, a function which indicates what should happen when the data contain `NA`

s. The default is to ignore missing values in either the response or the group.

…

additional parameters passed to the default method, or by it to `plot`

, `points`

, `axis`

, and `title`

to control the appearance of the plot.

method

the method to be used to separate coincident points. When `method="stack"`

coincident points are stacked, when `method="jitter"`

coincident points are jittered, and when `method="overplot"`

coincident points are overplotted. When there are 2 groups and `paired=TRUE`

and `paired.lines=TRUE`

the default value is `method="overplot"`

, otherewise the default method is `method="stack"`

(which differs from the default value for the R function `stripchart`

, which uses `method="overplot"`

by default).

seed

when `method="jitter"`

is used, the argument `seed`

is passed to the R function `set.seed`

. Since jittering depends on the R random number generator, using the same value of `seed`

each time the same data are plotted with `stripChart`

ensures that the resulting plot is the same.

jitter

when `method="jitter"`

is used, `jitter`

gives the amount of jittering applied.

offset

when stacking is used, points are stacked this many line-heights (symbol widths) apart.

vertical

when `vertical=TRUE`

(the default), the plots are drawn vertically rather than horizontally.

group.names

group labels which will be printed alongside (or underneath) each plot.

group.names.cex

numeric scalar indicating the amount by which the group labels should be scaled relative to the default (see the help file for `plot.default`

). The default is the current value of the graphics parameter `cex`

.

drop.unused.levels

when `drop.unused.levels=TRUE`

, groups with no observations are dropped.

add

logical, if true *add* the chart to the current plot.

at

numeric vector giving the locations where the charts should be drawn, particularly when `add=TRUE`

; defaults to `1:n`

where `n`

is the number of groups.

xlim, ylim

plot limits: see `plot.window`

.

ylab, xlab

labels: see `title`

.

dlab, glab

alternate way to specify axis labels. The `dlab`

and `glab`

labels may be used instead of `xlab`

and `ylab`

if those are not specified. `dlab`

applies to the continuous data axis (the \(y\)-axis unless `vertical=FALSE`

), and `glab`

to the group axis.

log

on which axes to use a log scale: see `plot.default`

.

pch, col, cex

Graphical parameters: see `par`

.

points.cex

Sets the `cex`

value for the points plotted.

axes, frame.plot

Axis control: see `plot.default`

.

show.ci

logical scalar indicating whether to plot the confidence interval. The default is `show.ci=TRUE`

.

location.pch

integer indicating which plotting character to use to indicate the estimate of location (mean or median) for each group (see the help file for `plot.default`

). The default is `location.pch=16`

, a filled circle.

location.cex

numeric scalar giving the amount by which the plotting characters indicating the estimate of location for each group should be scaled relative to the default (see the help file for `plot.default`

). The default is the current value of the graphics parameter `cex`

.

conf.level

numeric scalar between 0 and 1 indicating the confidence level associated with the confidence interval for the group location (population mean or median). The default value is `conf.level=0.95`

.

min.n.for.ci

integer indicating the minimum sample size required in order to plot a confidence interval for the group location. The default value is `min.n.for.ci=2`

.

ci.offset

numeric scalar or vector of length equal to the number of groups (`n`

) in units of `cex`

indicating the amount of space between the line showing the confidence interval and tick mark associated with a particular group. The default value depends on the number of groups and is given by `3/ifelse(n > 2, (n-1)^(1/3), 1)`

.

ci.bar.lwd

numeric scalar indicating the line width for the confidence interval bars. The default is the current value of the graphics parameter `cex`

.

ci.bar.ends

logical scalar indicating whether to add flat ends to the confidence interval bars. The default value is `ci.bar.ends=TRUE`

.

ci.bar.ends.size

numeric scalar in units of `cxy`

indicating the size of confidence interval bar ends. The default value is half of the current value of `cex`

.

ci.bar.gap

logical scalar indicating with to add a gap between the estimate of group location and the confidence interval bar. The default value is `ci.bar.gap=FALSE`

.

n.text

character string indicating whether and where to indicate the sample size for each group. Possible values are `"bottom"`

(the default), `"top"`

, and `"none"`

.

n.text.line

integer indicating on which plot margin line to show the sample sizes for each group. The default value is `n.text.line=2`

when `n.text="bottom"`

and `0`

otherwise.

n.text.cex

numeric scalar giving the amount by which the text indicating the sample size for each group should be scaled relative to the default (see the help file for `plot.default`

