In the natural gas industry, low average total costs are obtained only through large-scale production. In other words, the initial cost of setting up all the necessary pipes and hoses makes it risky and, most likely, unprofitable for competitors to enter the market.

Economies of Scale

Step-by-step explanation:

Economies of Scale describes the proportionate saving in costs gained by an increased level of production. Knowing that the production of natural gas is very expensive and requires a large investment. The costs and risks of the processes required in the upstream and downstream of natural gas discourages competition. Apart from the large initial investment, a drilling company can never be totally sure that they will be able to find and extract natural gas or petroleum. So besides having to spend a lot of money, so many risk is been assumed.

In a situation where the competitor finds natural gas, in order for the downstream process to be profitable, they must be able to extract a large volume to achieve economies of scale.

so firstly, we need to isolate the y variables to be able to solve these inequalities. firstly, add 0.5x on both sides of the first inequality and subtract 1.5x on both sides of the second inequality:

now since the slope is positive for the first inequality, this means that the line going upwards belongs to the first inequality, and the line going downwards belongs to the second inequality.

next, since y ≥ in the first inequality, this means that the shaded region will be above the first inequality's line, thus shading regions a and b.

next, since y ≤ in the second inequality, this means that the shaded region is going to be below this line, thus shading regions a and c.

since both lines shade region a, this means that region a is the solution.

step-by-step explanation:

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d. 24+-0.114

step-by-step explanation:

the question requires us to calculate the approximate 95% confidence interval for the mean number of ounces of ketchup per bottle in the sample given the following statistics;

sample mean = 24

standard deviation, σ = 0.4

sample size , n = 49

the confidence interval for a population mean is calculated using the formula;

sample mean ± z-score*(σ/sqrt(n))

the z-score associated with a 95% confidence interval, from the standard normal tables, is;

1.96

substituting these values into the formula;

24 ± 1.96*(0.4/7)

= 24 ± 0.112

from the alternatives given, choice d is closest to the above expression;