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san4es73 [151]
3 years ago
7

4 Gary has made 11 of 25 free throws in basketball. How many consecutive free throws must he make in

Mathematics
1 answer:
Alexeev081 [22]3 years ago
4 0
If he makes 15 out of 25 free throws then his shooting percentage will be 60%.
To figure it out just put 11 divided by 25 in your calculator and get .44 which is 44%. keep going up in numbers until you get .6 percent or 60 percent
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On a 1616 scale drawing of a bike, one part is 3 inches long. How long will the actual bike part be?
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4848 inches is how long the bike will be
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3 years ago
Paolo is using his grandmother’s cookie recipe. He always doubles the amount of chocolate chips and oats. The recipe calls for 2
nalin [4]

<u>Answer:</u>

y = 94.5 cups

<u>Step-by-step explanation:</u>

Let's say:

  • y = oats
  • x = chocolate chips = 212

=> Full Recipe = 212 + y

=> 2(Full Recipe) = 2(212 + y) = 613 cups

=> 2(Full Recipe) = 424 + 2y = 613 cups

=> 2y = 613 - 424

=> 2y = 189

=> y = 94.5

Therefore, the required oats to do double the recipe is 94.5 cups.

Hoped this helped.

GeniusUser

8 0
2 years ago
Are the following ratios proportional?<br><br> 5:8 and 25:40<br><br> a) Yes<br> b) No
Alenkasestr [34]

Answer:

a)yes

Step-by-step explanation:

5 times 5 is 25

8 times 5 is 40

5 0
2 years ago
Which expression is equal to 0?
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C if its a question on plato
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3 years ago
Read 2 more answers
A company compiles data on a variety of issues in education. In 2004 the company reported that the national college​ freshman-to
nasty-shy [4]

Answer:

1) Randomization: We assume that we have a random sample of students

2) 10% condition, for this case we assume that the sample size is lower than 10% of the real population size

3) np = 500*0.66= 330 >10

n(1-p) = 500*(1-0.66) =170>10

So then we can use the normal approximation for the distribution of p, since the conditions are satisfied

The population proportion have the following distribution :

p \sim N(p,\sqrt{\frac{\hat p(1-\hat p)}{n}})  

And we have :

\mu_p = 0.66

\sigma_{p}= \sqrt{\frac{0.66(1-0.66)}{500}}= 0.0212

Using the 68-95-99.7% rule we expect 68% of the values between 0.639 (63.9%) and 0.681 (68.1%), 95% of the values between 0.618(61.8%) and 0.702(70.2%) and 99.7% of the values between 0.596(59.6%) and 0.724(72.4%).

Step-by-step explanation:

For this case we know that we have a sample of n = 500 students and we have a percentage of expected return for their sophomore years given 66% and on fraction would be 0.66 and we are interested on the distribution for the population proportion p.

We want to know if we can apply the normal approximation, so we need to check 3 conditions:

1) Randomization: We assume that we have a random sample of students

2) 10% condition, for this case we assume that the sample size is lower than 10% of the real population size

3) np = 500*0.66= 330 >10

n(1-p) = 500*(1-0.66) =170>10

So then we can use the normal approximation for the distribution of p, since the conditions are satisfied

The population proportion have the following distribution :

p \sim N(p,\sqrt{\frac{\hat p(1-\hat p)}{n}})  

And we have :

\mu_p = 0.66

\sigma_{p}= \sqrt{\frac{0.66(1-0.66)}{500}}= 0.0212

And we can use the empirical rule to describe the distribution of percentages.

The empirical rule, also known as three-sigma rule or 68-95-99.7 rule, "is a statistical rule which states that for a normal distribution, almost all data falls within three standard deviations (denoted by σ) of the mean (denoted by µ)".

On this case in order to check if the random variable X follows a normal distribution we can use the empirical rule that states the following:

• The probability of obtain values within one deviation from the mean is 0.68

• The probability of obtain values within two deviation's from the mean is 0.95

• The probability of obtain values within three deviation's from the mean is 0.997

Using the 68-95-99.7% rule we expect 68% of the values between 0.639 (63.9%) and 0.681 (68.1%), 95% of the values between 0.618(61.8%) and 0.702(70.2%) and 99.7% of the values between 0.596(59.6%) and 0.724(72.4%).

8 0
3 years ago
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