This Excel tutorial explains how to interpret the summary table generated from Excel Descriptive Statistics.

## Excel Descriptive Statistics

One of the options under DATA > Data Analysis is **Descriptive Statistics**, which generates a statistics summary of a variable. It is very useful because it saves you a lot of time from entering a lot of formulas in order to get some basic analysis.

Before using Excel Descriptive Statistics feature, you should first install **Analysis Toolpak Add-Ins.**

Assume that you want to analyze the salary of the employees. (I used RandBetween Function to generate the random numbers)

Navigate to DATA > Data Analysis > Descriptive Statistics

Select Input Range as A1:A19 and check the box** Labels in first row**, so that the summary table header will display the name “Salary”.

Follow other options as below, click on OK.

A new worksheet is created for the below summary table.

Below are the meaning of each item.

Item | Description | Equivalent Formula |

Mean | Average of the values | =AVERAGE(Sheet1!A2:A19) |

Standard Error | Standard deviation of the sample mean | =STDEV.S(Sheet1!A2:A19) / SQRT(COUNT(Sheet1!A2:A19)) |

Median | Rank data from lowest to highest (or highest to lowest), the number in the middle | =MEDIAN(Sheet1!A2:A19) |

Mode | The most frequent occurrence | =MODE(Sheet1!A2:A19) |

Standard Deviation | Sample standard deviation, measure how close the data is to the mean. 0 means very close to the mean | =STDEV.S(Sheet1!A2:A19) |

Sample Variance | Square of standard deviation | =VAR.S(Sheet1!A2:A19) |

Kurtosis | Measure the flatness of the distribution. Positive kurtosis indicates a relatively peaked distribution.Negative kurtos is indicates a relatively flat distribution. |
=KURT(Sheet1!A2:A19) |

Skewness | Skewness is a measure of symmetry. Sk = 0 means frequency distribution is normally distributed. Positive Sk means positively skewed, negative Sk means negatively skewed. | =SKEW(Sheet1!A2:A19) |

Range | Largest value minus smallest value | =MAX(Sheet1!A2:A19)-MIN(Sheet1!A2:A19) |

Minimum | Smallest value | =MIN(Sheet1!A2:A19) |

Maximum | Largest value | =MAX(Sheet1!A2:A19) |

Sum | Sum of all values | =SUM(Sheet1!A2:A19) |

Count | Count of all values | =COUNT(Sheet1!A2:A19) |

At the bottom of the Descriptive Statistics box, there are three additional options.

#### Confidence Level for the Mean

Confidence level is the percentage that the value will fall into the range. Using our example, if we input 95% as confidence level, the generated value is 12422, meaning 95% chance that the values fall from sample mean – 12422 to sample mean + 12422 (from 36889 to 61734).

You can use CONFIDENCE Function to get the same result. Note that 95% is converted to 0.05 (1-0.95) in the first argument.

=CONFIDENCE.T(0.05,STDEV.S(Sheet1!A2:A19),18)

#### Kth Largest / Kth Smallest

The meaning is self explanatory. For example, if we input 2 for **Kth Largest**, which means we want to find the second largest value, and the summary table will show an additional row

Largest(2) | 83425 |

**Kth Smallest** on the other hand, finds the Kth smallest number.