Levels of Measurement

Wikipedia, the on-line, free encyclopedia,says:

The level of measurement of a variable in mathematics and statistics is a classification that is used to describe the nature of information contained within numbers assigned to objects and, therefore, within the variable. The levels were proposed by Stanley Smith Stevens in his 1946 article On the theory of scales of measurement. According to Stevens' theory of scales, different mathematical operations on variables are possible, depending on the level at which a variable is measured. In the paper he states "Scales are possible in the first place only because there is a certain isomorphism between what we can do with the aspects of objects and the properties of the numeral series.

According to the classification scheme, in statistics the kinds of descriptive statistics and significance tests that are appropriate depend on the level of measurement of the variables concerned

Stevens proposed four levels of measurement: nominal (also categorical or discrete); ordinal; interval; [and] ratio.

There's a lot in the Wikipedia article. Read the whole thing and google "Levels of Measurement" for a lot more.

Social Research Methods.net points out that

First, knowing the level of measurement helps you decide how to interpret the data from that variable...Second, knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned. If a measure is nominal, then you know that you would never average the data values or do a t-test on the data.

Check this website out for statistical methods. It looks to be excellent.

This is important for entrepreneurs who wish to analyze data. You can only use certain kinds of measures for data which are on different scales. Statistics offer a powerful set of intellectual tools to help entrepreneurs understand their world and to analyze it.

Are you interested in this? I'd like to know. Post a comment.

Entrepreneurship informs all of my professional activities. For my ideas on entrepreneurial writing, go to www.kearneymusicschool.blogspot.com and for my ideas on entrepreneurial real estate, go to www.yourstopforrealestate.com/blog

Regression Analysis

From the free, on-line encyclopedia, Wikipedia:

In statistics, regression analysis is a collective name for techniques for the modeling and analysis of numerical data consisting of values of a dependent variable (response variable) and of one or more independent variables (explanatory variables). The dependent variable in the regression equation is modeled as a function of the independent variables, corresponding parameters ("constants"), and an error term. The error term is treated as a random variable. It represents unexplained variation in the dependent variable. The parameters are estimated so as to give a "best fit" of the data. Most commonly the best fit is evaluated by using the least squares method, but other criteria have also been used.

Regression analysis offers another powerful set of tools we can use to understand our businesses. It can tell us what factors best influence buyer behavior. That is, if we know buyers' age, income, gender, and so forth, how much do all of these factors affect the propensity of a customer to buy and which factor is most important, which second, and so forth.

Further, we can look at various factors of our business, revenue, expenses, mean receivable days, etc., and find out which has had the greatest impact on profit or sales growth.

However it is very complicated and arcane to the normal person, and the "regressor" must be trained in its usage.

If you are interested in this, read the whole article and follow its links and references. And post a comment. I'd like to know what you think.

Entrepreneurship informs all my professional activities. For my entrepreneurial real estate, go to yourstopforrealestate.com/blog and for entrepreneurial writing and publishing, www.kearneymusicschoolmurders.blogspot.com

Statistical Sampling

From Wikipedia, the free on-line, encyclopedia, we have this:

Sampling is that part of statistical practice concerned with the selection of individual observations intended to yield some knowledge about a population of concern, especially for the purposes of statistical inference. Each observation measures one or more properties (weight, location, etc.) of an observable entity enumerated to distinguish objects or individuals. Survey weights often need to be applied to the data to adjust for the sample design. Results from probability theory and statistical theory are employed to guide practice.

Entrepreneurs have to be knowledgeable about statistical sampling so they can evaluate statistical studies about their market or their industry. Also, if entrepreneurs are thinking of designing a study to find out some information or other about their market, then they're going to have to know about sampling.

There are dozens of ways to sample, so consult a professional. If you're interested in sampling, you should look at the whole Wikipedia article and follow the links and references. Also, post a comment on this blog.

Entrepreneurship informs all my professional activities. For entrepreneurial real estate, go to www.yourstopforrealestate.com and for entrepreneurial writing go to www.kearneymusicschoolmurders.blogspot.com

Skewness

Okay, yes this blog had a lovely time down the shore. Now it's time to talk about skewness.

Wikipedia (5/24/2008), the free, on-line encyclopedia, defines skewness "in probability theory and statistics [as] a measure of the asymmetry of the probability distribution of a real-valued random variable." In English, this means, take a bunch of numbers, rank them from low to high, plot them as dots on a graph, and then connect the dots, you'll likely have a figure that bunches up high in the middle and tails off toward the right and the left. Ask yourself, "Which tail is longest?" Skeweness is a measure of how much longer the one tail is than the other. If the left tail is longer than the right, we say that the distribution is left-skewed, or negatively skewed. Credit card ownership can be said to be left (negatively) skewed because the average number of credit cards owned tends to be a pretty large number. If the right tail is longer than the left, we say that distribution is right (positively) skewed. Mother's age at the birth of her first child tends to be right (positively) skewed because most mothers tend to be in the teens or 20's when they first give birth. If the right and left tails are equal in length, skeweness is said to be equal to 0. The skewness of any normally distribution equals 0.

Skewness another powerful way of thinking about data. As such, the entrepreneur needs to know about it so he or she can think about his business and talk about his market to others. To learn more, read the entire Wikipedia article on it. And if something about this or anything else I've talked about resonates with you, post a comment.

Entrepreneurship informs everything I do. To read about entrepreneurial writing, go to www.kearneymusicschoolmurders.blogspot.com and for entrepreneurial real estate go to www.yourstopforrealestate.com/blog.