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What is the utility of statistics as a managerial tool?
utility of statistics as a managerial tool
Discuss the utility of statistics as a managerial tool Also describe its limitations?
The limitation of any statistical application is the fact that it always depends on some sampling. If this sampling is incomplete, or not representative of your actual base (say customers), your data may not yield accurate conclusions. Additionally, since it depends on sampling, your measurement is only applicable to a base that fits the profile of your sampling. For instance, if you took your sampling from Caucasian males over age 35, and it turns out your customer base has a large number of African, American females under 23, your conclusions based on the statistics could be imperfect.
How do you calculate utilization?
Now days, Many online utilities comparison websites are available. It has provided accurate and full information about your utility calculation. In Australia, you can easily get area wise information about electricity and gas utility calculation by the simple method use calculator.
What mathematical trait makes a character good for separating samples?
A character that is good for separating samples typically exhibits a high degree of variance or discriminative power across different groups or categories. This means the character's values or features should show clear distinctions between the samples being compared, allowing for effective classification. Additionally, robustness against noise and the ability to maintain distinctiveness under various conditions further enhance the character's utility in separation tasks.
What is the total area under the normal distribution curve?
The area under the normal distribution curve represents the probability of an event occurring that is normally distributed. So, the area under the entire normal distribution curve must be 1 (equal to 100%). For example, if the mean (average) male height is 5'10" then there is a 50% chance that a randomly selected male will have a height that is below or exactly 5'10". This is because the area under the normal curve from the left hand side up to the mean consists of half of the entire area of the normal curve. This leads us to the definitions of z-scores and standard deviations to represent how far along the normal curve a particular value is. We can calculate the likelihood of the value by finding the area under the normal curve to that point, usually by using a z-score cdf (cumulative density function) utility of a calculator or statistics software.
