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Perhaps a mistaken impression, after completing an initial course in statistics, is that one distribution is better than another. Many other distributions exists. Usually, introductory statistics classes concern confidence limits, hypothesis testing and sample size determination which all involve a sampling distribution of a particular statistic such as the mean. The normal distribution is often the appropriate distribution in these areas. The normal distribution is appropriate when the random variable in question is the result of many small independent random variables that have been are summed . The attached link shows this very well. Theoretically, a random variable approaches the normal distribution as the sample size tends towards infinity. (Central limit theory) As a practical matter, it is very important that the contributing variables be small and independent.

Q: Why you prefer normal distribution as compare to others in statistics?

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The standard normal distribution is a subset of a normal distribution. It has the properties of mean equal to zero and a standard deviation equal to one. There is only one standard normal distribution and no others so it could be considered the "perfect" one.

There are two main methods: theoretical and empirical. Theoretical: Is the random variable the sum (or mean) of a large number of imdependent, identically distributed variables? If so, by the Central Limit Theorem the variable in question is approximately normally distributed. Empirical: there are various goodness-of-fit tests. Two of the better known are the chi-square and the Kolmogorov-Smirnov tests. There are others. These compare the observed values with what might be expected if the distribution were Normal. The greater the discrepancy, the less likely it is that the distribution is Normal, the smaller the discrepancy the more likely that the distribution is Normal.

There are infinitely many sets of parameters that will generate a bell shaped curves - or near approximations. The Student's t or binomial, for large sample sizes get very close to the Gaussian distribution. There are others, too.

The answer depends on what is being tested: the t-test, F-test, Chi-square, Z-test are all commonly used with the Normal distribution. There are many others.

I would call it a quadrilateral. I cannot compare my answer with the 3 others and so am unable to comment.

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The statement is false. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.

No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.

The standard normal distribution is a subset of a normal distribution. It has the properties of mean equal to zero and a standard deviation equal to one. There is only one standard normal distribution and no others so it could be considered the "perfect" one.

There are two main methods: theoretical and empirical. Theoretical: Is the random variable the sum (or mean) of a large number of imdependent, identically distributed variables? If so, by the Central Limit Theorem the variable in question is approximately normally distributed. Empirical: there are various goodness-of-fit tests. Two of the better known are the chi-square and the Kolmogorov-Smirnov tests. There are others. These compare the observed values with what might be expected if the distribution were Normal. The greater the discrepancy, the less likely it is that the distribution is Normal, the smaller the discrepancy the more likely that the distribution is Normal.

Under the conventional distribution arrangement a channel member negotiates deals with others that do not result in binding relationships. But, under the vertical arrangement a channel member feels tied to one or more members of the distribution channel.

Compared to other hybrid cars, the Volvo C30 is nothing special when it comes to statistics but what the Volvo has that other hybrids don't specialize in is safety.

There are infinitely many sets of parameters that will generate a bell shaped curves - or near approximations. The Student's t or binomial, for large sample sizes get very close to the Gaussian distribution. There are others, too.

That is the normal distribution. If there are others on the deed that may affect things. And a spouse normally has a right to the property for at least a life estate.

The answer depends on what is being tested: the t-test, F-test, Chi-square, Z-test are all commonly used with the Normal distribution. There are many others.

The reference point.

They want to compare themselves to others

Based on 2005 statistics Colorado is: * 92.3 % White * 4.55 % Black * 2.84 % Asian * 3.16 % Others Colorado's population also has the Nations sixth largest Hispanic and Spanish speaking populations dating back to the Spanish colonial period.