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AnnyKZ [126]
2 years ago
9

Grandma received 0.25 liters of medicine from her doctor. The directions asked her to take one teaspoonful 3 times daily until i

t is finished. A full teaspoon has a capacity of 4 ml. Grandma started taking her medicine on November 20th. What date should the medicine finish?
Mathematics
1 answer:
kupik [55]2 years ago
3 0

Answer:

Dec 10

Step-by-step explanation:

0.25 liter = 250 ml

4 ml * 3 = 12 ml

250/12 = 20.83 days

Nov 20 - Nov 30: 11 days

Dec 1 - Dec 9: 9 days

On December 9, she can still take her 3 doses.

By December 9, she will have taken 12 ml per day for 20 days for a total of 240 ml. She has 10 ml left for Dec 10th.

On Dec 10, she will take 2 doses of 4 ml and 1 dose of 2 ml, and she will finish the medicine.

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3 years ago
Slove the inequality 5(x + 1) &lt;25<br> x &lt; 4<br> x &gt; -4<br> x &gt; 4<br> Pls help meee
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Use the distributive property to make 5x+5.

5x+5<25

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3 years ago
A fair coin is to be tossed 20 times. Find the probability that 10 of the tosses will fall heads and 10 will fall tails, (a) usi
lbvjy [14]

Using the distributions, it is found that there is a:

a) 0.1762 = 17.62% probability that 10 of the tosses will fall heads and 10 will fall tails.

b) 0% probability that 10 of the tosses will fall heads and 10 will fall tails.

c) 0.1742 = 17.42% probability that 10 of the tosses will fall heads and 10 will fall tails.

Item a:

Binomial probability distribution

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

C_{n,x} = \frac{n!}{x!(n-x)!}

The parameters are:

  • x is the number of successes.
  • n is the number of trials.
  • p is the probability of a success on a single trial.

In this problem:

  • 20 tosses, hence n = 20.
  • Fair coin, hence p = 0.5.

The probability is <u>P(X = 10)</u>, thus:

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 10) = C_{20,10}.(0.5)^{10}.(0.5)^{10} = 0.1762

0.1762 = 17.62% probability that 10 of the tosses will fall heads and 10 will fall tails.

Item b:

In a normal distribution with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

  • It measures how many standard deviations the measure is from the mean.  
  • After finding the z-score, we look at the z-score table and find the p-value associated with this z-score, which is the percentile of X.
  • The binomial distribution is the probability of <u>x successes on n trials, with p probability</u> of a success on each trial. It can be approximated to the normal distribution with \mu = np, \sigma = \sqrt{np(1-p)}.

The probability of an exact value is 0, hence 0% probability that 10 of the tosses will fall heads and 10 will fall tails.

Item c:

For the approximation, the mean and the standard deviation are:

\mu = np = 20(0.5) = 10

\sigma = \sqrt{np(1 - p)} = \sqrt{20(0.5)(0.5)} = \sqrt{5}

Using continuity correction, this probability is P(10 - 0.5 \leq X \leq 10 + 0.5) = P(9.5 \leq X \leq 10.5), which is the <u>p-value of Z when X = 10.5 subtracted by the p-value of Z when X = 9.5.</u>

X = 10.5:

Z = \frac{X - \mu}{\sigma}

Z = \frac{10.5 - 10}{\sqrt{5}}

Z = 0.22

Z = 0.22 has a p-value of 0.5871.

X = 9.5:

Z = \frac{X - \mu}{\sigma}

Z = \frac{9.5 - 10}{\sqrt{5}}

Z = -0.22

Z = -0.22 has a p-value of 0.4129.

0.5871 - 0.4129 = 0.1742.

0.1742 = 17.42% probability that 10 of the tosses will fall heads and 10 will fall tails.

A similar problem is given at brainly.com/question/24261244

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