A^8 * b^12
The exponent 4 is distributed to the other exponents within the parenthesis by multiplication.
a^2*4 * b^3*4
a^8 * b^12
answer 16.99%
We are given this function:
8700 is the initial amount.
1.04 shows the change of original amount. This is decimal form of percentage. We need to transform it into regular percentage.
1.04 * 100% = 104%
Now we observe this number. If it is greater than 100% we have growth, if it is lower than 100% it is decay, and if it is equal to 100% than there is no change.
In our case this number is greater than 100% so we have growth. To determine the percentage rate we must substract 100% as it represents the original amount.
104% - 100% = 4%
This would be our solution if we don't have an exponent.
We have exponent so first step is to calculate the number and then we repeat the steps from above.
1,16985856 * 100% ≈ 116,99%
116.99% - 100% = 16.99%
So, final solution is growth of 16.99%
bran-list please
Answer: D) the significance level of the test
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Explanation:
The significance level of the test, also known as "alpha", is the probability of making a type 1 error. A type 1 error is where you reject the null hypothesis but it was true all along.
The null hypothesis is where we test a certain probability distribution (eg: normal distribution). Specifically we gather a sample of values and compute the test statistic. If the probability of getting that test statistic or more extreme is smaller than alpha, then we reject the null. This probability value is known as the p-value.
If you lower the alpha value, then that will make it more likely you do not reject the null. Consider an example where alpha = 0.10 to start with. If you get a p-value of 0.02, then you would reject the null. The same would apply for alpha = 0.05; however, with alpha = 0.01, the p-value is no longer smaller than alpha. At this point we do not reject the null. Your textbook may use the phrasing "fail to reject the null".
Going in the opposite direction, increasing the alpha value will make it more likely to reject the null. Each time you adjust the alpha value, keep the p-value to some fixed number (between 0 and 1).
