Central Limit Theorem simulation
Description
Central Limit Theorem simulation
Usage
clt(
dist,
n = 100,
m = 100,
norm_mean = 0,
norm_sd = 1,
binom_size = 10,
binom_prob = 0.2,
unif_min = 0,
unif_max = 1,
expo_rate = 1
)
Arguments
dist
Distribution to simulate
n
Sample size
m
Number of samples
norm_mean
Mean for the normal distribution
norm_sd
Standard deviation for the normal distribution
binom_size
Size for the binomial distribution
binom_prob
Probability for the binomial distribution
unif_min
Minimum for the uniform distribution
unif_max
Maximum for the uniform distribution
expo_rate
Rate for the exponential distribution
Details
See https://radiant-rstats.github.io/docs/basics/clt.html for an example in Radiant
Value
A list with the name of the Distribution and a matrix of simulated data
Examples
clt("Uniform", 10, 10, unif_min = 10, unif_max = 20)
Compare sample means
Description
Compare sample means
Usage
compare_means(
dataset,
var1,
var2,
samples = "independent",
alternative = "two.sided",
conf_lev = 0.95,
comb = "",
adjust = "none",
test = "t",
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset
var1
A numeric variable or factor selected for comparison
var2
One or more numeric variables for comparison. If var1 is a factor only one variable can be selected and the mean of this variable is compared across (factor) levels of var1
samples
Are samples independent ("independent") or not ("paired")
alternative
The alternative hypothesis ("two.sided", "greater" or "less")
conf_lev
Span of the confidence interval
comb
Combinations to evaluate
adjust
Adjustment for multiple comparisons ("none" or "bonf" for Bonferroni)
test
t-test ("t") or Wilcox ("wilcox")
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/compare_means.html for an example in Radiant
Value
A list of all variables defined in the function as an object of class compare_means
See Also
summary.compare_means to summarize results
plot.compare_means to plot results
Examples
compare_means(diamonds, "cut", "price") %>% str()
Compare sample proportions across groups
Description
Compare sample proportions across groups
Usage
compare_props(
dataset,
var1,
var2,
levs = "",
alternative = "two.sided",
conf_lev = 0.95,
comb = "",
adjust = "none",
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset
var1
A grouping variable to split the data for comparisons
var2
The variable to calculate proportions for
levs
The factor level selected for the proportion comparison
alternative
The alternative hypothesis ("two.sided", "greater" or "less")
conf_lev
Span of the confidence interval
comb
Combinations to evaluate
adjust
Adjustment for multiple comparisons ("none" or "bonf" for Bonferroni)
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/compare_props.html for an example in Radiant
Value
A list of all variables defined in the function as an object of class compare_props
See Also
summary.compare_props to summarize results
plot.compare_props to plot results
Examples
compare_props(titanic, "pclass", "survived") %>% str()
Car brand consideration
Description
Car brand consideration
Usage
data(consider)
Format
A data frame with 1000 rows and 2 variables
Details
Survey data of consumer purchase intentions. Description provided in attr(consider,"description")
Store a correlation matrix as a (long) data.frame
Description
Store a correlation matrix as a (long) data.frame
Usage
cor2df(object, labels = c("label1", "label2"), ...)
Arguments
object
Return value from correlation
labels
Column names for the correlation pairs
...