). The default is the current value of the graphics parameter `cex`

.

location.scale.text

character string indicating whether and where to indicate the estimates of location (mean or median) and scale (standard deviation or interquartile range) for each group. Possible values are `"top"`

(the default), `"bottom"`

, and `"none"`

.

location.scale.digits

integer indicating the number of digits to round the estimates of location and scale. The default value is `location.scale.digits=1`

.

nsmall

integer passed to the function `format`

indicating the the minimum number of digits to the right of the decimal point for the estimates of location and scale. The default value is the value of `location.scale.digits`

, which forces all estimates of location and scale have the same number of digits to the right of the decimal point (including, possibly, trailing zeros). To omit trailing zeros, set `nsmall=0`

.

location.scale.text.line

integer indicating on which plot margin line to show the estimates of location and scale for each group. The default value is `location.scale.text.line=0`

when `n.text="top"`

and `3.5`

otherwise.

location.scale.text.cex

numeric scalar giving the amount by which the text indicating the estimates of location and scale for each group should be scaled relative to the default (see the help file for `plot.default`

). The default depends on the number of groups and is given by `cex * 0.8 * ifelse(n > 6, max(0.4, 1 - (n-6) * 0.06), 1)`

, where `cex`

denotes the current value of the graphics parameter `cex`

.

p.value

logical scalar indicating whether to show the p-value associated with testing whether all groups have the same population location. The default value is `p.value=FALSE`

. The p-value is displayed at the top of the graph.

p.value.digits

integer indicating the number of digits to round to when displaying the p-value associated with the test of equal group locations. The default value is `p.value.digits=3`

.

p.value.line

integer indicating on which plot margin line to show the p-value associated with the test of equal group locations. The default value is `p.value.line=2`

.

p.value.cex

numeric scalar giving the amount by which the text indicating the p-value associated with the test of equal group locations should be scaled relative to the default (see the help file for `plot.default`

). The default is the current value of the graphics parameter `cex`

.

group.difference.ci

for the case when there are just 2 groups, a logical scalar indicating whether to display the confidence interval for the difference between group locations. The default is the value of the `p.value`

argument. The confidence interval is displayed at the top of the graph in the format [Lower CI, Upper CI].

group.difference.conf.level

for the case when there are just 2 groups, a numeric scalar between 0 and 1 indicating the confidence level associated with the confidence interval for the difference between group locations. The default is `conf.level=0.95`

.

group.difference.digits

for the case when there are just 2 groups, an integer indicating the number of digits to round to when displaying the confidence interval for the difference between group locations. The default value is `group.difference.digits=location.scale.digits`

.

ci.and.test

character string indicating whether confidence intervals and tests should be based on parametric or nonparametric (`ci.and.test="nonparametric"`

) methods. When `ci.and.test="parametric"`

(the default), confidence intervals for the population mean are based on the one-sample t-test (see `t.test`

), and the test of group differences is based on the two-sample t-test if there are two groups and the F-test (i.e., one-way analysis of variance, see `aov`

) if there are three or more groups. When `ci.and.test="nonparametric"`

, confidence intervals for the population pseudo-median are based on the Wilcoxon signed rank test (see `wilcox.test`

and page 56 of Hollander and Wolfe, 1999), and the test of group differences is based on the Wilcoxon rank sum test if there are two groups (see `wilcox.test`

) and the Kruskal-Wallis test (see `kruskal.test`

) if there are three or more groups.

ci.arg.list

an optional list of arguments to pass to the function used to compute confidence intervals. The default value is `ci.arg.list=NULL`

.

test.arg.list

an optional list of arguments to pass to the function used to test for group differences in location. The default value is `test.arg.list=NULL`

. In particular, in the case when there are two groups, `ci.and.test="parametric"`

, and `ci.arg.list`

is `NULL`

or does not contain a component specifying the value for `var.equal`

, this argument is updated to include the component `var.equal=TRUE`

, which is not the default behavior of `t.test`

. NOTE: If `test.arg.list`

contains a component named `"paired"`

, the value of that component is set to the value of the argument `paired`

(see below).

alternative

character string describing the alternative hypothesis for the test of group differences in the case when there are two groups. Possible values are `"two.sided"`

(the default), `"less"`

, and `"greater"`

.

plot.diff

applicable only to the case when there are two groups: logical scalar indicating whether to plot the confidence interval for the difference between the groups. The default is `plot.diff=FALSE`

.

