Descriptive statistics quantitatively describes the main features of data. Descriptive Statistics includes a summary of information used to better understand the data set by using a variety of information, including but not limited to means, standard deviations, maximums, and minimums. When using descriptive statistics, you are trying to understand your sample size in comparison to that of a population. This summarization of the data set comes in multiple forms; the one that are typically used are numerical and graphical. 

For example, the technology committee states that the average amount of time that students spend on computers in the lab has increased, and therefore, so has the need for increased lab fees. To support their claim, the committee conducts a study by randomly sampling 12 students' lab visits and recording the amount of time spent in minutes. When the data is recorded it strongly supports the idea that time has been increased on the computer, we can not reject the hypothesis because of this.  In order to better express the need for the fees, the committee looks at the descriptive statistics to fully analyze the data set.  From the collected data on computer usage, here is the output. 

What the committee can conclude from this data set is that the center, (mean) for all users is 63.25 minutes. The previous mean amount of time spent was 55 minutes. We then proceeded to look at the confidence intrevals that SPSS provides, and are confident that the mean is between 44.87 minutes and 81.63 minutes, only furthering our hypothesis to be correct. Another thing we can examine in our data is the percentiles output. The Q3 and Q1 also support our hypothesis by furthering our understanding of the mean being between 73.75 and 52.25 minutes. Therefore, from descriptive statistics the committee can conclude that average amount of time spent on a computer per visit has increased. However, because the difference in means is only 8.25 minutes, it is not conclusive as to whether or not the change is significant enough to increase the lab fees.

One thing the technology committee may notice about their findings is that there may be a variety of hidden variables that are effecting the data set. For instance, if the data were collected during the end of a semester, students may be spending more time on the computer due to temporarily increased workloads. It is important the the committee also recognizes that the sample size is very small, and may want to run another analysis with new data.

Generating descriptive statistics in SPSS

• Go to the "Analyze" menu at the top of the screen and scroll to "Descriptive Statistics", and then click "Explore".
• Then drag the variable(s) to the "dependent" or "factor list" box. 
• In the same window, click on "Statistics", and change information if needed (for instance, in this scenario we clicked on "percentiles").
• Click "Continue". 
• Then click on "Plots", and unselect "Stem-and-leaf" plots.
• In the same window, check the "Histogram" box also make sure to select "Normality plots with tests." 
• Click "Continue."
• Go to the output window to see the output that is produced.