further arguments passed to or from other methods
Details
Return the correlation matrix as a (long) data.frame. See https://radiant-rstats.github.io/docs/basics/correlation.html for an example in Radiant
Calculate correlations for two or more variables
Description
Calculate correlations for two or more variables
Usage
correlation(
dataset,
vars = "",
method = "pearson",
hcor = FALSE,
hcor_se = FALSE,
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset
vars
Variables to include in the analysis. Default is all but character and factor variables with more than two unique values are removed
method
Type of correlations to calculate. Options are "pearson", "spearman", and "kendall". "pearson" is the default
hcor
Use polycor::hetcor to calculate the correlation matrix
hcor_se
Calculate standard errors when using polycor::hetcor
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/correlation.html for an example in Radiant
Value
A list with all variables defined in the function as an object of class compare_means
See Also
summary.correlation to summarize results
plot.correlation to plot results
Examples
correlation(diamonds, c("price", "carat")) %>% str()
correlation(diamonds, "x:z") %>% str()
Evaluate associations between categorical variables
Description
Evaluate associations between categorical variables
Usage
cross_tabs(
dataset,
var1,
var2,
tab = NULL,
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset (i.e., a data.frame or table)
var1
A categorical variable
var2
A categorical variable
tab
Table with frequencies as alternative to dataset
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/cross_tabs.html for an example in Radiant
Value
A list of all variables used in cross_tabs as an object of class cross_tabs
See Also
summary.cross_tabs to summarize results
plot.cross_tabs to plot results
Examples
cross_tabs(newspaper, "Income", "Newspaper") %>% str()
table(select(newspaper, Income, Newspaper)) %>% cross_tabs(tab = .)
Demand in the UK
Description
Demand in the UK
Usage
data(demand_uk)
Format
A data frame with 1000 rows and 2 variables
Details
Survey data of consumer purchase intentions. Description provided in attr(demand_uk,"description")
Evaluate if sample data for a categorical variable is consistent with a hypothesized distribution
Description
Evaluate if sample data for a categorical variable is consistent with a hypothesized distribution
Usage
goodness(
dataset,
var,
p = NULL,
tab = NULL,
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset
var
A categorical variable
p
Hypothesized distribution as a number, fraction, or numeric vector. If unspecified, defaults to an even distribution
tab
Table with frequencies as alternative to dataset
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/goodness.html for an example in Radiant
Value
A list of all variables used in goodness as an object of class goodness
See Also
summary.goodness to summarize results
plot.goodness to plot results
Examples
goodness(newspaper, "Income") %>% str()
goodness(newspaper, "Income", p = c(3 / 4, 1 / 4)) %>% str()
table(select(newspaper, Income)) %>% goodness(tab = .)
Newspaper readership
Description
Newspaper readership
Usage
data(newspaper)
Format
A data frame with 580 rows and 2 variables
Details
Newspaper readership data for 580 consumers. Description provided in attr(newspaper,"description")
Plot method for the Central Limit Theorem simulation
Description
Plot method for the Central Limit Theorem simulation
Usage
## S3 method for class 'clt'
plot(x, stat = "sum", bins = 15, ...)
Arguments
x
Return value from clt
stat
Statistic to use (sum or mean)
bins
Number of bins to use
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/clt.html for an example in Radiant
Examples
clt("Uniform", 100, 100, unif_min = 10, unif_max = 20) %>% plot()
Plot method for the compare_means function
Description
Plot method for the compare_means function
Usage
## S3 method for class 'compare_means'
plot(x, plots = "scatter", shiny = FALSE, custom = FALSE, ...)
Arguments
x
Return value from compare_means
plots
One or more plots ("bar", "density", "box", or "scatter")
shiny
Did the function call originate inside a shiny app
custom
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org/ for options.
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/compare_means.html for an example in Radiant
See Also
compare_means to calculate results
summary.compare_means to summarize results
Examples
result <- compare_means(diamonds, "cut", "price")
plot(result, plots = c("bar", "density"))
Plot method for the compare_props function
Description
Plot method for the compare_props function
Usage
## S3 method for class 'compare_props'
plot(x, plots = "bar", shiny = FALSE, custom = FALSE, ...)
Arguments
x
Return value from compare_props
plots
One or more plots of proportions ("bar" or "dodge")
shiny
Did the function call originate inside a shiny app
custom
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org/ for options.
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/compare_props.html for an example in Radiant
See Also
compare_props to calculate results
summary.compare_props to summarize results
Examples
result <- compare_props(titanic, "pclass", "survived")
plot(result, plots = c("bar", "dodge"))
Plot method for the correlation function
Description
Plot method for the correlation function
Usage
## S3 method for class 'correlation'
plot(x, nrobs = -1, jit = c(0, 0), dec = 2, ...)
