Apply a confidence interval to values in a dataframe based on the normal distribution.

Apply a confidence interval to values in a dataframe based on the normal distribution.

Usage

normal_interval(.data, mean, std_dev, conf = 0.95)

Arguments

.data

Data frame; a confidence interval will be applied to each row in the data frame.

mean

Mean of the distribution

std_dev

Standard deviation of the distribution

conf

Confidence interval, must be between [0, 1]. Defaults to 0.95.

See also

Other interval verbs: beta_interval()

Examples

# create example df
mean <- rnorm(10, 100, 20)
std_dev <- rnorm(10, 80, 10)
example <- dplyr::bind_cols(mean, std_dev)
#> New names:
#> • `` -> `...1`
#> • `` -> `...2`
colnames(example) <- c("mean", "std_dev")

# apply the default confidence interval of 0.95
normal_interval(example, mean, std_dev)
#> # A tibble: 10 × 4
#>     mean std_dev ci_lower ci_upper
#>    <dbl>   <dbl>    <dbl>    <dbl>
#>  1 155.     85.5    -12.5     323.
#>  2 101.     57.3    -11.3     213.
#>  3 112.    107.     -97.8     321.
#>  4 102.     76.4    -47.4     252.
#>  5  61.8    82.1    -99.2     223.
#>  6 117.     90.7    -60.6     295.
#>  7  95.1    73.3    -48.6     239.
#>  8  95.9    91.1    -82.8     275.
#>  9 100.     77.5    -51.6     252.
#> 10 101.     68.2    -33.1     234.

# apply a custom confidence interval
normal_interval(example, mean, std_dev, conf = 0.99)
#> # A tibble: 10 × 4
#>     mean std_dev ci_lower ci_upper
#>    <dbl>   <dbl>    <dbl>    <dbl>
#>  1 155.     85.5    -65.1     375.
#>  2 101.     57.3    -46.6     248.
#>  3 112.    107.    -164.      387.
#>  4 102.     76.4    -94.4     299.
#>  5  61.8    82.1   -150.      273.
#>  6 117.     90.7   -116.      351.
#>  7  95.1    73.3    -93.8     284.
#>  8  95.9    91.1   -139.      331.
#>  9 100.     77.5    -99.3     300.
#> 10 101.     68.2    -75.1     276.