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Nat2105 [25]
3 years ago
7

David rolls a fair dice 240 times. How many times would David expect to roll a three?

Mathematics
1 answer:
jolli1 [7]3 years ago
4 0

Answer:

40

Step-by-step explanation:

There are 6 numbers on an dice (1-6) Divide 240 by 6 and the reasonable amount of times to roll a 3 is 40 time

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Miles wanted to spend his allowance on computer games. He saved $65.00. How many games could he buy if each game costs $17.99
Llana [10]

65/17.99 =3.61

The answer would be 3 games because you can't buy .61 of a game.


8 0
3 years ago
Read 2 more answers
Y = x – 6
zhenek [66]
-4-6= -10
-10 = Y
-4 = X
Therefore the answer is (-4,-10) which isn’t on the options
8 0
2 years ago
Triangle M is also a scaled copy of S. The scale
kozerog [31]

Answer:

I believe it’s 2/3

Step-by-step explanation:

If s to m is 3/2 then m to a should be 2/3 not 100% sure though

4 0
3 years ago
A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The s
Fofino [41]

Answer:

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use 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}}

In this question, we have that:

\mu = 270, \sigma = 90, n = 18, s = \frac{90}{\sqrt{18}} = 21.2

What is the probability that 18 randomly selected bulbs would have an average life of no more than 260 days?

This is the pvalue of Z when X = 260. So

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

By the Central Limit Theorem

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

Z = \frac{260 - 270}{21.2}

Z = -0.47

Z = -0.47 has a pvalue of 0.3192.

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

5 0
2 years ago
Written as a simplified polynomial in standard form, what is the result when
grin007 [14]
The simplified form is 6x-6
5 0
3 years ago
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