Arguments
x
Return value from correlation
nrobs
Number of data points to show in scatter plots (-1 for all)
jit
A numeric vector that determines the amount of jittering to apply to the x and y variables in a scatter plot. Default is 0. Use, e.g., 0.3 to add some jittering
dec
Number of decimals to show
...
further arguments passed to or from other methods.
Details
See https://radiant-rstats.github.io/docs/basics/correlation.html for an example in Radiant
See Also
correlation to calculate results
summary.correlation to summarize results
Examples
result <- correlation(diamonds, c("price", "carat", "table"))
plot(result)
Plot method for the cross_tabs function
Description
Plot method for the cross_tabs function
Usage
## S3 method for class 'cross_tabs'
plot(x, check = "", shiny = FALSE, custom = FALSE, ...)
Arguments
x
Return value from cross_tabs
check
Show plots for variables var1 and var2. "observed" for the observed frequencies table, "expected" for the expected frequencies table (i.e., frequencies that would be expected if the null hypothesis holds), "chi_sq" for the contribution to the overall chi-squared statistic for each cell (i.e., (o - e)^2 / e), "dev_std" for the standardized differences between the observed and expected frequencies (i.e., (o - e) / sqrt(e)), and "row_perc", "col_perc", and "perc" for row, column, and table percentages respectively
shiny
Did the function call originate inside a shiny app
custom
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org/ for options.
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/cross_tabs.html for an example in Radiant
See Also
cross_tabs to calculate results
summary.cross_tabs to summarize results
Examples
result <- cross_tabs(newspaper, "Income", "Newspaper")
plot(result, check = c("observed", "expected", "chi_sq"))
Plot method for the goodness function
Description
Plot method for the goodness function
Usage
## S3 method for class 'goodness'
plot(x, check = "", fillcol = "blue", shiny = FALSE, custom = FALSE, ...)
Arguments
x
Return value from goodness
check
Show plots for variable var. "observed" for the observed frequencies table, "expected" for the expected frequencies table (i.e., frequencies that would be expected if the null hypothesis holds), "chi_sq" for the contribution to the overall chi-squared statistic for each cell (i.e., (o - e)^2 / e), and "dev_std" for the standardized differences between the observed and expected frequencies (i.e., (o - e) / sqrt(e))
fillcol
Color used for bar plots
shiny
Did the function call originate inside a shiny app
custom
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org/ for options.
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/goodness for an example in Radiant
See Also
goodness to calculate results
summary.goodness to summarize results
Examples
result <- goodness(newspaper, "Income")
plot(result, check = c("observed", "expected", "chi_sq"))
goodness(newspaper, "Income") %>% plot(c("observed", "expected"))
Plot method for the probability calculator (binomial)
Description
Plot method for the probability calculator (binomial)
Usage
## S3 method for class 'prob_binom'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_binom
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_binom to calculate results
summary.prob_binom to summarize results
Examples
result <- prob_binom(n = 10, p = 0.3, ub = 3)
plot(result, type = "values")
Plot method for the probability calculator (Chi-squared distribution)
Description
Plot method for the probability calculator (Chi-squared distribution)
Usage
## S3 method for class 'prob_chisq'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_chisq
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_chisq to calculate results
summary.prob_chisq to summarize results
Examples
result <- prob_chisq(df = 1, ub = 3.841)
plot(result, type = "values")
Plot method for the probability calculator (discrete)
Description
Plot method for the probability calculator (discrete)
Usage
## S3 method for class 'prob_disc'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_disc
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_disc to calculate results
summary.prob_disc to summarize results
Examples
result <- prob_disc(v = 1:6, p = c(2 / 6, 2 / 6, 1 / 12, 1 / 12, 1 / 12, 1 / 12), pub = 0.95)
plot(result, type = "probs")
Plot method for the probability calculator (Exponential distribution)
Description
Plot method for the probability calculator (Exponential distribution)
Usage
## S3 method for class 'prob_expo'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_expo
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_expo to calculate results
summary.prob_expo to summarize results
Examples
result <- prob_expo(rate = 1, ub = 2.996)
plot(result, type = "values")
