I believe that the best answer to the choices given in your question is<span>D) Public service- police, fire fighter, social worker</span>
I hope I d come to help you with your question.
Have a nice day ahead.
Answer:
A
D
Explanation:
Internal rate of return is the discount rate that equates the after tax cash flows from an investment to the amount invested.
Because the IRR of both projects are positive, both projects are acceptable.
If the manager can only choose one project, she should choose the one with the higher IRR because it would be more profitable.
Answer:
the amount of interest expense as on June 30 is $50,000
Explanation:
The computation of the amount of interest expense as on June 30 is shown below
= Bond amount × rate of interest × number of months ÷ total number of months
= $2,000,000 × 5 months × 6 months ÷ 12 months
= $50,000
hence, the amount of interest expense as on June 30 is $50,000
We simply applied the above formula so that the correct value could come
And, the same is to be considered
<span>Put the individual p-values in ascending order.Assign ranks to the p-values. For example, the smallest has a rank of 1, the second smallest has a rank of 2.<span>Calculate each individual p-value’s Benjamini-Hochberg critical value, using the formula (i/m)Q, where:<span>i = the individual p-value’s rank,m = total number of tests,Q = the false discovery rate (a percentage, chosen by you).</span></span>Compare your original p-values to the critical B-H from Step 3; find the largest p value that is smaller than the critical value.</span>
As an example, the following list of data shows a partial list of results from 25 tests with their p-values in column 2. The list of p-values was ordered (Step 1) and then ranked (Step 2) in column 3. Column 4 shows the calculation for the critical value with a false discovery rate of 25% (Step 3).
The bolded p-value (for Children) is the highest p-value that is also smaller than the critical value: .042 < .050. <span>All </span>values above it (i.e. those with lower p-values) are highlighted and considered significant, even if those p-values are lower than the critical values. For example, Obesity and Other Health are individually, not significant when you compare the result to the final column (e.g. .039 > .03). However, with the B-H correction, they are considered significant; in other words, you would reject the null hypothesis for those values.