Which best describes the relationship between the two triangles below?Triangle M N L. Angle M is 51 degrees and angle L is 36 degrees. Triangle F H G. Angle F is 51 degrees and angle G is 36 degrees.
Triangle M L N is similar to Triangle F G H because of the third angle theorem, Angle M is congruent to angle F, Angle L is congruent to angle G, and Angle N is congruent to angle H.
Triangle M L N may or may not be similar to Triangle F G H because the third angle is unknown.
Triangle M L N is similar to Triangle F G H because of the angle-angle criterion, Angle M is similar to angle F, Angle L is similar to angle G, and Angle N is similar to angle H.
Triangle M L N may or may not be similar to Triangle F G H because the side lengths are unknown.

Answer: 203, 204, 205

Step-by-step explanation:

Consecutive numbers are numbers that are right next to each other. An example would be 1,2,3 or 67,68,69. Since this problem is asking for three consecutive numbers where the sum is equal to 612, we need to find the numbers that will be greater than 200.

Since we know that the sum is 612, we know that the numbers will be in the 2 hundreds. All we need to do is find 3 numbers that equal to 12.

3+4+5=12

Now that we have the three numbers, let's add 200.

203+204+205=612

Therefore, the three numbers are 203, 204, 205.

Answer: 203, 204, 205

Step-by-step explanation:

Let's say the number is x.

So the three consecutive numbers are: x, x + 1, and x+ 2

3x + 3 = 612

3x = 609

x = 203

Plug in x.

203, 204, and 205

Answer:

5.47% of the total variation between the two variables can be explained by the regression line.

Step-by-step explanation:

Given :

R value = 0.234

The R value is the correlation Coefficient ; which gives the type and level of correlation between two variables.

However, to Obtian the percentage variation which can be explained by by the regression line, we have to obtain the Coefficient of determination, R².

R² value is Obtained by taking the squared of the correlation Coefficient

Hence,

R² = 0.234² = 0.054756

R² = 0.05476 * 100% = 5.4756%

Hence, R² = 5.48%

This is interpreted as ; 5.47% of the total variation between the two variables can be explained by the regression line.

Answer:

12.5

Step-by-step explanation:

If the number of workers injured in each accident is independent of the number of accidents that occur, then the expected number of workers injured in a week equals the expected number of accidents per week times the expected number of workers injured in each accident.

But the expected number of workers injured in each accident is precisely the average or mean, so

Expected number of workers injured in a week = 5*2.5 = 12.5.

Or in other words, in 10 weeks there will probably be 125 workers injured.

Final answer:

The expected number of workers injured in a week at the industrial plant is 12.5, calculated by multiplying the expected number of accidents per week (5) by the expected number of workers injured per accident (2.5).

Explanation:

The expected number of accidents at an industrial plant per week is given as 5 and the mean number of workers injured per accident is given as 2.5. As the number of workers injured per accident is stated to be independent from the number of accidents that occur, we can merely multiply the two expected values to find the overall expected value of workers injured in a week.

So, Expected number of workers injured per week = Expected number of accidents per week * Expected number of workers injured per accident = 5 * 2.5 = 12.5.

This implies that, on average, we can expect 12.5 workers to be injured at the industrial plant per week.

Learn more about Expectation of Random Variables here:

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Answer:

Um i have no idea sorry i couldnt help

Step-by-step explanation:

Answer:

38.9

Step-by-step explanation: