Find the LCM (least common multiple) of 13 and 52. LCM =

Mathematics

2 answers:

photoshop1234 [79]4 years ago

4 0

52, because 52 is a multiple of 13 (13*4 = 52)

defon4 years ago

3 0

Answer:

The answer is 52

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A transformation T : (x, y) → (x + 3, y + 1). Find the preimage of the point (4, 3) under the given transformation. (7, 4) (1, 2

motikmotik

Answer:

(1, 2)

Step-by-step explanation:

Remember that the final shape and position of a figure after a transformation is called the image, and the original shape and position of the figure is the pre-image.

In our case, our figure is just a point. We know that after the transformation T : (x, y) → (x + 3, y + 1), our image has coordinates (4, 3).

The transformation rule T : (x, y) → (x + 3, y + 1) means that we add 3 to the x-coordinate and add 1 to the y-coordinate of our pre-image. Now to find the pre-image of our point, we just need to reverse those operations; in other words, we will subtract 3 from the x-coordinate and subtract 1 from the y-coordinate.

So, our rule to find the pre-image of the point (4, 3) is:

T : (x, y) → (x - 3, y - 1)

We know that the x-coordinate of our image is 4 and its y-coordinate is 3.

Replacing values:

(4 - 3, 3 - 1)

(1, 2)

We can conclude that our pre-image is the point (1, 2).

6 0

3 years ago

Making handcrafted pottery usually takes two major steps:wheel throwing and firing. The time of wheel throwing and thetime of fi

levacccp [35]

Answer:

a) $P(R$

And we can find this probability using the normal standard table or excel and we got:

$P(z$

b) $P(R>110)=P(\frac{R-\mu}{\sigma}>\frac{110-\mu}{\sigma})=P(Z>\frac{110-100}{3.606})=P(Z>2.774)$

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

$P(z>2.774)=1-P(Z$

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".

Part a

Let X the random variable that represent the time for the step 1 and Y the time for the step 2, we define the random variable R= X+Y for the total time and the distribution for R assuming independence between X and Y is:

$R \sim N(40+60 = 100,\sqrt{2^2 +3^2}= 3.606 s)$