Answer:
C. The importance of secondary effects
Explanation:
Secondary economic impact is a study of economic activities due to recurring rounds of spending by companies, households, and the government.
Secondary effects are long term and comes after the primary effect (first round of spending).
It is also called induced economic effect.
Answer:
It is cheaper to make the units in-house.
Explanation:
Giving the following information:
Make in-house:
Direct material $ 8
Direct labor 24
Overhead 40
Total costs per unit $72
Buying price= $60
<u>We need to determine which option provides the lower cost. Because 40% of overhead will remain constant, we have to take it out of the equation.</u>
<u>Production cost:</u>
Direct material $ 8
Direct labor 24
Overhead= 40*0.6= 24
Total production cost= $56
It is cheaper to make the units in-house.
Answer:
The correct answer is
d. lower interest rates and greater investment.
good luck
Based on the percentage of readers who own a particular make of the car and the random sample, we can infer that there is sufficient evidence at a 0.02 level to support the executive claim.
<h3>What is the evidence to support the executive's claim?</h3>
The hypothesis is:
Null hypothesis : P = 0.55
Alternate hypothesis : P ≠ 0.55
We then need to find the test statistic:
= (Probability found by marketing executive - Probability from publisher) / √( (Probability from publisher x (1 - Probability from publisher))/ number of people sampled
= (0.46 - 0.55) / √(( 0.55 x ( 1 - 0.55)) / 200
= -2.56
Using this z value as the test statistic, perform a two-tailed test to show:
= P( Z < -2.56) + P(Z > 2.56)
= 0.0052 + 0.0052
= 0.0104
The p-value is 0.0104 which is less than the significance level of 0.02. This means that we reject the null hypothesis.
The Marketing executive was correct.
Find out more on the null and alternate hypothesis at brainly.com/question/25263462
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The point estimate or p hat is a single value that shows the best estimation of a certain parameter among a population.
To calculate point estimate, we divide the parameter by the whole population.
In case of this problem:
p hat = 51/84 = 0.607
To get the percent, we multiply the output by 100:
% of point estimate = 0.607 x 100 = 60.7%
