Answer:
monthly data series in a GDP
Explanation:
A GDP is defined as the actual domestically manufactured or produced products or the services provided in a financial year which describes or estimates the financial status or economic status of a country. GDP stands for Gross domestic product.
By analyzing the monthly data series of goods or services produced one can predict the real GDP of a country to be. One can use the monthly observations of the employment, unit auto as well as truck sales, sousing starts, retail sales, trade, automobile inventories, manufacturing, shipment of machinery and equipment, index of the industrial production, etc. to predict the GDP growth or get an idea of the GDP figures that are going to show the robust growth of the economy.
The right answer for the question that is being asked and shown above is that: "TRUE."Almost every phase of business and economic activity falls under some form of government regulation. This statement is true as far as the phase of business and economic activity is concerned.
Answer:
Assuming that you can only choose one answer, the most suitable one would be (A) Chris designs models to make traffic flow better, which enables Brian to get to his company’s warehouse faster.
Explanation:
This answer is correct because Chris is a traffic planner – thus he merely designs the traffic flow, he does not create it, thus making answer (D) incorrect. Though (B) is true, it doesn’t relate to Chris’ career, making it false as well. As for (C), the answer is not correct because Chris doesn’t design the maps of the state, he only designs the traffic flow.
Answer:
$C$8
Explanation:
The Symbol $ means that by copying and pasting to another cell, the cell references will not change.
In this case, the references are "locked" onto column C. Copying the formula to some other location will not change the references since they are absolute.
Answer:
Explanation:
Experiments were performed for 240 people, 60 people test positive.
Step 1: we calculate the sample proportion; p= 60/240= 0.25.
Step 2: calculate the standard error for the sample, which is the square root of sample proportion,p = p(1-p)/n, n=100
0.25(1-0.25)/100
= 0.04.
Step 3: calculate the test statistics; assuming the hypothesis test percentage is 25%
Then, we say 0.25-1=0.75
-0.75/0.04
= -1.875.
In particular, the sample results are -1.875 standard error.
Probability of Z is less than -1.875.
Look up it value in the Z table
