Two sided or one sided interval estimation of mu of one normal sample

Compute the two sided or one sided interval estimation of mu of one normal sample when the population variance is known or unknown.

Usage

interval_estimate4(x, sigma = -1, side = 0, alpha = 0.05)

Arguments

x: A numeric vector.
sigma: The standard deviation of the population. sigma>=0 indicates it is known, sigma<0 indicates it is unknown. Default to unknown standard deviation.
side: A parameter used to control whether to compute two sided or one sided interval estimation. When computing the one sided upper limit, input side = -1; when computing the one sided lower limit, input side = 1; when computing the two sided limits, input side = 0 (default).
alpha: The significance level, a real number in [0, 1]. Default to 0.05. 1-alpha is the degree of confidence.

Value

A data.frame with variables:

mean: The sample mean.
df: The degree of freedom.
a: The confidence lower limit.
b: The confidence upper limit.

References

Zhang, Y. Y., Wei, Y. (2013), One and two samples using only an R funtion, doi:10.2991/asshm-13.2013.29 .

Author

Ying-Ying Zhang (Robert) robertzhangyying@qq.com

Examples

x=rnorm(10, mean = 1, sd = 0.2); x
#>  [1] 0.9528708 1.0088669 0.5760600 0.9343016 1.0924105 1.1387249 0.8582811
#>  [8] 0.9582206 1.0704558 1.3489427
interval_estimate4(x, sigma = 0.2, side = -1)
#>        mean df    a        b
#> 1 0.9939135 10 -Inf 1.097943
interval_estimate4(x, side = 1)
#>        mean df         a   b
#> 1 0.9939135  9 0.8776059 Inf