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Archy [21]
3 years ago
15

Mai had 5 candy bars she ate half of one candy bar and dicided to distribute the remaining bars between her two sisters and her

self how many candy bars did each girl reicive
Mathematics
1 answer:
gogolik [260]3 years ago
7 0

━━━━━━━━━━━━━━━ ♡ ━━━━━━━━━━━━━━━  

So there are five candy bars.

Herself and two sisters equals 3 people in total.

This is a graph of 5 candy bars, each line being 1/2.

━ ━

━ ━

━ ━

━ ━

━ ━

If she ate half of one... the graph would become this.

━ ━

━ ━

━ ━

━ ━

━

Now there are 9 halves. You need to split the 9 halves for 3 people. 9 divided by 3 is 3.

Each person gets 3 halves, or 1 and 1 half.

Mai: ━ ━ ━

Sister 1: ━ ━ ━

Sister 2: ━ ━ ━

Altogether that is 9 halves, AKA the number of halves Mai had after she ate 1/2.

The amount Mai ate in the first place: ━

9 halves plus 1 half, equals 10 halves. Each whole has 2 halves. 10 divided by 2 is 5, AKA the number of candy bars she had in the first place.

━━━━━━━━━━━━━━━ ♡ ━━━━━━━━━━━━━━━  

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With 89.9% we can say that the mean improvement is between 583.1 and 728.1 vehicles per hour.

Step-by-step explanation:

We are given that the effectiveness of the new method was evaluated in a simulation study. In 50 simulations, the mean improvement in traffic flow in a particular intersection was 655.6 vehicles per hour, with a standard deviation of 311.7 vehicles per hour.

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<em>Let </em>\bar X<em> = sample mean improvement</em>

The z-score probability distribution for sample mean is given by;

            Z =  \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } ~ N(0,1)

where, \mu = mean improvement = 655.6 vehicles per hour

            \sigma = standard deviation = 311.7 vehicles per hour

            n = sample of simulations = 50

The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X.

Now, Probability that the mean improvement is between 583.1 and 728.1 vehicles per hour is given by = P(583.1 < \bar X < 728.1) = P(\bar X < 728.1) - P(\bar X \leq 583.1)

  P(\bar X < 728.1) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } < \frac{728.1-655.6}{\frac{311.7}{\sqrt{50} } } ) = P(Z < 1.64) = 0.9495

  P(\bar X \leq 583.1) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } \leq \frac{583.1-655.6}{\frac{311.7}{\sqrt{50} } } ) = P(Z \leq -1.64) = 1 - P(Z < 1.64)

                                                            = 1 - 0.9495 = 0.0505                      

<em />

<em>So, in the z table the P(Z </em>\leq<em> x) or P(Z < x) is given. So, the above probability is calculated by looking at the value of x = 1.64 in the z table which has an area of 0.9495.</em>

Therefore, P(583.1 < \bar X < 728.1) = 0.9495 - 0.0505 = 0.899 or 89.9%

Hence, with 89.9% we can say that the mean improvement is between 583.1 and 728.1 vehicles per hour.

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