Pls help me I really need it.

timama [110]

First: You add 3 to each side. Second: You multiply each side by 3. Third: You gaze in wondrous amazement at the answer, which lies revealed before you on the page.

3 0

3 years ago

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Determine Cove’s break-even point in units and sales dollars. 2. Determine the bakery’s margin of safety if it currently sells 4

swat32

Answer:

a) At break even point, Q = 380 units, Sales dollar = $5247.8

b) Margin of safety at Q = 400 units is 0.05 × 100 = 5

c) Number of cakes that need to be sold before a profit of $2200 is made = 595 cakes

Step-by-step explanation:

Let the number of units be Q

Cost equation = (fixed cost) + (Variable cost)

Fixed Cost = $3898.8

Variable Cost = Variable cost per unit × number of units produced = (2.32 + 1.11 + 0.12) × Q = 3.55Q

Cost equation = 3898.8 + 3.55Q

Revenue = price per unit × number of units sold = 13.81 × Q = 13.81Q

At break even point,

Total cost = Revenue

3898.8 + 3.55Q = 13.81Q

10.26Q = 3898.8

Q = 380 units

In sales dollars, R = 13.81Q = 13.81 × 380 = $5247.8

b) Margin of safety = 100 × (Current sales - Breakeven point sales)/(current sales)

Breakeven point sales = $5247.8

At Q = 400 units, Current sales = 13.81 × 400 = $5524

Margin of safety = 100 × (5524 - 5247.8)/5524 = 5

c) number of cakes that Cove must sell to generate $2,200 in profit.

Profit = Revenue - Total Cost

2200 = 13.81Q - (3898.8 + 3.55Q)

2200 = 10.26Q - 3898.8

10.26Q = 2200 + 3898.8 = 6098.8

Q = 594.4 = 595 units

5 0

3 years ago

The percentage of married couples who own a single family home is 33% for a given population. A financial analyst is interested

erik [133]

Answer:

For samples of size n=200, the standard error is of 0.033.

For samples of size n=300, the standard error is of 0.027.

For samples of size n=400, the standard error is of 0.024.

Step-by-step explanation:

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$