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ss7ja [257]
2 years ago
7

BIDEN OR TrUmP have a nice day

Mathematics
2 answers:
lana [24]2 years ago
6 0

Answer:

biden

Step-by-step explanation:

sammy [17]2 years ago
3 0

Answer:

BIDEN

Step-by-step explanation:

no trump hehehhehehe

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Help anyone? please?
ValentinkaMS [17]

Answer:

x=11.2

Step-by-step explanation:

Set up a proportion:

x+11/36 = 37/60

Cross multiply:

1332=60(x+11)

Distribute:

1332=60x+660

Subtract 660 from 1332

672=60x

Divide:

x=11.2

I'm not sure if this is the correct answer but I hope this helps! :)

Correct me if I'm wrong!

6 0
3 years ago
Is the first side “SW=XW” or “ST=XU”?
olya-2409 [2.1K]

Answer:

SW =XW and ST=XU and UW=TW

Step-by-step explanation:

All are true and correct since the two triangles are congruent

5 0
3 years ago
Read 2 more answers
In 2008 the Better Business Bureau settled 75% of complaints they received (USA Today, March 2, 2009). Suppose you have been hir
Ede4ka [16]

Answer:

Explained below.

Step-by-step explanation:

According to the Central limit theorem, if from an unknown population large samples of sizes n > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.

The mean of this sampling distribution of sample proportion is:

 \mu_{\hat p}= p

The standard deviation of this sampling distribution of sample proportion is:

 \sigma_{\hat p}=\sqrt{\frac{p(1-p)}{n}}

(a)

The sample selected is of size <em>n</em> = 450 > 30.

Then according to the central limit theorem the sampling distribution of sample proportion is normally distributed.

The mean and standard deviation are:

\mu_{\hat p}=p=0.75\\\\\sigma_{\hat p}=\sqrt{\frac{p(1-p)}{n}}=\sqrt{\frac{0.75(1-0.75)}{450}}=0.0204

So, the sampling distribution of sample proportion is \hat p\sim N(0.75,0.0204^{2}).

(b)

Compute the probability that the sample proportion will be within 0.04 of the population proportion as follows:

P(p-0.04

                                          =P(-1.96

Thus, the probability that the sample proportion will be within 0.04 of the population proportion is 0.95.

(c)

The sample selected is of size <em>n</em> = 200 > 30.

Then according to the central limit theorem the sampling distribution of sample proportion is normally distributed.

The mean and standard deviation are:

\mu_{\hat p}=p=0.75\\\\\sigma_{\hat p}=\sqrt{\frac{p(1-p)}{n}}=\sqrt{\frac{0.75(1-0.75)}{200}}=0.0306

So, the sampling distribution of sample proportion is \hat p\sim N(0.75,0.0306^{2}).

(d)

Compute the probability that the sample proportion will be within 0.04 of the population proportion as follows:

P(p-0.04

                                          =P(-1.31

Thus, the probability that the sample proportion will be within 0.04 of the population proportion is 0.81.

(e)

The probability that the sample proportion will be within 0.04 of the population proportion if the sample size is 450 is 0.95.

And the probability that the sample proportion will be within 0.04 of the population proportion if the sample size is 200 is 0.81.

So, there is a gain in precision on increasing the sample size.

6 0
2 years ago
1.56 times 48 equals
Crank

Answer:

It equals 74.88

Step-by-step explanation:

U jus multiply them

5 0
2 years ago
Read 2 more answers
A)$150 at 3 % interest for 2 years
tamaranim1 [39]

Answer:

A)  159.135 = X

B) 2,531.25 = X

C)  6,187.5 = X

D) 831,947.46 = X

Step-by-step explanation:

The following investments are required to be calculated:

A) $ 150 at 3% interest for 2 years

B) $ 750.00 at 1/2% interest for 3 years

C) $ 2,250.00 at 1 3/4% interest for 1 year

D) $ 2,550.00 at 3 1/4 interest for 4 years

Therefore, the following calculations must be performed:

A)

150 x (1 + 0.03) ^ 2 = X

150 x 1.03 ^ 2 = X

159.135 = X

B)

750 x (1 + 0.5) ^ 3 = X

750 x 1.5 ^ 3 = X

2,531.25 = X

C)

2,250 x (1 + 1.75) = X

2,250 x 2.75 = X

6,187.5 = X

D)

2,550 x (1 + 3.25) ^ 4 = X

2,550 x 4.25 ^ 4 = X

831,947.46 = X

4 0
2 years ago
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