Plot method for the probability calculator (F-distribution)
Description
Plot method for the probability calculator (F-distribution)
Usage
## S3 method for class 'prob_fdist'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_fdist
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_fdist to calculate results
summary.prob_fdist to summarize results
Examples
result <- prob_fdist(df1 = 10, df2 = 10, ub = 2.978)
plot(result, type = "values")
Plot method for the probability calculator (log normal)
Description
Plot method for the probability calculator (log normal)
Usage
## S3 method for class 'prob_lnorm'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_norm
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_lnorm to calculate results
plot.prob_lnorm to plot results
Examples
result <- prob_lnorm(meanlog = 0, sdlog = 1, lb = 0, ub = 1)
plot(result, type = "values")
Plot method for the probability calculator (normal)
Description
Plot method for the probability calculator (normal)
Usage
## S3 method for class 'prob_norm'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_norm
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_norm to calculate results
summary.prob_norm to summarize results
Examples
result <- prob_norm(mean = 0, stdev = 1, ub = 0)
plot(result)
Plot method for the probability calculator (poisson)
Description
Plot method for the probability calculator (poisson)
Usage
## S3 method for class 'prob_pois'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_pois
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_pois to calculate results
summary.prob_pois to summarize results
Examples
result <- prob_pois(lambda = 1, ub = 3)
plot(result, type = "values")
Plot method for the probability calculator (t-distribution)
Description
Plot method for the probability calculator (t-distribution)
Usage
## S3 method for class 'prob_tdist'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_tdist
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_tdist to calculate results
summary.prob_tdist to summarize results
Examples
result <- prob_tdist(df = 10, ub = 2.228)
plot(result, type = "values")
Plot method for the probability calculator (uniform)
Description
Plot method for the probability calculator (uniform)
Usage
## S3 method for class 'prob_unif'
plot(x, type = "values", ...)
Arguments
x
Return value from prob_unif
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_unif to calculate results
summary.prob_unif to summarize results
Examples
result <- prob_unif(min = 0, max = 1, ub = 0.3)
plot(result, type = "values")
Plot method for the single_mean function
Description
Plot method for the single_mean function
Usage
## S3 method for class 'single_mean'
plot(x, plots = "hist", shiny = FALSE, custom = FALSE, ...)
Arguments
x
Return value from single_mean
plots
Plots to generate. "hist" shows a histogram of the data along with vertical lines that indicate the sample mean and the confidence interval. "simulate" shows the location of the sample mean and the comparison value (comp_value). Simulation is used to demonstrate the sampling variability in the data under the null-hypothesis
shiny
Did the function call originate inside a shiny app
custom
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org/ for options.
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/single_mean.html for an example in Radiant
See Also
single_mean to generate the result
summary.single_mean to summarize results
Examples
result <- single_mean(diamonds, "price", comp_value = 3500)
plot(result, plots = c("hist", "simulate"))
Plot method for the single_prop function
Description
Plot method for the single_prop function
Usage
## S3 method for class 'single_prop'
plot(x, plots = "bar", shiny = FALSE, custom = FALSE, ...)
Arguments
x
Return value from single_prop
plots
Plots to generate. "bar" shows a bar chart of the data. The "simulate" chart shows the location of the sample proportion and the comparison value (comp_value). Simulation is used to demonstrate the sampling variability in the data under the null-hypothesis
shiny
Did the function call originate inside a shiny app
custom
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This option can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and https://ggplot2.tidyverse.org/ for options.
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/single_prop.html for an example in Radiant
See Also
single_prop to generate the result
summary.single_prop to summarize the results
Examples
result <- single_prop(titanic, "survived", lev = "Yes", comp_value = 0.5, alternative = "less")
plot(result, plots = c("bar", "simulate"))
Print method for the correlation function
Description
Print method for the correlation function
Usage
## S3 method for class 'rcorr'
print(x, ...)
