1. Now that you've learned a bit more about measurement scales and different levels of data, see if you understand the different data types. For each of the following variables, identify (1) whether the variable is quantitative or qualitative; (2) whether the data is discrete or continuous; (3) the data's level of measurement (nominal, ordinal, interval, or ratio):

1. Taxable income
2. Hair color
3. Price of gasoline
4. Number of television sets in a private home
5. Television set as a possible household item
6. Possible responses to questionnaire items are: yes, no, don't know
7. This is a class 5 hurricane!
8. Earthquake intensity (Richter scale)
9. Final position in a race - 1st, 3rd, etc.
10. The year of aperson's birth (not the age, but year born)

(2. ) The two main categories of descriptive statistics are (1) measures of central tendency and (2) measures of dispersion. What are some of the descriptive statistics in each of these categories? Why it is important to describe data from both categories? Provide examples of how you might use descriptive statistics in your workplace.

(3.) Provide a brief summary of one of the Lynda.com videos. Describe how the information presented in the video could be used in your workplace and present an example using Excel.

(4. ) 1. Review theHow to Install the Data Analysis ToolPak in Microsoft Excelvideo and then install the Analysis ToolPak.

2. Enter the data: 1, 2, 3, 4, 5, 6 into Excel.

3. Use the Analysis ToolPak to calculate the descriptive statistics for this data.

4. Post and explain your results.

(5) The four common levels of data measurement are nominal, ordinal, interval, and ratio. Why is it important to know what level of measurement data is? Provide some examples of each of the four levels from your workplace.