Target: To check if the assumed μ_{0} is statistically correct, based on a sample average

Example1: A farmer calculated last year the average of the apples' weight in his apple orchard μ_{0} equals 17 kg, based on big sample

Current year he checked a small sample of apples and the sample average x equals 18 kg

Was the average of the apple's weight changed this year?

Normal distribution | |

The standard deviations of the population is known | |

Population expected mean is known |

Sample average of the population | |

Sample size of the population |

H

When enter raw data, the tool will run the Shapiro-Wilk normality test (when n≤5000) and calculate outliers, as part of the test calculation.

The test will validate the priori power

or
or enter summarized data (x, n, σ, S) in **following** form

**Header**:
You may change groups' name to the real names.

**Data**:
When entering data, press Enter after each value

You may copy data from Excel, Google sheets or any tool that separate data with **Tab** and **Line Feed**.

Copy the data, **one column includes the header**, and paste below.

x: | sample average | ||

μ_{0}: |
expected population mean | ||

n: | sample size | ||

σ: | standard deviation | ||

S: | |||

skewness: | |||

normality p-val: | shapiro wilk test | ||

outliers | count: ,based on the Tukey's fences method, k=1.5 | ||

The difference between the expected SD and the sample SD

validation message