Description:
The Descriptive Statistics procedure in NCSS is used to summarize a column of data both statistically and graphically. The summaries focus on the center, the spread, and the distribution of the data.
The dataset for this procedure need only be a single column of values. Additional columns could be used to break up the data into groups, but grouping is optional.
In this example, we will use a column of heights.
To obtain descriptive statistics of the height column, we open the Descriptive Statistics procedure from the menu.
Height is entered as a Data Variable.
We will not be using Frequencies or Groups in this case, so those can be left blank.
We will leave all the boxes checked on the Reports tab, as well as the Plots tab.
The Run button is pressed to generate the output report.
The first two sections give a variety of basic summaries of the height data.
The Means Section shows various means, the median, and the mode, as well as the corresponding confidence intervals.
The Variation Section focuses on the spread of the data.
The Skewness and Kurtosis Section shows how the tails of the distribution relate to the Normal distribution.
The Trimmed Section gives the mean and standard deviation for the height data after a percentage of the outside values have been removed. These statistics can be useful when there are outliers or other anomalies in the distribution.
The Normality Test section gives a variety of tests for determining whether the distribution of the data is significantly different from Normal. There does not appear to be strong evidence of non-Normality for this data.
The histogram doesn’t seem to show a very Normal-shaped distribution, but the Normal Probability Plot better reflects Normality.
The Percentile Section gives various percentile values and the corresponding confidence intervals.
The Stem-Leaf Plot shows each value individually in the distribution.
We hope you have enjoyed this overview of the Descriptive Statistics procedure. We suggest you download and install the free trial to learn more.
