Visualize how changes in mean and standard deviation affect the shape of the normal distribution. Compute & visualize quantiles out of given probability and probability from a given quantile.

dist_norm_plot(mean = 0, sd = 1)

dist_norm_perc(probs = 0.95, mean = 0, sd = 1, type = c("lower",
  "upper", "both"))

dist_norm_prob(perc, mean = 0, sd = 1, type = c("lower", "upper", "both"))

Arguments

mean

Mean of the normal distribution.

sd

Standard deviation of the normal distribution.

probs

Probability value.

type

Lower tail, upper tail or both.

perc

Quantile value.

Value

Percentile for the probs based on mean, sd and type or probability value for perc based on mean, sd and type.

Deprecated functions

norm_plot(), norm_prob() and norm_per() have been deprecated. Instead use dist_norm_plot(), dist_norm_prob() and dist_norm_per().

See also

Normal

Examples

# visualize normal distribution dist_norm_plot()
dist_norm_plot(mean = 2, sd = 0.6)
# visualize probability from a given quantile dist_norm_prob(3.78, mean = 2, sd = 1.36)
dist_norm_prob(3.43, mean = 2, sd = 1.36, type = 'upper')
dist_norm_prob(c(-1.74, 1.83), type = 'both')
# visualize quantiles out of given probability dist_norm_perc(0.95, mean = 2, sd = 1.36)
dist_norm_perc(0.3, mean = 2, sd = 1.36, type = 'upper')
dist_norm_perc(0.95, mean = 2, sd = 1.36, type = 'both')