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son4ous [18]
2 years ago
15

Which scatterplot shows a nonlinear association?

Mathematics
1 answer:
Lubov Fominskaja [6]2 years ago
5 0

Answer:

B

Step-by-step explanation:

B shows a parabola, which is a quadratic equation, not a linear one.

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Please Help Me! Look at the Image!
ozzi

Answer:

y=-2x+1

Step-by-step explanation:

Just look at photo dap

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Liana is making muffins.she uses 2 cups to make 12 muffins. How much flour is needed for each muffin
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Which fraction is larger 2/3 or 3/4 and find the common denominator
tangare [24]

Answer:

3/4

Step-by-step explanation:

2/3=8/12

3/4=9/12

Common denominator: 12

larger fraction: 3/4

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a box of cereal contains 23.4 ounces. It cost $5.49. What is the cost,to the nearest cent, of the cereal per ounce.
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3 years ago
Construct the discrete probability distribution for the random variable described. Express the probabilities as simplified fract
lisov135 [29]

Answer:

P(X = 0) = 0.03125

P(X = 1) = 0.15625

P(X = 2) = 0.3125

P(X = 3) = 0.3125

P(X = 4) = 0.15625

P(X = 5) = 0.03125

Step-by-step explanation:

For each toss, there are only two possible outcomes. Either it is tails, or it is not. The probability of a toss resulting in tails is independent of any other toss, which means that the binomial probability distribution is used to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

Fair coin:

Equally as likely to be heads or tails, so p = 0.5

5 tosses:

This means that n = 5

Probability distribution:

Probability of each outcome, so:

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{5,0}.(0.5)^{0}.(0.5)^{5} = 0.03125

P(X = 1) = C_{5,1}.(0.5)^{1}.(0.5)^{4} = 0.15625

P(X = 2) = C_{5,2}.(0.5)^{2}.(0.5)^{3} = 0.3125

P(X = 3) = C_{5,3}.(0.5)^{3}.(0.5)^{2} = 0.3125

P(X = 4) = C_{5,4}.(0.5)^{4}.(0.5)^{1} = 0.15625

P(X = 5) = C_{5,5}.(0.5)^{5}.(0.5)^{0} = 0.03125

5 0
2 years ago
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