Arguments
x
Return value from correlation
...
further arguments passed to or from other methods
Probability calculator for the binomial distribution
Description
Probability calculator for the binomial distribution
Usage
prob_binom(n, p, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
n
Number of trials
p
Probability
lb
Lower bound on the number of successes
ub
Upper bound on the number of successes
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_binom to summarize results
plot.prob_binom to plot results
Examples
prob_binom(n = 10, p = 0.3, ub = 3)
Probability calculator for the chi-squared distribution
Description
Probability calculator for the chi-squared distribution
Usage
prob_chisq(df, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
df
Degrees of freedom
lb
Lower bound (default is 0)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_chisq to summarize results
plot.prob_chisq to plot results
Examples
prob_chisq(df = 1, ub = 3.841)
Probability calculator for a discrete distribution
Description
Probability calculator for a discrete distribution
Usage
prob_disc(v, p, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
v
Values
p
Probabilities
lb
Lower bound on the number of successes
ub
Upper bound on the number of successes
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_disc to summarize results
plot.prob_disc to plot results
Examples
prob_disc(v = 1:6, p = 1 / 6, pub = 0.95)
prob_disc(v = 1:6, p = c(2 / 6, 2 / 6, 1 / 12, 1 / 12, 1 / 12, 1 / 12), pub = 0.95)
Probability calculator for the exponential distribution
Description
Probability calculator for the exponential distribution
Usage
prob_expo(rate, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
rate
Rate
lb
Lower bound (default is 0)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_expo to summarize results
plot.prob_expo to plot results
Examples
prob_expo(rate = 1, ub = 2.996)
Probability calculator for the F-distribution
Description
Probability calculator for the F-distribution
Usage
prob_fdist(df1, df2, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
df1
Degrees of freedom
df2
Degrees of freedom
lb
Lower bound (default is 0)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_fdist to summarize results
plot.prob_fdist to plot results
Examples
prob_fdist(df1 = 10, df2 = 10, ub = 2.978)
Probability calculator for the log normal distribution
Description
Probability calculator for the log normal distribution
Usage
prob_lnorm(meanlog, sdlog, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
meanlog
Mean of the distribution on the log scale
sdlog
Standard deviation of the distribution on the log scale
lb
Lower bound (default is -Inf)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_lnorm to summarize results
plot.prob_lnorm to plot results
Examples
prob_lnorm(meanlog = 0, sdlog = 1, lb = 0, ub = 1)
Probability calculator for the normal distribution
Description
Probability calculator for the normal distribution
Usage
prob_norm(mean, stdev, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
mean
Mean
stdev
Standard deviation
lb
Lower bound (default is -Inf)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_norm to summarize results
plot.prob_norm to plot results
Examples
prob_norm(mean = 0, stdev = 1, ub = 0)
Probability calculator for the poisson distribution
Description
Probability calculator for the poisson distribution
Usage
prob_pois(lambda, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
lambda
Rate
lb
Lower bound (default is 0)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_pois to summarize results
plot.prob_pois to plot results
Examples
prob_pois(lambda = 1, ub = 3)
Probability calculator for the t-distribution
Description
Probability calculator for the t-distribution
Usage
prob_tdist(df, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
df
Degrees of freedom
lb
Lower bound (default is -Inf)
ub
Upper bound (default is Inf)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_tdist to summarize results
plot.prob_tdist to plot results
Examples
prob_tdist(df = 10, ub = 2.228)
Probability calculator for the uniform distribution
Description
Probability calculator for the uniform distribution
Usage
prob_unif(min, max, lb = NA, ub = NA, plb = NA, pub = NA, dec = 3)
Arguments
min
Minimum value
max
Maximum value
lb
Lower bound (default = 0)
ub
Upper bound (default = 1)
plb
Lower probability bound
pub
Upper probability bound
dec
Number of decimals to show
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
summary.prob_unif to summarize results
plot.prob_unif to plot results
Examples
prob_unif(min = 0, max = 1, ub = 0.3)
radiant.basics
Description
Launch radiant.basics in the default web browser
Usage
radiant.basics(state, ...)
