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Llana [10]
2 years ago
13

24 is 40% of what number? please show me the steps also.

Mathematics
1 answer:
ella [17]2 years ago
4 0
Answer:

1) 24 is <span>40%</span> of 60

<span><span>2) (.4)100x</span>=24</span>

<span><span>3) 25</span>x=24</span>

<span><span>4) 25</span>x⋅5=24⋅5</span>

<span>5) 2x=120</span>

<span><span><span>6) 2x/</span>2</span>=<span>120/2</span></span>

<span>7) x=<span>60</span></span>

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Leo has 18 yards of fabric that he wants to cut into pieces that are each 1 foot long. How many one foot long pieces can Leo cre
weqwewe [10]
54 pieces. Here is why:
1 yard = 3 feet
18 yards * (3 feet)/yard = 18*3 feet = 54 feet
Note that the yard units cancel out, leaving the answer in feet.
6 0
3 years ago
How are the lengths of the sides of the triangle and the measure of its angles related? 5cm,7cm,10cm.
Veronika [31]

5cm,7cm,and 10cm? im no professional but might wanna double check first


4 0
3 years ago
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Consider vectors u = ⟨2, 1⟩ and v = ⟨4, –1⟩ with the angle between them equal to 40°. What are the scalar projections uv and vu?
Crank

Answer: D. uv = 1.71 and vu = 3.16

Step-by-step explanation:

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7 0
2 years ago
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Jill’s bowling scores are approximately normally distributed with mean 170 and standard deviation 20, while Jack’s scores are ap
miss Akunina [59]

Answer:

a) The probability of Jack scoring higher is 0.3446

b) They probability of them scoring above 350 is 0.2119

Step-by-step explanation:

Lets call X the random variable that determines Jill's bowling score and Y the random variable that determines jack's. We have

X \simeq N(170,400)\\Y \simeq N(160,225)

Note that we are considering the variance on the second entry, the square of the standard deviation.

If we have two independent Normal distributed random variables, then their sum is also normally distributed. If fact, we have this formulas:

N(\lambda_1, \sigma^2_1) + N(\lambda_2, \sigma^2_2) = N(\lambda_1 + \lambda_2,\sigma^2_1 + \sigma^2_2) \\r* N(\lambda_1, \sigma^2_1) = N(r\lambda_1,r^2\sigma^2_1)  

for independent distributions N(\lambda_1, \sigma^2_1) , N(\lambda_2, \sigma^2_2) , and a real number r.

a) We define Z to be Y-X. We want to know the probability of Z being greater than 0. We have

Z = Y-X = N(160,225) - N(170,400) = N(160,225) + (N(-170,(-1)^2 * 400) = N(-10,625)

So Z is a normal random variable with mean equal to -10 and vriance equal to 625. The standard deviation of Z is √625 = 25.

Lets work with the standarization of Z, which we will call W. W = (Z-\mu)/\sigma = (Z+10)/25. W has Normal distribution with mean 0 and standard deviation 1. We have

P(Z > 0) = P( (Z+10)/25 > (0+10)/25) = P(W > 0.4)

To calculate that, we will use the <em>known </em>values of the cummulative distribution function Φ of the standard normal distribution. For a real number k, P(W < k) = Φ(k). You can find those values in the Pdf I appended below.

Since Φ is a cummulative distribution function, we have P(W > 0.4) = 1- Φ(0.4)

That value of Φ(0.4) can be obtained by looking at the table, it is 0.6554. Therefore P(W > 0.4) = 1-0.6554 = 0.3446

As a result, The probability of Jack's score being higher is 0.3446. As you may expect, since Jack is expected to score less that Jill, the probability of him scoring higher is lesser than 0.5.

b) Now we define Z to be X+Y Since X and Y are independent Normal variables with mean 160 and 170 respectively, then Z has mean 330. And the variance of Z is equal to the sum of the variances of X and Y, that is, 625. Hence Z is Normally distributed with mean 330 and standard deviation rqual to 25 (the square root of 625).

We want to know the probability of Z being greater that 350, for that we standarized Z. We call W the standarization. W is s standard normal distributed random variable, and it is obtained from Z by removing its mean 330 and dividing by its standard deviation 25.

P(Z > 350) = P((Z  - 330)/25 > (350-330)/25) = P(W > 0.8) = 1-Φ(0.8)

The last equality comes from the fact that Φ is a cummulative distribution function. The value of Φ(0.8) by looking at the table is 0.7881, therefore P(X+Y > 350) = 1 - Φ(0.8) = 0.2119.

As you may expect, this probability is pretty low because the mean value of the sum of their combined scores is quite below 350.

I hope this works for you!

Download pdf
6 0
3 years ago
Belle's Cupcakes recently sold 6 pistachio cupcakes and 8 other cupcakes. Considering this data, how many of the next 56 cupcake
VikaD [51]

Answer: 24 pistachios cupcakes.

Step-by-step explanation:

We know that:

They recently sold 6 pistachio cupcakes and 8 other cupcakes.

Then we can model this with the ratio 6:8

This means that for each 6 pistachio cupcakes sold, they also sell 8 of another type of cupcakes.

Whit this info, if they sell 56 cupcakes, how many of them will be pistachio cupcakes?

Using the ratio above, we must find a number N such that:

N*6 + N*8 = 56.

N*(6 + 8) =  56

N*14 = 56

N = 56/14 = 4.

This means that:

out of the 56 cupcakes, 4*6 = 24 are pistachios cupcakes

                                        4*8 = 32 are other cupcakes.

Then you should expect that 24 out of the 56 cupcakes are pistachios cupcakes.

6 0
3 years ago
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