Can someone help me please

Factorise m2 - 10m + 24 =0

Finger [1]

Answer:

the answer is =》

$(m - 6)( m- 4)$

Step-by-step explanation:

let's solve :-

=》

${m}^{2} - 10m + 24$

=》

$m {}^{2} - 6 m - 4m + 24$

=》

$m(m - 6) - 4(m - 6)$

=》

$(m - 6)(m - 4)$

4 0

3 years ago

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An aquarium tank can hold 6300 liters of water. There are two pipes that can be used to fill the tank.The first pipe alone can f

liq [111]

Answer: it will take them 28 minutes to fill the tank.

Step-by-step explanation:

The first pipe alone can fill the tank in 84 minutes. This means that the rate at which the first pipe fills the tank per minute is 1/84

The second pipe can fill the tank in 42 minutes by itself. This means that the rate at which the second pipe fills the tank per minute is 1/42

If they work together, they would work simultaneously and their individual rates are additive. This means that their combined rate of filling the tank would be

1/84 + 1/42

Assuming it takes t hours for both pipes to fill the tank working together, the working rate per minute would be 1/t. Therefore,

1/84 + 1/42 = 1/t

3/84 = 1/t

t = 84/3

t = 28 minutes

6 0

4 years ago

Read 2 more answers

Solve for y: -5y + 6 = 16

Murrr4er [49]

Answer:

y= -2

Step-by-step explanation:

5 0

3 years ago

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Reduce 12/30 to lowest term

Simora [160]

Answer:

6/15

Step-by-step explanation:

Divide the numerator and the denominator by 2.

7 0

3 years ago

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The standard normal distribution is most completely described as a: A. distribution that exhibits zero skewness and no excess ku

Kaylis [27]

Answer:

A. distribution that exhibits zero skewness and no excess kurtosis.

Correct. We know that the skewness for a normal distribution is zero, since for any symmetric distributio we need to have a skewness near zero, since this measure represent the assymetry of the data.

And the will not have excess of kurtosis for this distribution since the kurtosis measures the extreme values and for this case in the normal distribution we don't expect the outliers with high frequency.

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".

And this distribution is described by two parameters. The first one is the mean given by $\mu$ and is a measure of central tendency. And the seconde parameter is the deviation given by $\sigma$ .

And with this two parameters we say that if X follows a normal distribution then:

$X \sim N(\mu, \sigma)$

Let's analyze one by one the options:

A. distribution that exhibits zero skewness and no excess kurtosis.

Correct. We know that the skewness for a normal distribution is zero, since for any symmetric distributio we need to have a skewness near zero, since this measure represent the assymetry of the data.

And the will not have excess of kurtosis for this distribution since the kurtosis measures the extreme values and for this case in the normal distribution we don't expect the outliers with high frequency.

B. normal distribution with a mean of zero and a standard deviation of one.

False. For this case this distribution is a particular case of the normal distribution and is known as the normal standard distribution but the mean is not always equal to 0 and the deviation =1 for any normal distributon.

C. symmetrical distribution with a mean equal to its median.

False. This statement is true but we don't have the mode incoroporate on this definition. Since in the normal distribution we have:

$Mean = Median = Mode$

So for this reason is not the most complete answer for this case.

5 0

3 years ago