When `plot.diff=TRUE`

and `paired=FALSE`

, the confidence interval for the difference between the two locations is displayed and the right-hand axis (when `vertical=TRUE`

) or top axis (when `vertical=FALSE`

) is labeled in units of the confidence interval for the difference between the two locations. If `ci.and.test="parametric"`

, the confidence interval for the difference between the two means is displayed. If `ci.and.test="nonparametric"`

, the confidence interval for the median of the difference between a sample from the first group and a sample from the second group is displayed (see the help file for `wilcox.test`

.

When `plot.diff=TRUE`

and `paired=TRUE`

, the paired differences are displayed and the right-hand axis (when `vertical=TRUE`

) or top axis (when `vertical=FALSE`

) is labeled in units of the paired differences. In addition, if `show.ci=TRUE`

, the confidence interval based on the paired differences is displayed. In this case, if `ci.and.test="parametric"`

the confidence interval for the mean of the paired differences is displayed, and if `ci.and.test="nonparametric"`

the confidence interval for the pseudomedian is displayed (see the help file for `wilcox.test`

.

diff.col

applicable only to the case when there are two groups and `plot.diff=TRUE`

: numeric or character scalar indicating what color to use for the confidence interval for the difference in locations between the two groups. When `paired=TRUE`

, this argument also controls the color of the paired differences. The default is `diff.col=col[1]`

.

diff.method

applicable only to the case when there are two groups, `plot.diff=TRUE`

, and `paired=TRUE`

: the method to be used to separate coincident points for the paired differences. The default value is `diff.method="stack"`

. Other options are `diff.method="jitter"`

and `diff.method="overplot"`

. See the explanation for the argument `method`

above.

diff.pch

applicable only to the case when there are two groups, `plot.diff=TRUE`

, and `paired=TRUE`

: numeric or character scalar indicating what plotting symbol to use for the paired differences. The default is `diff.pch=pch[1]`

.

paired

applicable only to the case when there are two groups: logical scalar indicating whether the observations in the first group are paired with those in the second group. The default is `paired=FALSE`

. NOTE 1: When the formula method for the argument `x`

is used (see above) and the argument `paired=TRUE`

, the data in the vector `y`

must have the same number of observations for each level of the factor `g`

and for each level sorted in the same way according to the pairing variable. NOTE 2: If the argument `test.arg.list`

(see above) contains a component named `"paired"`

, the value of that component is set to the value of the argument `paired`

.

paired.lines

applicable only to the case when there are two groups and `paired=TRUE`

: logical scalar indicating whether to join the paired observations with lines. The default value is the value of the argument `paired`

.

paired.lty

applicable only to the case when there are two groups, `paired=TRUE`

, and `paired.lines=TRUE`

: numeric vector indicating the line types to use to join the paired observations with lines. The default value is `paired.lty=1:6`

.

paired.lwd

applicable only to the case when there are two groups, `paired=TRUE`

, and `paired.lines=TRUE`

: numeric vector indicating the widths of the lines used to join the paired observations with lines. The default value is `paired.lwd=1`

.

paired.pch

applicable only to the case when there are two groups, `paired=TRUE`

, and `paired.lines=TRUE`

: numeric vector indicating the plotting characters to use at each end of the lines used to join the paired observations with lines. The default value is `paired.pch=1:14`

.

paired.col

applicable only to the case when there are two groups, `paired=TRUE`

, and `paired.lines=TRUE`

: character or numeric vector indicating the colors for the lines (and plotting characters) used to join the paired observations with lines. The default value is `paired.col=NULL`

, in which case the vector becomes `c("black", "red", "green3", "blue", "magenta", "darkgreen",`

`"purple", "orange", "darkolivegreen", "steelblue", "darkgray")`

.

diff.name

applicable only to the case when there are two groups and `plot.diff=TRUE`

: character scalar indicating the label to use for the confidence interval for the difference between groups. For the case when `paired=TRUE`

, this label also describes the paired differences. The default value is `diff.name=NULL`

, in which case the label is "group 2 - group 1", where group 1 and group 2 denote the names for the each group. For example, if group 1 is labeled "A" and group 2 is labeled "B", then the default value is `diff.name="B-A"`

.

diff.name.cex

applicable only to the case when there are two groups and `plot.diff=TRUE`

: numeric scalar indicating the amount by which the label for group differences should be scaled relative to the default (see the help file for `plot.default`

). The default value is `diff.name.cex=group.names.cex`

.

sep.line

applicable only to the case when there are two groups and `plot.diff=TRUE`

: logical scalar indicating whether to draw a line between the strip charts for the two groups and the confidence interval for the difference between the two groups (and paired differences when `paired=TRUE`

). The default value is `sep.line=TRUE`

.

sep.lty

applicable only to the case when there are two groups, `plot.diff=TRUE`

, and `sep.line=TRUE`

: numeric scalar indicating the line type to use for the line drawn between the strip charts for the two groups and the confidence interval for the difference between the two groups. The default value is `sep.lty=2`

.

sep.lwd

applicable only to the case when there are two groups, `plot.diff=TRUE`

, and `sep.line=TRUE`

: numeric scalar indicating the line width to use for the line drawn between the strip charts for the two groups and the confidence interval for the difference between the two groups. The default value is the current value of the graphics parameter `cex`

.

sep.col

applicable only to the case when there are two groups, `plot.diff=TRUE`

, and `sep.line=TRUE`

: numeric or character scalar indicating the color of the line drawn between the strip charts for the two groups and the confidence interval for the difference between the two groups. The default value is `sep.col="gray"`

.

diff.lim

applicable only to the case when there are two groups and `plot.diff=TRUE`

: numeric vector of length 2 indicating the limits to use for the axis associated with the confidence interval for the difference between the two groups. When `paired=FALSE`

, the default value is the range of the y-axis, but centered at the mean of the confidence interval for the difference in locations. When `paired=TRUE`

, the default value is `range(pretty(c(X, range(CI))))`

where `X`

denotes the vector containing the paired differences.

diff.at

applicable only to the case when there are two groups and `plot.diff=TRUE`

: numeric vector indicating the locations of the tick marks for the axis associated with the confidence interval for the difference between groups (see the explanation for the argument `at`

in the help file for `axis`

). The default value is `diff.at=NULL`

, in which case default values are used for the locations of the tick marks.

diff.axis.label

applicable only to the case when there are two groups and `plot.diff=TRUE`

: character string indicating the label to use for the axis associated with the confidence interval for the difference between groups. When `paired=FALSE`

the default value is `"Difference Between Groups"`

, and when `paired=TRUE`

the default value is `"Paired Difference"`

.

plot.diff.mar

applicable only to the case when there are two groups, `plot.diff=TRUE`

, and `add=FALSE`

: numeric vector of length 4 indicating the number of lines in the plotting margins (see the explanation for the argument `mar`

in the help file for `par`

). The default value is `plot.diff.mar = c(5, 4, 4, 4) + 0.1`

.

## Value

`stripChart`

invisibly returns a list with the following components:

numeric vector of values on the group axis (the \(x\)-axis unless `vertical=FALSE`

) indicating the centers of the groups.

a matrix with the number of rows equal to the number of groups and six columns indicating the sample size of the group (N), the estimate of the group location parameter (Mean or Median), the estimate of the group scale (SD or IQR), the lower confidence limit for the group location parameter (LCL), the upper confidence limit for the group location parameter (UCL), and the confidence level associated with the confidence interval (Conf.Level)

In addition, if the argument p.value=TRUE and/or 1) there are two groups and 2) plot.diff=TRUE, the list also includes these components:

numeric scalar indicating the p-value associated with the test of equal group locations.

numeric vector of two elements indicating the confidence interval for the difference between the group locations. Only present when there are two groups.

## References

Hollander, M., and D.A. Wolfe. (1999). *Nonparametric Statistical Methods*. Second Edition. John Wiley and Sons, New York.

Millard, S.P., and N.K. Neerchal. (2001). *Environmental Statistics with S-PLUS*. CRC Press, Boca Raton, FL.

Zar, J.H. (2010). *Biostatistical Analysis*. Fifth Edition. Prentice-Hall, Upper Saddle River, NJ.

## See Also

`stripchart`

, `t.test`

, `wilcox.test`

, `aov`

, `kruskal.test`

, `t.test`

.

