All categories

3 years ago

Word expression for 3+(4×12)

Mathematics

1 answer:

Anni [7]3 years ago

4 0

Fifty one is the answer to your question

You might be interested in

Convert a markup of 15% on selling price to its equivalent markup on cost.

spayn [35]

Answer:

option: D is correct. ( (D) a markup of 15% on selling price is equivalent to a 85% markup on cost ).

Step-by-step explanation:

" Markup is the percentage difference between a product's cost and its selling price "

Since we are asked to Convert a markup of 15% on selling price to its equivalent markup on cost.

As there is a markup of 15% on selling price. Hence the cost of the product would be (100-15)%=85% of the selling price.

<em>Hence, a markup of 15% on selling price is equivalent to a 85% markup on cost.</em>

<em>Hence, option D is true.</em>

5 0

3 years ago

Roger completed a probability experiment with a coin. He flipped the coin 32 times, and it landed on tails eight times. He looke

Vsevolod [243]

This is easy!
The overall amounts of flips is 32, which puts it on the bottom. It gave you a number of times you flipped it and received 8.

Giving us 8/32
which is 1/4 and in percentage form it is 25%

6 0

2 years ago

Will give brainlist if you can help!

kkurt [141]

Answer: 12:5

Step-by-step explanation:

4 0

2 years ago

You throw two four-sided dice. Let the random variable X represent the maximum value of the two dice. Compute E(X). Round your a

Troyanec [42]

Answer:

E(X)=3.125

Step-by-step explanation:

We are given that two four sided dice.

Then , the sample space

{(1,1),(1,2),(1,3),(1,4),(2,1),(2,2),(2,3),(2,4),(3,1),(3,2),(3,3),(3,4),(4,1),(4,2),(4,3),(4,4)}

Total number of outcomes=16

Let the random variable X represent the maximum value of the two dice

Outcomes X P(X)

(1,1) 1 1/16

(1,2),(2,1),(2,2) 2 3/16

(1,3),(2,3),(3,1),(3,2),(3,3) 3 5/16

(1,4),(3,4) ,(2,4),(4,1),(4,2),(4,3),(4,4) 4 7/16

Using the probability formula

$P(E)=\frac{Favorable\;outcomes}{Total\;number\;of\;outcomes}$

Now,

$E(X)=\sum_{i=1}^{n}x_iP(x_i)$

$E(x)=1(1/16)+2(3/16)+3(5/16)+4(7/16)$

$E(x)=\frac{1+6+15+28}{16}$

$E(x)=\frac{50}{16}=3.125$

7 0

3 years ago

Adult male heights have a normal probability distribution with a mean of 70 inches and a standard deviation of 4 inches. What is

raketka [301]

Answer: 0.5

Step-by-step explanation:

Given : Adult male heights have a normal probability distribution .

Population mean : $\mu = 70 \text{ inches}$

Standard deviation: $\sigma= 4\text{ inches}$

Let x be the random variable that represent the heights of adult male.

z-score : $z=\dfrac{x-\mu}{\sigma}$

For x=70, we have

$z=\dfrac{70-70}{4}=0$

Now, by using the standard normal distribution table, we have

The probability that a randomly selected male is more than 70 inches tall :-

$P(x\geq70)=P(z\geq0)=1-P(z$

Hence, the probability that a randomly selected male is more than 70 inches tall = 0.5

4 0

2 years ago

Read 2 more answers