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ale4655 [162]
3 years ago
5

What is an acquisition fee?

Mathematics
1 answer:
pantera1 [17]3 years ago
8 0

A lessor charges an acquisition fee to cover any expenses they incur while arranging a lease. Acquisition fees can sometimes also refer to charges and commissions that someone pays for the acquisition or purchase of property

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15-<br><br><br> pls help!!!!<br><br><br><br> math<br><br> pls help answer other questions<br> too
ddd [48]

Answer:

A

Step-by-step explanation:

The projection of vector B on unit vector a is

(B•a)a

av(unit vector of v)= 1/√2(-1,1)

u•av= 1/√2 × (-5+7)= √2

(u•av)av= √2 × 1/√2(-1,1)= (-1,1)

3 0
3 years ago
When a survey asked subjects whether they would be willing to accept cuts in their standard of living to protect the​ environmen
gtnhenbr [62]

Answer:

(a) The point estimate of the proportion of the population who would answer yes is 0.295.

(b) The margin of error for a​ 95% confidence interval is 0.0259.

(c) 95% confidence interval for population proportion is [0.2691 , 0.3209].

Step-by-step explanation:

We are given that a survey asked subjects whether they would be willing to accept cuts in their standard of living to protect the​ environment, 352 of 1195 subjects said yes.

Let \hat p = <u><em>sample proportion of subjects who said yes.</em></u>

(a) The point estimate of the proportion of the population who would answer yes = \hat p =  \frac{X}{n}

So,  \hat p = \frac{352}{1195}  = <u>0.295</u>

(b) Margin of error is given by =  Z_(_\frac{\alpha}{2}_) \times \text{Standard of Error}

where, \alpha = level of significance = 1 - 0.95 = 5%

At 5% level of significance, z table gives critical value of 1.96 for two-sided interval.

Standard of error =  \sqrt{\frac{\hat p(1-\hat p)}{n} } =  \sqrt{\frac{0.295(1-0.295)}{1195} }  = 0.0132

So, Margin of error for 95% confidence interval = 1.96 \times 0.0132

                                                                               = <u>0.0259</u>

(c) 95% confidence interval for population proportion is given by =

                   Point estimate \pm Margin of error

              ⇒ 0.295 \pm 0.0259

              ⇒ [0.295 - 0.0259 , 0.295 + 0.0259]

              ⇒ [0.2691 , 0.3209]

So, 95% confidence interval = [0.2691 , 0.3209]

The numbers in this interval​ represent that we are 95% confident that the population proportion will lie between 0.2691 and 0.3209.

(d) Assumptions needed for constructing a confidence interval are;

  • The data must be sampled randomly.
  • Sample values must be independent of each other.
  • Data must follow normal distribution.
8 0
3 years ago
How to find the inverse of h(x) = 3/ -x - 2 List steps.
PtichkaEL [24]
To find the inverse,

First, you would have to switch the domain and range. In other words, swap x and y:

h(x) = 3/ -x-2
y = 3/ -x-2
x = 3/ -y-2

Then, when you have this, simply solve for y:

x = 3/-y-2
x (-y-2) = 3/-y-2 (-y-2)
x(-y-2) /x= 3 /x
-y-2 = 3/x
-y = 3/x + 2
 y = -3/x -2

So the inverse would be
 h⁻¹(x)= -3/x -2
7 0
4 years ago
What was the mean price
ahrayia [7]

Answer:

$6

Step-by-step explanation:

add all of them up and divide by the amout of numbers there

5 0
3 years ago
Help ASAP please thanks
andrew-mc [135]

Answer:

#1: -2 ≤ y ≤ ∞

#2: -2 ≤ x ≤ 2

#3: -4 ≤ y ≤ 3

#4: -5 ≤ y ≤ ∞

#5: 0 ≤ x ≤ ∞

Step-by-step explanation:

To do these, you must understand what range and domain are:

Range: all the values that y can be

Domain: all the values that x can be

#1: It's asking for range, so look at the posible y values. The smallest y value is -2, and the largest is actually infinity. So, the range is: -2 ≤ y ≤ ∞.

#2: It's asking for domain, so look at the possible x values. The smallest is -2 and the largest is 2, so: -2 ≤ x ≤ 2.

#3: Again, it's asking for range, so look at the possible y values. The smallest is -4, and the largest is 3, so: -4 ≤ y ≤ 3.

#4: It's asking for range. The smallest value is -5, and the largest goes to infinity (from the arrows), so: -5 ≤ y ≤ ∞.

#5: It's asking for domain. The smallest x value is 0, and it goes to infinity. So: 0 ≤ x ≤ ∞.

6 0
3 years ago
Read 2 more answers
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