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3 years ago

James, Kendra, Nick, and Natasha spent $56.00 to buy a present for their Aunt Jane.

Mathematics

1 answer:

Olenka [21]3 years ago

3 0

Answer:

Each person contributed $14.00

Step-by-step explanation:

$56.00 total

James, Kendra, Nick, Natasha = 4 people

56 ÷ 4 = $14

To check:

$14 × 4 people = $56 total

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34 divided by 3 3/4 equals what in fraction form

anygoal [31]

Answer:

9.06

Step-by-step explanation:

6 0

3 years ago

I'm not really looking for an exact answer, I'm more so looking for an explanation on how to do this.

marshall27 [118]

I would have each block be 1/6 of a yard

You could technically have any value you want, but for me 1/6 is easiest because 1/2 and 1/3 will scale up to this like so

1/2 = (1/2)*(3/3) = 3/6

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2 years ago

A factory sells backpacks for $35 each. The cost to make 1 backpack is $15. In addition to the cost of making backpacks, the fac

Otrada [13]

Answer:9400 backpacks

$\geq$ Step-by-step explanation

since the number of packs to be sold in a is represented by x,

selling price for 1 week = 35x

cost price for 1 week = 15x

profit = 35x-15x = 20x

additional cost of production = 11,000

this implies that 20x - 11,000 $\geq$ 7800

20x - 11,000 $\geq$ 7,800

20x $\geq$ 7800+ 11000

20x $\geq$ 18,800

x $\geq$ 18800/2

x $\geq$ 9,400

at least 9,400 packs have to be sold each week to make a profit of $7800

7 0

3 years ago

Plz help I don’t know the answer

Rudiy27

Answer:

0.95

Step-by-step explanation:

8-3.25=4.75

4.75÷5=0.95

5 0

3 years ago

Of the volunteers donating blood in a clinic, 30% have the Rhesus (Rh) factor present in their blood. (a) If five volunteers are

maksim [4K]

Answer:

0.83193

Step-by-step explanation:

Probability of having the Rhesus (Rh) factor present in their blood; p = 0.3

Sample size; n = 5

We want to find the probability the probability that at least one does not have the Rh factor.

This will be;1 - P(X < 1)

This is a binomial probability distribution. Thus;

P(X = k) = C(n, k) × p^(k) × (1 - p)^(n - k)

P(X < 1) = P(X = 0)

Thus;

P(X = 0) = C(5, 0) × 0.3^(0) × (1 - 0.3)^(5 - 0)

P(X = 0) = 1 × 1 × 0.16807

P(X = 0) = 0.16807

Thus;

1 - P(X < 1) = 1 - 0.16807 = 0.83193

4 0

3 years ago