Arguments
state
Path to state file to load
...
additional arguments to pass to shiny::runApp (e.g, port = 8080)
Details
See https://radiant-rstats.github.io/docs/ for documentation and tutorials
Examples
## Not run:
radiant.basics()
## End(Not run)
Launch radiant.basics in the Rstudio viewer
Description
Launch radiant.basics in the Rstudio viewer
Usage
radiant.basics_viewer(state, ...)
Arguments
state
Path to state file to load
...
additional arguments to pass to shiny::runApp (e.g, port = 8080)
Details
See https://radiant-rstats.github.io/docs/ for documentation and tutorials
Examples
## Not run:
radiant.basics_viewer()
## End(Not run)
Launch radiant.basics in an Rstudio window
Description
Launch radiant.basics in an Rstudio window
Usage
radiant.basics_window(state, ...)
Arguments
state
Path to state file to load
...
additional arguments to pass to shiny::runApp (e.g, port = 8080)
Details
See https://radiant-rstats.github.io/docs/ for documentation and tutorials
Examples
## Not run:
radiant.basics_window()
## End(Not run)
Salaries for Professors
Description
Salaries for Professors
Usage
data(salary)
Format
A data frame with 397 rows and 6 variables
Details
2008-2009 nine-month salary for professors in a college in the US. Description provided in attr(salary,description")
Compare a sample mean to a population mean
Description
Compare a sample mean to a population mean
Usage
single_mean(
dataset,
var,
comp_value = 0,
alternative = "two.sided",
conf_lev = 0.95,
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset
var
The variable selected for the mean comparison
comp_value
Population value to compare to the sample mean
alternative
The alternative hypothesis ("two.sided", "greater", or "less")
conf_lev
Span for the confidence interval
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/single_mean.html for an example in Radiant
Value
A list of variables defined in single_mean as an object of class single_mean
See Also
summary.single_mean to summarize results
plot.single_mean to plot results
Examples
single_mean(diamonds, "price") %>% str()
Compare a sample proportion to a population proportion
Description
Compare a sample proportion to a population proportion
Usage
single_prop(
dataset,
var,
lev = "",
comp_value = 0.5,
alternative = "two.sided",
conf_lev = 0.95,
test = "binom",
data_filter = "",
envir = parent.frame()
)
Arguments
dataset
Dataset
var
The variable selected for the proportion comparison
lev
The factor level selected for the proportion comparison
comp_value
Population value to compare to the sample proportion
alternative
The alternative hypothesis ("two.sided", "greater", or "less")
conf_lev
Span of the confidence interval
test
bionomial exact test ("binom") or Z-test ("z")
data_filter
Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")
envir
Environment to extract data from
Details
See https://radiant-rstats.github.io/docs/basics/single_prop.html for an example in Radiant
Value
A list of variables used in single_prop as an object of class single_prop
See Also
summary.single_prop to summarize the results
plot.single_prop to plot the results
Examples
single_prop(titanic, "survived") %>% str()
single_prop(titanic, "survived", lev = "Yes", comp_value = 0.5, alternative = "less") %>% str()
Summary method for the compare_means function
Description
Summary method for the compare_means function
Usage
## S3 method for class 'compare_means'
summary(object, show = FALSE, dec = 3, ...)
Arguments
object
Return value from compare_means
show
Show additional output (i.e., t.value, df, and confidence interval)
dec
Number of decimals to show
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/compare_means.html for an example in Radiant
See Also
compare_means to calculate results
plot.compare_means to plot results
Examples
result <- compare_means(diamonds, "cut", "price")
summary(result)
Summary method for the compare_props function
Description
Summary method for the compare_props function
Usage
## S3 method for class 'compare_props'
summary(object, show = FALSE, dec = 3, ...)
