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IgorC [24]
2 years ago
9

on her first day of work, mia sold one straw hat. on day two, she sold three straw hats. on day three, she sold five straw hats,

on each succeeding day, she sold two more straw hats than she had sold on the previous day. how many straw hats in total had mia sold after working 40 days?
Mathematics
1 answer:
garri49 [273]2 years ago
6 0

If Mia sold 2 more hats on each suceeding day, after working 40 days it is expected Mia had sold a total of 1523 hats.

<h3>How many hats will Mia sell everyday?</h3>

Day: Hats

  • 1 = 1
  • 2=3
  • 3 = 5
  • 4=7
  • 5= 9
  • 6=11
  • 7= 13
  • 8= 15
  • 9=17
  • 10=19
  • 11= 21
  • 12=23
  • 13= 25
  • among others

You can notice the number of hats she will sell follow a pattern as there are only sequential odd numbers.

<h3>How many hats will Mia sell in total?</h3>

By following the sequence let's add the hats she will sell everyday:

  • 1 + 3 + 5 + 7 + 9 + 11 + 13 + 15 + 17 + 19 + 21 + 23 + 25 + 27 + 29 + 31 + 33 + 35 + 37 + 39 + 41 + 43 + 45 + 47 + 49 + 51 + 53 + 55 + 57 + 59 + 61 + 63 + 65 + 67 + 69 + 71 + 73 + 75 + 79 = 1523

Learn more about sums in: brainly.com/question/13013054

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What is the value of the expression below when x = 3?<br> 10x2 – 7x + 10
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Answer:

79

Step-by-step explanation:

To find the value of 10x^2 – 7x + 10, when x = 3, simply plug in the value of x in the expression and solve as follows:

10(3)^2 – 7(3) + 10

10(9) – 21 + 10

90 – 21 + 10

79

The value of 10x^2 – 7x + 10, when x = 3, is 79

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Find the area of EBCD using (a) and (b).
ioda

I hope this helps you

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What would be the third step in simplifying the expression 4 2 ÷ (2 · 9) + 5?
ludmilkaskok [199]
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3 years ago
Consider the question of whether the home team wins more than half of its games in the National Basketball Association. Suppose
spayn [35]

Answer:

0.0037 = 0.37% probability that the home team would win 65% or more of its games in a simple random sample of 80 games

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

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

The Z-score 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. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

The home team therefore wins 50% of its games

This means that p = 0.5

Determine the probability that the home team would win 65% or more of its games in a simple random sample of 80 games

Sample of 80 means that n = 80 and, by the Central Limit Theorem:

\mu = p = 0.65

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.5*0.5}{80}} = 0.0559

This probability is 1 subtracted by the pvalue of Z when X = 0.65. So

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

By the Central Limit Theorem

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

Z = \frac{0.65 - 0.5}{0.0559}

Z = 2.68

Z = 2.68 has a pvalue of 0.9963

1 - 0.9963 = 0.0037

0.0037 = 0.37% probability that the home team would win 65% or more of its games in a simple random sample of 80 games

7 0
2 years ago
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