Limitations of arithmetic mean, Applied Statistics

The calculations of arithmetic mean may be simple and foolproof, but the application of the result may not be so foolproof. An arithmetic mean may not merely lack significance; it may well be positively misleading. Mean should never be accepted as significant without supporting credentials 

Posted Date: 9/14/2012 1:43:30 AM | Location : United States







Related Discussions:- Limitations of arithmetic mean, Assignment Help, Ask Question on Limitations of arithmetic mean, Get Answer, Expert's Help, Limitations of arithmetic mean Discussions

Write discussion on Limitations of arithmetic mean
Your posts are moderated
Related Questions
Mode Mode is the value of the observation which occurs with the   greatest  frequency and thus  it is the most fashionable value, Mode has been derived from French  word  La  m

If the data set contains an odd number of items, the middle item of the array is the median. If there is an even number of items, the median is the average of the two items. If the

Theories of Business forecasting

Chi Square Test as a Distributional Goodness of Fit In day-to-day decision making managers often come across situations wherein they are in a state of dilemma about the applica

A medical researcher has 100 bone cancer patients in a study. Every patient's condition is one of six types, type \A" to type \F". The 100 patients split as follows: x There

For a distribution of scores with = 82 and standard deviation = 2.5, find the following: (Don't forget to sketch the normal curve to help you visualize what you are trying to fi

Create the Venn diagram: A   - you work for an insurance company.  80% of your company's staff is sales force and 70% of your company's sales is force is male. in your company

Analytical Approach We will illustrate this through an example. Example 1 A firm sells a product in a market with a few competitors. The average price charged by the

The first step in this case is to ensure that you are adequately clear on the General Linear Model and its relationship to both ANOVA and regression. The distinction is approxim

Multivariate analysis involves a set of techniques to analyse data sets on more than one variable. Many of these techniques are modern and often involve quite sophisticated use of