Answer:
A. 40
Explanation:
Calculation for what was the labor productivity, in chairs per worker per day
Using this formula
Labor productivity per day =Company Per day output/ Number of labor
Let plug in the formula
Labor productivity per day= 1600/8 days×5 workers
Labor productivity per day=1,600/40
Labor productivity per day= 40
Therefore the Labor productivity per day will be 40
Answer:
6%
Explanation:
As per given data
Quarter Real GDP ($billions) Long-Run Trend of Real GDP ($billions)
1 4,000 4,000
2 4,160 4,120
3 4,326 4,244
4 4,413 4,371
5 4,501 4,502
6 4,591 4,637
7 4,499 4,776
8 4,409 4,919
9 4,673 5,067
10 4,954 5,219
11 5,252 5,376
12 5,376 5,537
Growth of GDP = (DGP of Current/recent period - GDP of Prior period) / DGP of Prior period
In this question prior period is quarter 10 and current /recent period is quarter 11.
So, formula will be
Growth of GDP = (DGP of quarter 11 - GDP of quarter 10) / GDP of quarter 10
As we need to calculate the real GDP growth the formula will be as follow
Growth of real GDP = (Real DGP of quarter 11 - Real GDP of quarter 10) / Real GDP of quarter 10
Growth of real GDP = ($5,252 billion - $4,954 billion) / $4,954 billion
Growth of real GDP = $298 billion / $4,954 billion
Growth of real GDP = 6.02% = 6%
Based on the collected data on salaries of compliance specialists in corporate accounting firms. The salaries ranged from 69,000 to 369,000.
<h3>How much can one make as Compliance Specialist?</h3>
As a Compliance Specialist salary, the amount that can be made varies from country to another, but in U.S it us possible to make $60,491 per year, or $29.08 per hour.
Learn more about Compliance Specialist salary, at:
brainly.com/question/15414254
Job training had a positive effect on the Group 1 and it would be beneficial for the second group to have had it too.
Explanation:
In series analysis one compares two set of data in terms of their initial points and their final results and within if there are fluctuations in the matter during the series. In ere, the data given is of two points that is the initial data and the final data.
The two data points clearly show that the two groups were equivalent in 2003 but the first group which received job raining ended up progressing more than the second group so it is beneficial to get the job training that was offered.
