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  70.3    75.4    -77.5     218.
#>  2 102.     93.2    -81.0     284.
#>  3 123.     79.4    -32.1     279.
#>  4  88.1    70.6    -50.3     227.
#>  5  59.1    89.9   -117.      235.
#>  6 104.     91.7    -75.5     284.
#>  7  93.7    70.2    -43.9     231.
#>  8 112.     77.9    -40.8     264.
#>  9  92.6    79.5    -63.3     248.
#> 10  91.2    77.5    -60.6     243.

# 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  70.3    75.4   -124.      265.
#>  2 102.     93.2   -138.      342.
#>  3 123.     79.4    -81.0     328.
#>  4  88.1    70.6    -93.8     270.
#>  5  59.1    89.9   -172.      291.
#>  6 104.     91.7   -132.      340.
#>  7  93.7    70.2    -87.2     275.
#>  8 112.     77.9    -88.7     312.
#>  9  92.6    79.5   -112.      297.
#> 10  91.2    77.5   -108.      291.