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Mademuasel [1]
3 years ago
9

A car dealer who sells only late-model luxury cars recently hired a new salesman and believes that this salesman is selling at l

ower markups. He knows that the long-run average markup in his lot is $5,600. He takes a random sample of 16 of the new salesman's sales and finds an average markup of $5,000 and a standard deviation of $800. Assume the markups are normally distributed. What is the value of an appropriate test statistic for the car dealer to use to test his claim?
Business
1 answer:
Natasha2012 [34]3 years ago
4 0

Answer:

t=\frac{5000-5600}{\frac{800}{\sqrt{16}}}=-3      

Explanation:

Data given and notation      

\bar X=5000 represent the sample mean      

s=800 represent the standard deviation for the sample      

n=16 sample size      

\mu_o =5600 represent the value that we want to test    

\alpha represent the significance level for the hypothesis test.    

t would represent the statistic (variable of interest)      

p_v represent the p value for the test (variable of interest)  

State the null and alternative hypotheses.      

We need to conduct a hypothesis in order to determine if the mean is lower than 5600, the system of hypothesis would be:      

Null hypothesis:\mu \geq 5600      

Alternative hypothesis:\mu < 5600      

We don't know the population deviation, so for this case is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:      

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}} (1)      

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic      

We can replace in formula (1) the info given like this:      

t=\frac{5000-5600}{\frac{800}{\sqrt{16}}}=-3      

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3 0
2 years ago
You work for a marketing firm that has just landed a contract with Run-of-the-Mills to help them promote three of their products
Mazyrski [523]

Answer:

1.1 substitutes do not market together

-0.35 complements market together

Explanation:

1.1

-0.35

Cross price elasticity of demand measures the responsiveness of quantity demanded of good A to changes in price of good B.

If cross price elasticity of demand is positive, it means that the goods are substitute goods.

Substitute goods are goods that can be used in place of another good.

if the price of a good increases, the demand for the substitute increases and if the price of the good reduces, the demand for the substitute increases.

If the cross-price elasticity is negative, it means that the goods are complementary goods.

Complementary goods are goods that are consumed together

Cross price elasticity = percentage change in quantity demanded of good A / percentage change in the price of good B

Frizzles = -22% / -20% = 1.1

Mookies = 7 / -20 = -0.35

5 0
3 years ago
Which of the following is a non depository financial institution?
NISA [10]

It’s D just did the test


5 0
3 years ago
W
Alexxandr [17]

Answer:

a).

  • Labor hours productivity=3.500
  • Multi-factor productivity=2.423

b). The reduction in labor hours per employee per week to achieve this goal=15.735 hours

c). The maximum value that the overhead costs per week can be to ensure the multi-factor productivity is at least 1.257=$21,059.666

Explanation:

a).

  • <em>Step 1: Determine the labor hours productivity</em>

Labor output per week=potential leads×fee

where;

potential leads=5% of potential leads, and potential leads=3,000

potential leads=5%×3,000

potential leads=(5/100)×3,000=150

one-time fee=$70

replacing;

Labor output per week=70×150=$10,500

Labor input per week=cost per hour per employee×number of employees×number of hours worked

where;

cost per hour per employee=$25

number of employees=3

number of hours worked=40

replacing;

Labor input per week=25×3×40=$3,000

Labor hours productivity=labor output per week/labor input per week

Labor hours productivity=10,500/3,000=3.500

  • <em>Step 2: Determine the multi-factor productivity</em>

Multi-factor productivity=Generated fees/(labor cost+material cost+overhead cost)

where;

generated fees=number of employees×potential leads×potential ratio×fee

number of employees=3, potential leads=3,000, potential ratio=5%=5/100=0.05, fee=$70

generated fees=3×3,000×0.05×70=$31,500

Labor cost=$3,000

Material cost=$1,000

Overhead cost=$9,000

Total cost=3,000+1,000+9,000=$13,000

replacing;

Multi-factor productivity=31,500/13,000=2.423

b). Increasing the multi-factor productivity (MP) by 10%

New MP=(110/100)×2.423=2.665

New MP=generated fees/labor cost+material cost+overhead cost

labor cost=cost per hour per employee×number of employees×number of hours worked

where;

cost per hour per employee=$25

number of employees=3

number of hours worked=h

labor cost=25×3×h=75 h

material cost=$1,000

overhead cost=$9,000

generated fees=$31,500

New MP=2.665

replacing;

2.665=31,500/{(75 h)+(1,000)+(9,000)}

2.665=31,500/75 h+10,000

2.665(75 h+10,000)=31,500

199.875 h+26,650=31,500

199.875 h=31,500-26,650

199.875 h=4,850

h=4,850/199.875

h=24.265

New labor hours=24.265 hours per week

Initial labor hours=40 hours per week

Reduction in labor hours=Initial labor hours-new labor hours

Reduction in labor hours=(40-24.265)=15.735

The reduction in labor hours per employee per week to achieve this goal=15.735 hours

c). Using a multi-factor of 1.257

MP=generated fees/labor cost+material cost+overhead cost

where;

MP=1.257

generated fees=$31,500

Labor cost=$3,000

Material cost=$1,000

Overhead cost=c

replacing;

1.257=31,500/(c+3,000+1,000)

1.257=31,500/c+4,000

1.257(c+4,000)=31,500

1.257 c+5,028=31,500

1.257 c=31,500-5,028

1.257 c=26,472

c=26,472/1.257=21,059.666

The maximum value that the overhead costs per week can be to ensure the multi-factor productivity is at least 1.257=$21,059.666

8 0
3 years ago
Brandy works in a laboratory. She performs experiments to develop new methods of food production and processing
Len [333]

Answer:

1) Food scientist

2) Farm management advisor

3) Farm labor contractor

Explanation:

6 0
3 years ago
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