Descriptive Statistics

# Graphical description in which we use graphs to summarize data.
# Tabular description in which we use tables to summarize data.
# Summary statistics in which we calculate certain values to summarize data.

In general, statistical data can be described as a list of ''subjects'' or ''units'' and the data associated with each of them. Although most research uses many data types for each ''unit'', we will limit ourselves to just one data item each for this simple introduction.

We have two objectives for our summary:

#We want to choose a Statistic that shows how different ''units'' seem similar. Statistical textbooks call the solution to this objective, a ''measure of Central Tendency .''
#We want to choose another Statistic that shows how they differ. This kind of statistic is often called a ''measure of Statistical Variability ''.

When we are summarizing a quantity like length or weight or age, it is common to answer the first question with the Arithmetic Mean , the ''' Median ,''' or the ''' Mode .''' Sometimes, we choose specific values from the Cumulative Distribution Function called Quantile s.

The most common measures of variability for Quantitative Data are the Variance ; its square root, the Standard Deviation ; the Range ; Interquartile Range ; and the Absolute Deviation .

STEPS IN DESCRIPTIVE STATISTICS

# Collect data
# Classify data
# Summarize data
# Present data
# Proceed to Inferential Statistics if there is enough Data to draw a Conclusion .

SEE ALSO

Information About

Descriptive Statistics