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Mademuasel [1]
3 years ago
12

Ming made a triangular picture frame out of cardboard. The sides of the frame are 6.75 in., 6.75 in., and 8.375 in. Ming uses th

e addition below to determine the amount of string she needs to decorate the edges of the frame.
Which explains Ming’s error?

A. She should have included the decimal in 6.75 and aligned the decimal points to add 6.750 + 6.750 + 8.375 = 21.875.
B. She forgot to put the decimal point in two of the numbers: 0.675 + 0.675 + 8.375 = 9.725..
C. She added 6.75 twice, and she should have only added it once: 6.75 + 8.375 = 15.125.
D. She should have placed a zero placeholder after the decimal point to add 6.075 + 6.075 + 8.375 = 20.525.

Mathematics
2 answers:
netineya [11]3 years ago
8 0

Answer:

A hope this helps

Step-by-step explanation:

bija089 [108]3 years ago
4 0
The answer is A. When adding decimals, you need to line up the decimal points before adding them together. To make the problems clear, adding zeroes at the end of the numbers will help make the alignment clear.

   6.750
   6.750
<u>+ 8.375</u>
<u /> 21.875
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When a scientist conducted a genetics experiments with peas, one sample of offspring consisted of 943 peas, with 717 of them hav
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Using the normal approximation to the binomial distribution, it is found that:

a) 0.242 = 24.2% probability of getting 717 or more peas with red flowers.

b) Since Z < 2, 717 peas with red flowers is not significantly high.

c) Since 717 peas with red flowers is not a significantly high result, we cannot conclude that the scientist's assumption is wrong.

For each pea, there are only two possible outcomes. Either they have a red flower, or they do not. The probability of a pea having a red flower is independent of any other pea, which means that the binomial distribution is used to solve this question.

Binomial distribution:

Probability of x successes on n trials, with p probability.

Normal distribution:

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.
  • If Z > 2, the result is considered <u>significantly high</u>.

If np \geq 10 and n(1-p) \geq 10, the binomial distribution can be approximated to the normal with:

\mu = np

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

In this problem:

  • 943 peas, thus, n = 943
  • 3/4 probability of being red, thus p = \frac{3}{4} = 0.75.

Applying the approximation:

\mu = np = 943(0.75) = 707.25

\sigma = \sqrt{np(1-p)} = \sqrt{943(0.75)(0.25)} = 13.297

Item a:

Using continuity correction, this probability is P(X \geq 717 - 0.5) = P(X \geq 716.5), which is <u>1 subtracted by the p-value of Z when X = 716.5</u>.

Then:

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

Z = \frac{716.5 - 707.25}{13.297}

Z = 0.7

Z = 0.7 has a p-value of 0.758.

1 - 0.758 = 0.242

0.242 = 24.2% probability of getting 717 or more peas with red flowers.

Item b:

Since Z < 2, 717 peas with red flowers is not significantly high.

Item c:

Since 717 peas with red flowers is not a significantly high result, we cannot conclude that the scientist's assumption is wrong.

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