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Q: What does a p value of less than 0.05 mean?
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Is .625 percent of a percent more than .005 percent?

Answer: Yes, .625% of a % is greater than .005 % Solution: .625% of a percent = .625% * 1% = .625 / 100 * (1 / 100) = 0.00625 * .01 = 0.0000625 .005% = .005/100 = .00005 0.0000625 > 0.00005 The easy way to determine which converted number is larger is to align them as follows & look to see which number is greater: 0.0000625 0.00005 As you can see above, 6 is greater than 5, which means the upper number is greater than the lower number. === An easier way to convert .625% of 1% is to count the number of % characters & then know each % represents 2 digits. In this case .625% of 1% means you have 4 decimal places. So you just move the decimal place of .625, 4 decimal places to the left as in .625 converts to .0000625. Since there is only 1 % associated with the .005 number, you just have to move the decimal place 2 digits to the left as in .005 converts to .00005. Then line up your numbers as shown above and you should be able to easily see which number is larger.


How many 3 digit numbers have the sum of their digits equal to 5?

002+002+001=005


Which is better a 005 level of significance or 001 level of significance?

"Better" is subjective. A 0.005 level of significance refers to a statistical test in which there is only a 0.5 percent chance that a result as extreme as that observed (or more extreme) occurs by pure chance. A 0.001 level of significance is even stricter. So with the 0.001 level of significance, there is a much better chance that when you decide to reject the null hypothesis, it did deserve to be rejected. And consequently the probability that you reject the null hypothesis when it was true (Type I error) is smaller. However, all this comes at a cost. As the level of significance increases, the probability of the Type II error also increases. So, with the 0.001 level of significance, there is a greater probability that you fail to reject the null hypothesis because the evidence against it is not strong enough. So "better" then becomes a consideration of the relative costs and benefits of the consequences of the correct decisions and the two types of errors.