Arguments
object
Return value from compare_props
show
Show additional output (i.e., chisq.value, df, and confidence interval)
dec
Number of decimals to show
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/compare_props.html for an example in Radiant
See Also
compare_props to calculate results
plot.compare_props to plot results
Examples
result <- compare_props(titanic, "pclass", "survived")
summary(result)
Summary method for the correlation function
Description
Summary method for the correlation function
Usage
## S3 method for class 'correlation'
summary(object, cutoff = 0, covar = FALSE, dec = 2, ...)
Arguments
object
Return value from correlation
cutoff
Show only correlations larger than the cutoff in absolute value. Default is a cutoff of 0
covar
Show the covariance matrix (default is FALSE)
dec
Number of decimals to show
...
further arguments passed to or from other methods.
Details
See https://radiant-rstats.github.io/docs/basics/correlation.html for an example in Radiant
See Also
correlation to calculate results
plot.correlation to plot results
Examples
result <- correlation(diamonds, c("price", "carat", "table"))
summary(result, cutoff = .3)
Summary method for the cross_tabs function
Description
Summary method for the cross_tabs function
Usage
## S3 method for class 'cross_tabs'
summary(object, check = "", dec = 2, ...)
Arguments
object
Return value from cross_tabs
check
Show table(s) for variables var1 and var2. "observed" for the observed frequencies table, "expected" for the expected frequencies table (i.e., frequencies that would be expected if the null hypothesis holds), "chi_sq" for the contribution to the overall chi-squared statistic for each cell (i.e., (o - e)^2 / e), "dev_std" for the standardized differences between the observed and expected frequencies (i.e., (o - e) / sqrt(e)), and "dev_perc" for the percentage difference between the observed and expected frequencies (i.e., (o - e) / e)
dec
Number of decimals to show
...
further arguments passed to or from other methods.
Details
See https://radiant-rstats.github.io/docs/basics/cross_tabs.html for an example in Radiant
See Also
cross_tabs to calculate results
plot.cross_tabs to plot results
Examples
result <- cross_tabs(newspaper, "Income", "Newspaper")
summary(result, check = c("observed", "expected", "chi_sq"))
Summary method for the goodness function
Description
Summary method for the goodness function
Usage
## S3 method for class 'goodness'
summary(object, check = "", dec = 2, ...)
Arguments
object
Return value from goodness
check
Show table(s) for the selected variable (var). "observed" for the observed frequencies table, "expected" for the expected frequencies table (i.e., frequencies that would be expected if the null hypothesis holds), "chi_sq" for the contribution to the overall chi-squared statistic for each cell (i.e., (o - e)^2 / e), "dev_std" for the standardized differences between the observed and expected frequencies (i.e., (o - e) / sqrt(e)), and "dev_perc" for the percentage difference between the observed and expected frequencies (i.e., (o - e) / e)
dec
Number of decimals to show
...
further arguments passed to or from other methods.
