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tekilochka [14]
3 years ago
14

Dan is going to fix dinner.He turns on the oven.The graph shows the temperature over time.Why does the graph not start at zero

Mathematics
1 answer:
morpeh [17]3 years ago
6 0
Because there is the initial temperature of the oven before it was turned on<span />
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A number cube with the numbers 1 through 6 is rolled. What is the probability of the number cube showing a 4 or a number less th
Sonja [21]

Answer:

Step-by-step explanation:

The probability is

P

(

A

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=

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3

Explanation:

To calculate the probability you have to count the number of all possible results

|

Ω

|

and the number of results that fulfill the given condition

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A

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.

In this case

Ω

=

{

1

,

2

,

3

,

4

,

5

,

6

}

Thereare 6 possible result of a dice toss. So

|

Ω

|

=

6

The given condition is "the result is divisible by

3

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A

=

{

3

,

6

}

- those are the only numbers divisible by

3

, so

|

A

|

=

2

.

Finally to calculate the probability we have to divide

|

A

|

by

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Ω

|

.

P

(

A

)

=

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A

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|

Ω

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3

Note The probability is never larger than

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4 0
3 years ago
Read 2 more answers
Josiah skateboards from his house to school 3 miles away. It takes home 36 minutes. If Josiah’s speed, in miles per minute, is c
arlik [135]

c constant of proportionality is 12

Step-by-step explanation:

36÷3= 12

5 0
3 years ago
How many solutions does the following equation have?<br> -7x-10-15x=-22x+83
Vlada [557]

Answer:

-22x-10=-22x+83

=-22x-10=-22x+83

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3 years ago
Please help i dont get it and its for a grade! :(
Tju [1.3M]

Answer:

y=-4x+5

Step-by-step explanation:

7 0
3 years ago
A sample size 25 is picked up at random from a population which is normally
Margarita [4]

Answer:

a) P(X < 99) = 0.2033.

b) P(98 < X < 100) = 0.4525

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 z-score 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 p-value, 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.

Mean of 100 and variance of 36.

This means that \mu = 100, \sigma = \sqrt{36} = 6

Sample of 25:

This means that n = 25, s = \frac{6}{\sqrt{25}} = 1.2

(a) P(X<99)

This is the pvalue of Z when X = 99. So

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

By the Central Limit Theorem

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

Z = \frac{99 - 100}{1.2}

Z = -0.83

Z = -0.83 has a pvalue of 0.2033. So

P(X < 99) = 0.2033.

b) P(98 < X < 100)

This is the pvalue of Z when X = 100 subtracted by the pvalue of Z when X = 98. So

X = 100

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

Z = \frac{100 - 100}{1.2}

Z = 0

Z = 0 has a pvalue of 0.5

X = 98

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

Z = \frac{98 - 100}{1.2}

Z = -1.67

Z = -1.67 has a pvalue of 0.0475

0.5 - 0.0475 = 0.4525

So

P(98 < X < 100) = 0.4525

6 0
3 years ago
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