Obviously, we should pursue options 2 and 3. In other words, examine all the characteristics of the data.
Perform statistical (or other scientific) analyses. Plot the data in a way that allows the general properties of the data to be visualized. For some data sets, this might mean throwing away most of the data! This is very definitely not recommended although it is quite frequently done. Discard all the data that do not fit some preconceived notion or model. If your data set is either huge or complicated looking, what is the best approach for analyzing it? Here are some We will cover some basic statistics in Excel: histograms and frequency. In today's lecture we are continuing our introduction to Microsoft's Excel. So, you should probably select all of the columns and then in the sort dialogue, choose the column(s) on which you want to sort. One really important point is that you should be aware that sorting with only You can sort on multiple columns (size, then shape, etc. The simplest way to look at a dataset is just to sort it. Here is a video (no audio) showing the basic import of those data and making a bar chart: It gives a visual impression of the data, but can we do more? Of course! Open this web page in a browser:īelow I show a plot of the masses of the individual pebbles in our sample: (a default Excel bar plot). 
Here we will play with a small data set of pebbles. We select a subset (10 or 100 or 1000, etc.) and that is a sample (dataset) of the population which we hope is representative. But we cannot examine all of the pebbles on the beach, so It might not be representative of all the pebbles on the beach ( population).
If you pick up a pebble on the beach, it is a specimen. Let's take an example of the masses of pebbles on a beach.
Lecture 5: Basic statistics in a spreadsheet: histograms, frequency, skewness Example: Pebbles on a Beach
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