Details
See https://radiant-rstats.github.io/docs/basics/goodness for an example in Radiant
See Also
goodness to calculate results
plot.goodness to plot results
Examples
result <- goodness(newspaper, "Income", c(.3, .7))
summary(result, check = c("observed", "expected", "chi_sq"))
goodness(newspaper, "Income", c(1 / 3, 2 / 3)) %>% summary("observed")
Summary method for the probability calculator (binomial)
Description
Summary method for the probability calculator (binomial)
Usage
## S3 method for class 'prob_binom'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_binom
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_binom to calculate results
plot.prob_binom to plot results
Examples
result <- prob_binom(n = 10, p = 0.3, ub = 3)
summary(result, type = "values")
Summary method for the probability calculator (Chi-squared distribution)
Description
Summary method for the probability calculator (Chi-squared distribution)
Usage
## S3 method for class 'prob_chisq'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_chisq
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_chisq to calculate results
plot.prob_chisq to plot results
Examples
result <- prob_chisq(df = 1, ub = 3.841)
summary(result, type = "values")
Summary method for the probability calculator (discrete)
Description
Summary method for the probability calculator (discrete)
Usage
## S3 method for class 'prob_disc'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_disc
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_disc to calculate results
plot.prob_disc to plot results
Examples
result <- prob_disc(v = 1:6, p = c(2 / 6, 2 / 6, 1 / 12, 1 / 12, 1 / 12, 1 / 12), pub = 0.95)
summary(result, type = "probs")
Summary method for the probability calculator (exponential)
Description
Summary method for the probability calculator (exponential)
Usage
## S3 method for class 'prob_expo'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_expo
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_expo to calculate results
plot.prob_expo to plot results
Examples
result <- prob_expo(rate = 1, ub = 2.996)
summary(result, type = "values")
Summary method for the probability calculator (F-distribution)
Description
Summary method for the probability calculator (F-distribution)
Usage
## S3 method for class 'prob_fdist'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_fdist
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_fdist to calculate results
plot.prob_fdist to plot results
Examples
result <- prob_fdist(df1 = 10, df2 = 10, ub = 2.978)
summary(result, type = "values")
Summary method for the probability calculator (log normal)
Description
Summary method for the probability calculator (log normal)
Usage
## S3 method for class 'prob_lnorm'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_norm
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_lnorm to calculate results
plot.prob_lnorm to summarize results
Examples
result <- prob_lnorm(meanlog = 0, sdlog = 1, lb = 0, ub = 1)
summary(result, type = "values")
Summary method for the probability calculator (normal)
Description
Summary method for the probability calculator (normal)
Usage
## S3 method for class 'prob_norm'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_norm
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_norm to calculate results
plot.prob_norm to plot results
Examples
result <- prob_norm(mean = 0, stdev = 1, ub = 0)
summary(result)
Summary method for the probability calculator (poisson)
Description
Summary method for the probability calculator (poisson)
Usage
## S3 method for class 'prob_pois'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_pois
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_pois to calculate results
plot.prob_pois to plot results
Examples
result <- prob_pois(lambda = 1, ub = 3)
summary(result, type = "values")
Summary method for the probability calculator (t-distribution)
Description
Summary method for the probability calculator (t-distribution)
Usage
## S3 method for class 'prob_tdist'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_tdist
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_tdist to calculate results
plot.prob_tdist to plot results
Examples
result <- prob_tdist(df = 10, ub = 2.228)
summary(result, type = "values")
Summary method for the probability calculator (uniform)
Description
Summary method for the probability calculator (uniform)
Usage
## S3 method for class 'prob_unif'
summary(object, type = "values", ...)
Arguments
object
Return value from prob_unif
type
Probabilities ("probs") or values ("values")
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/prob_calc.html for an example in Radiant
See Also
prob_unif to calculate results
plot.prob_unif to plot results
Examples
result <- prob_unif(min = 0, max = 1, ub = 0.3)
summary(result, type = "values")
Summary method for the single_mean function
Description
Summary method for the single_mean function
Usage
## S3 method for class 'single_mean'
summary(object, dec = 3, ...)
Arguments
object
Return value from single_mean
dec
Number of decimals to show
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/single_mean.html for an example in Radiant
See Also
single_mean to generate the results
plot.single_mean to plot results
Examples
result <- single_mean(diamonds, "price")
summary(result)
diamonds %>%
single_mean("price") %>%
summary()
Summary method for the single_prop function
Description
Summary method for the single_prop function
Usage
## S3 method for class 'single_prop'
summary(object, dec = 3, ...)
Arguments
object
Return value from single_prop
dec
Number of decimals to show
...
further arguments passed to or from other methods
Details
See https://radiant-rstats.github.io/docs/basics/single_prop.html for an example in Radiant
See Also
single_prop to generate the results
plot.single_prop to plot the results
Examples
result <- single_prop(titanic, "survived", lev = "Yes", comp_value = 0.5, alternative = "less")
summary(result)