## Examples

`# NOT RUN { #------------------------ # Two Independent Samples #------------------------ # The guidance document USEPA (1994b, pp. 6.22--6.25) # contains measures of 1,2,3,4-Tetrachlorobenzene (TcCB) # concentrations (in parts per billion) from soil samples # at a Reference area and a Cleanup area. These data are strored # in the data frame EPA.94b.tccb.df. # # First create one-dimensional scatterplots to compare the # TcCB concentrations between the areas and use a nonparametric # test to test for a difference between areas. dev.new() stripChart(TcCB ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"), p.value = TRUE, ci.and.test = "nonparametric", ylab = "TcCB (ppb)") #---------- # Now log-transform the TcCB data and use a parametric test # to compare the areas. dev.new() stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"), p.value = TRUE, ylab = "log10 [ TcCB (ppb) ]") #---------- # Repeat the above procedure, but also plot the confidence interval # for the difference between the means. dev.new() stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"), p.value = TRUE, plot.diff = TRUE, diff.col = "black", ylab = "log10 [ TcCB (ppb) ]") #---------- # Repeat the above procedure, but allow the variances to differ. dev.new() stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"), p.value = TRUE, plot.diff = TRUE, diff.col = "black", ylab = "log10 [ TcCB (ppb) ]", test.arg.list = list(var.equal = FALSE)) #---------- # Repeat the above procedure, but jitter the points instead of # stacking them. dev.new() stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"), p.value = TRUE, plot.diff = TRUE, diff.col = "black", ylab = "log10 [ TcCB (ppb) ]", test.arg.list = list(var.equal = FALSE), method = "jitter", ci.offset = 4) #---------- # Clean up #--------- graphics.off() #==================== #-------------------- # Paired Observations #-------------------- # The data frame ACE.13.TCE.df contians paired observations of # trichloroethylene (TCE; mg/L) at 10 groundwater monitoring wells # before and after remediation. # # Create one-dimensional scatterplots to compare TCE concentrations # before and after remediation and use a paired t-test to # test for a difference between periods. ACE.13.TCE.df # TCE.mg.per.L Well Period #1 20.900 1 Before #2 9.170 2 Before #3 5.960 3 Before #... ...... .. ...... #18 0.520 8 After #19 3.060 9 After #20 1.900 10 After dev.new() stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df, col = c("brown", "green"), p.value = TRUE, paired = TRUE, ylab = "TCE (mg/L)") #---------- # Repeat the above procedure, but also plot the confidence interval # for the mean of the paired differences. dev.new() stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df, col = c("brown", "green"), p.value = TRUE, paired = TRUE, ylab = "TCE (mg/L)", plot.diff = TRUE, diff.col = "blue") #========== # Repeat the last two examples, but use a one-sided alternative since # remediation should decrease TCE concentration. dev.new() stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df, col = c("brown", "green"), p.value = TRUE, paired = TRUE, ylab = "TCE (mg/L)", alternative = "less", group.difference.digits = 2) #---------- # Repeat the above procedure, but also plot the confidence interval # for the mean of the paired differences. # # NOTE: Although stripChart can *report* one-sided confidence intervals # for the difference between two groups (see above example), # when *plotting* the confidence interval for the difference, # only two-sided CIs are allowed. # Here, we will set the confidence level of the confidence # interval for the mean of the paired differences to 90%, # so that the upper bound of the CI corresponds to the upper # bound of a 95% one-sided CI. dev.new() stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df, col = c("brown", "green"), p.value = TRUE, paired = TRUE, ylab = "TCE (mg/L)", group.difference.digits = 2, plot.diff = TRUE, diff.col = "blue", group.difference.conf.level = 0.9) #---------- # Clean up #--------- graphics.off() #========== # The data frame Helsel.Hirsch.02.Mayfly.df contains paired counts # of mayfly nymphs above and below industrial outfalls in 12 streams. # # Create one-dimensional scatterplots to compare the # counts between locations and use a nonparametric test # to compare counts above and below the outfalls. Helsel.Hirsch.02.Mayfly.df # Mayfly.Count Stream Location #1 12 1 Above #2 15 2 Above #3 11 3 Above #... ... .. ..... #22 60 10 Below #23 53 11 Below #24 124 12 Below dev.new() stripChart(Mayfly.Count ~ Location, data = Helsel.Hirsch.02.Mayfly.df, col = c("green", "brown"), p.value = TRUE, paired = TRUE, ci.and.test = "nonparametric", ylab = "Number of Mayfly Nymphs") #---------- # Repeat the above procedure, but also plot the confidence interval # for the pseudomedian of the paired differences. dev.new() stripChart(Mayfly.Count ~ Location, data = Helsel.Hirsch.02.Mayfly.df, col = c("green", "brown"), p.value = TRUE, paired = TRUE, ci.and.test = "nonparametric", ylab = "Number of Mayfly Nymphs", plot.diff = TRUE, diff.col = "blue") #---------- # Clean up #--------- graphics.off()# }`

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