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A beta error is another term for a type II error, an instance of accepting the null hypothesis when the null hypothesis is false.

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Q: What is a beta error?
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What is the major difference between a mathematical model and an econometric model?

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Relationship between type 1 error and type 2 error?

In statistics, there are two types of errors for hypothesis tests: Type 1 error and Type 2 error. Type 1 error is when the null hypothesis is rejected, but actually true. It is often called alpha. An example of Type 1 error would be a "false positive" for a disease. Type 2 error is when the null hypothesis is not rejected, but actually false. It is often called beta. An example of Type 2 error would be a "false negative" for a disease. Type 1 error and Type 2 error have an inverse relationship. The larger the Type 1 error is, the smaller the Type 2 error is. The smaller the Type 2 error is, the larger the Type 2 error is. Type 1 error and Type 2 error both can be reduced if the sample size is increased.


True or False For a given level of significance if the sample size is increased the probability of comitting a Type II error will increase?

The statement is false. For a fixed alpha, an increase in the sample size will cause a decrease in beta (but an increase in the power).


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How do you calculate beta in mutual funds?

Check out these websites: http://faculty.babson.edu/academic/Beta/CalculateBeta.htm http://www.money-zine.com/Investing/Stocks/Stock-Beta-and-Volatility/