flock to swimming pools , leading to more accidents , and the more ice cream is sold . So you see , although statistics are vital in the world of decision making , you have to be wise , and ask the right questions .
STEP 1 : Getting Started — Worksheet Template Please download this week ' s iLab file : Week7 _ iLab _ Statistics Your first step should be to save and rename this file according to the naming convention above . It is recommended , as you work on this iLab , that you save your work often . STEP 2 : Create a Documentation Page This will be a similar documentation page that you have used for all prior iLabs . Please refer to instructions in iLab 1 for detailed instructions . Be sure to place the documentation sheet as your first sheet . STEP 3 : Descriptive Statistics The Data _ 1971 _ 2000 worksheet is already loaded with data for you , which is the actual temperatures for all of the U . S . states between 1971 and 2001 . As you can see , the data already contains the averagetemperature for each state , in both Fahrenheit and Celsius , along with the ranking of the states , in terms of warmest average temperature (# 1 ) to the lowest . 1 . Freeze the top row , so that the column headers are visible as you scroll through the data . 2 . At the bottom of the page , you are asked to provide the Count , Average , Median , Mode , Min , and Max for each of the states for each of the data columns . The shaded area at the end of the states is where these descriptive statistics should be entered . 3 . To the right of the data , starting at approximately Texas ( row 44 ), use the Data Analysis feature to display the summary descriptive statistics for each temperature and the rank . Be sure to shade and format your descriptive statistics ( similar to the shading in Step # 2 above ) so as to be able to read everything well . As you read your results , you might note some interesting results . First and foremost , note how the statistics associated with the rankings are virtually worthless , as they really don ' t provide any insight to the data itself . This is a little of what I meant above when I