Write each expression using fewer terms. Show your work and/or explain your reasoning.
a) [tex]\frac{3}{4}-\frac{1}{4}(8x-16)[/tex]

Answer:-12 - 15x

Step-by-step explanation: multiply both numbers in the parentheses by 3 so 3(-4) and 3(-5) then the X stays with the 5

Answer:

You have 15 friends.

Step-by-step explanation

Simplify 20 down to where it cannot go any further (meaning no decimals) 20/2= 10 10/2=5, then multiply 5 by 3, and you get 15.

Answer:

P = 36 inches

Step-by-step explanation:

To find the perimeter of the triangle, add up all the sides.

P = s1 + s2+ s3

P = 13+13+10

P = 36 inches

Answer: The perimeter of the triangle is 36 inches. The correct option is d

Step-by-step explanation:

The perimeter of a triangle is calculated by adding the length of all sides of the triangle. This is an isosceles triangle. This means that the length of two sides out of three of the shape have the same length.

In such a triangle, the two equal sides are called the arms. The other side, represented usually as the lowermost, is called the base. The formula to find the perimeter of any isosceles triangle is-

Perimeter=(arm length)*2+base length

Therefore-

Perimeter=(13 inches)*2+10inches=36

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The more simulations you run, the closer the experimental probabilities will be to the theoretical probabilities.

To calculate the experimental probability, we can use a simulation where we simulate multiple sets of three games and count the number of times the desired outcomes occur.

Here's how we can calculate the experimental probability for each case:

P(1 win and 2 losses):

Simulate a large number of sets of three games (e.g., 10,000).

For each set, randomly assign a win or a loss for each game based on the average of one win to every one loss.

Count the number of sets where there is exactly one win and two losses.

Divide the count by the total number of sets (10,000) to get the experimental probability.

P(three losses):

Simulate a large number of sets of three games (e.g., 10,000).

For each set, randomly assign a win or a loss for each game based on the average of one win to every one loss.

Count the number of sets where there are three losses.

Divide the count by the total number of sets (10,000) to get the experimental probability.

Note: The above method assumes that the probability of winning or losing each game is equal (i.e., 0.5 for each).

Here's an example of how the calculations can be performed using a simulation:

P(1 win and 2 losses):

Simulate 10,000 sets of three games.

Count the number of sets with exactly one win and two losses.

Let's say the count is 4,100.

Experimental probability = 4,100 / 10,000 = 0.41

P(three losses):

Simulate 10,000 sets of three games.

Count the number of sets with three losses.

Let's say the count is 5,200.

Experimental probability = 5,200 / 10,000 = 0.52

Remember, the experimental probabilities obtained through simulations may vary slightly due to the random nature of the simulation.

The more simulations you run, the closer the experimental probabilities will be to the theoretical probabilities.

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Answer:The data collected using length measurements can be represented using a graph called line plots which we can make interpretations.

Step-by-step explanation:

Answer:

he data collected using length measurements can be represented using a graph called line plots which we can make interpretations.

Step-by-step explanation: