Topics: Level of measurement, Qualitative data, Measurement Pages: 8 (2251 words) Published: April 15, 2013
Phase 1
Concepts and Terminology of Statistics Applied to Business
Decision Making (DB2)
Terrence Ellison
Professor Daryl Korinek
May 23, 2012

There are two kinds of quantitative variables: discrete and continuous. Discrete variables have values that can be counted and must be integers, while continuous variables can assume any values between two given values. Examples of discrete variables include the value showing on the roll of a die (1–6), or the number of rainy days in a week (1–7). While continuous variable is the opposite, as such, although each event is unique, the probability of any one event cannot be directly measured because it can always be further broken down into smaller parts. Example of continuous variables would be height, although it can be measured in feet, inches would provide a more precise measurement. If measured in inches, a more precise measurement can be made in centimeters, then millimeters, then decimeters (CTU, 2011).

Three potential quantitative objectives that can be used to keep track of caller behavior are listed below:

1) How many are in your household
2) Ages in household
3) How often they buy snacks

The first quantitative objectives would be considered a discrete variable. As defined above, discrete variables are mutually exclusive and cannot be broken down into more precise measurements. In accordance with the requirements, the call center would need to keep track of the number of household members. In this case, the outcome would be a whole number; you can’t have .5 household members (Bowerman, 2011).

The second and third quantitative objective would be considered a continuous variable. These items can be broken down into smaller parts. For example, the caller may have a small child that is 2.5 or 29 months. Although the most common answer would not include a decimal, it could and this symbolizes a continual variable when the answer falls between two whole numbers. The same applies for the number of snacks purchased, unless you give specified guidelines for reporting this data (Bowerman, 2011).

In conclusion, depending on how you want the data reported, it can come back to you in a variety of ways. The goal is to capture the data and translate it into usable information; the call center can provide the meanings. But, it’s important to capture this information when it becomes available.


Colorado Technical University Online. (2012). PM600 – Project Management. Retrieved from Colorado Technical University Online Virtual Campus, PM600-1201B-01.

Bowerman, O'Connell, Orris (2011). Essentials of Business Statistics (4th ed.). McGraw-Hill - Irwin, Columbus, OH

Individual Project

One of the products that Company W makes is snack foods. The Research and Development department of Company W has developed a new formula for one type of snack food that is cheaper to make than the current formula. They want to test the new formula with consumers. They want to see if consumers can tell the difference between the old and new formulas. You propose to conduct this test and analyze the results in line with WidgeCorp's approach to gathering statistical data and using it to make decisions. You first need to explain the process to senior management at Company W. You advocate using an unbiased sample of consumers in their test, so that Company W is randomly selecting people based on the following: age; whether or not they have kids; where they live; how often they buy snack foods; whether or not they already buy the current product..

Prepare a presentation that addresses the following:

List at least 3 qualitative attributes of the snack food about which they might want to ask consumers. Make sure at least one of them is nominal.

Qualitative attributes| Remarks|
How many are in your household | Ordinal data|
How often do you buy snacks...
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