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DMAR (version 1.0.0)

cv_z: Provides the Critical Value(s) for the Standard Normal Distribution (the z-distribution, With Mean 0 and Variance 1)

Description

Provides the Critical Value(s) for the Standard Normal Distribution (the z-distribution, With Mean 0 and Variance 1)

Usage

cv_z(
  alpha_level,
  alternative = "not_equal",
  alpha_lower,
  alpha_upper,
  verbose = TRUE
)

Value

Returns the critical value(s), based on the input specifications, in a output style.

Arguments

alpha_level

Type I error rate (i.e., the false positive rate).

alternative

The type of alternative hypothesis of interest.

alpha_lower

The error rate on the lower (negative) side of the distribution.

alpha_upper

The error rate on the upper (positive) side of the distribution.

verbose

Provides extra information about areas under the curve.

Author

Ken Kelley [email protected]

See Also

Other critical values: cv_bonferroni_f(), cv_bryant_paulson(), cv_chisq(), cv_dunnett(), cv_f(), cv_scheffe(), cv_smm(), cv_t(), cv_tukey_hsd()

Examples

Run this code
# A basic call for finding critical values with equal area in the two tails.
cv_z(alpha_level = .05)

# A basic call for a single-sided confidence interval (for "a greater than" alternative hypothesis)
cv_z(alpha_level = .05, alternative = "greater")

# A single-sided confidence interval (for "a greater than" alternative hypothesis); simple output.
cv_z(alpha_lower = 0, alpha_upper = .05, verbose = FALSE)

# For a nonsymmetric 95% confidence interval.
cv_z(alpha_lower = .01, alpha_upper = .04)

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