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Alisiya [41]
2 years ago
5

B. Mason put sticky notes on some pages of his math book. The page numbers for this sequence 3, 5, 8, 13, 21,34, ... Describe th

e rule for the sequence. I Find the next two terms of the sequence. Show your work.​
Mathematics
2 answers:
katrin [286]2 years ago
6 0

Answer:

The next two terms are 55 and 89

Step-by-step explanation:

This is an example of the Fibonacci Sequence: The sum of the previous two numbers equals the next number.

You can see that :

  • 3 + 5 = 8
  • 5 + 8 = 13
  • 8 + 13 = 21
  • 13 + 21 = 24

Rule: the sum of the previous two numbers, equals the next number.

Solve:

  • 3, 5, 8, 13, 21, 34, (21 + 34), (34 + 21 + 34)
  • 3, 5, 8, 13, 21, 34, 55, 89

The next two terms are 55 and 89

-Chetan K

Mademuasel [1]2 years ago
6 0

Step-by-step explanation:

the next 2 term is 55 and 89

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Todd Holland from NY grows pumpkins. He studied his past records carefully and concluded that his biggest pumpkins are distribut
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Answer:

P(X>1000)

And the best way to solve this problem is using the normal standard distribution and the z score given by:

z=\frac{x-\mu}{\sigma}

If we apply this formula to our probability we got this:

P(X>1000)=P(\frac{X-\mu}{\sigma}>\frac{1000-\mu}{\sigma})=P(Z>\frac{1000-950}{50})=P(z>1)

And we can find this probability using the complement rule and the normal standard table and we got:

P(z>1)=1-P(z

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution problem

Let X the random variable that represent the variable of interest of a population, and for this case we know the distribution for X is given by:

X \sim N(950,50)  

Where \mu=950 and \sigma=50

We are interested on this probability

P(X>1000)

And the best way to solve this problem is using the normal standard distribution and the z score given by:

z=\frac{x-\mu}{\sigma}

If we apply this formula to our probability we got this:

P(X>1000)=P(\frac{X-\mu}{\sigma}>\frac{1000-\mu}{\sigma})=P(Z>\frac{1000-950}{50})=P(z>1)

And we can find this probability using the complement rule and the normal standard table and we got:

P(z>1)=1-P(z

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Answer:

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