The net of a solid figure is shown below:

Which of the following is a characteristic of a line?

navik [9.2K]

$\huge\rm\purple{\underline{Line:-}}$

➜ A line is a figure in geometry which has only length with no breadth in a two dimensional plane , and extended infinitely in opposite directions .

➜ A line may be of any length and breadth . An infinite number of combination of long, short , thick or thin lines can Accord to their application unify , divide , balance , or unbalance a pictorial area . This emotion dynamic is set up by lines measures .

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$\large\sf\orange{\underline{Characteristics\:of\:line:}}$

Line type : dotted , short dashed , long dashed and continuous line.
Line width : extra dark , thick , medium annd thin
Line quality : the quality of line depends largely upon the drawing medium

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5 0

2 years ago

In ΔVWX, the measure of ∠X=90°, WV = 17, VX = 15, and XW = 8. What ratio represents the sine of ∠W?

Dahasolnce [82]

Answer:

$Sin \ \angle W=\frac{15}{17}$

Step-by-step explanation:

-In a right triangle, the Sine of the base acute angle is usually given as:

$Sin \angle (base)=\frac{Opposite \ Length}{Hypotenuse}$

-In ΔVWX,, VX is the opposite and WV the hypotenuse.

-Therefore, sine of ∠Wis calculated as;

$Sin \ \angle W=\frac{Opp}{Hyp}\\\\=\frac{15}{17}$

Hence, sine of ∠W is given represented by the ratio $\frac{15}{17}$

7 0

3 years ago

Read 2 more answers

At least 96.00% of the data in any data set lie within how many standard deviations of the mean? Explain how you arrived at yo

zheka24 [161]

The answer assumes that the question is about the normal distribution.

Answer:

96% of the data in any data set normally distributed is 2.05 standard deviations above and below the mean.

Step-by-step explanation:

The key to solving this question is having into account that exists the standard normal distribution that permits obtaining any probability from any normally distributed data, doing the following transformation:

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

That is, in this case, we subtract a given value x from the population mean and then divide the result by the population standard deviation. This is a z-score, and this value is associated with the probability for a standard normal distribution, with a population mean = 0 and population standard deviation = 1.

Fortunately, for the standard normal distribution, there is associated a ubiquitous standard normal table for possible values of z and the corresponding probability. Then, knowing that the data are normally distributed and having both distribution parameters, namely, the population mean and population standard deviation, we can consult any standard normal table to find the probabilities for any data distributed following the normal distribution.

However, even without previously know the values of the normal parameters, the standard normal distribution can tell us how many standard deviations from the mean are 96.00% of the data for every normally distributed population.

<h3>Solving the question</h3>

Having all this information at hand, we know that the z-score value tells us how many standard deviations from the mean are the data normally distributed. As a result, we can determine how many standard deviations below and above the population mean represent the 96.00% of the cases for this normal distribution consulting a cumulative standard normal table from the mean.

If we divide 96.00/2 = 48, that is, 0.48, we need to find the z-score for this probability consulting a cumulative standard normal table from the mean. The values for a z-score for that probability is z=2.05, approximately. So, since the normal distribution is also symmetrical, those values are above and below the mean, that is, z =2.05 (above) and z=-2.05(below).

Thus, 96% of the data in any data set normally distributed is 2.05 standard deviations above and below the mean.

5 0

3 years ago

The distance between the points (12,9) and (0,4) is A) 14 units B) 13 units C) 15 units D) 16 units

Juliette [100K]

Answer:

Option B 13 units is correct.

Step-by-step explanation:

The formula used to find distance between 2 points is:

$d(P1,P2)=\sqrt{(x_{2} -x_{1})^2 + (y_{2} -y_{1})^2 }$