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PIT_PIT [208]
3 years ago
5

In this diagram, CD is the perpendicular bisected of AB. The two-column proof shows that AC is congruent to BC.

Mathematics
1 answer:
mezya [45]3 years ago
6 0
Yes hi ‍♂️ yes hi yes is ok bye ok enough fooling around it would be C.
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$20.40

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Please answer soon (45 Points)
Nataliya [291]

Answer:

Step-by-step explanation:

The answer is the first choice.

The maximum calories per week for the dog is 4900

One week is seven days which means:

maximum calorie/day = \frac{4900 calorie/day}{7 day}=700 calories/day

Thus the dog can have 700 or fewer calories per day

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3 years ago
Please help it due asap <br> Helppppppp
Leno4ka [110]

Answer:

x = 30°

2x = 60°

3x = 90°

Step-by-step explanation:

GBF = CBD (opposite angle)

; 2x+x+3x = 180° (Size of straight angle)

6x = 180

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substitution x in 2x ; 2×30 = 60°

substitution x in 3x ; 3×30 = 90°

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4 0
3 years ago
Bottles filled by a certain machine are supposed to contain 12 oz of liquid. In fact the fill volume is random with mean 12.01 o
stepan [7]

Answer:

27.43% probability that the mean volume of a random sample of 144 bottles is less than 12 oz.

Step-by-step explanation:

To solve this problem, it is important to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 12.01, \sigma = 0.2, n = 144, s = \frac{0.2}{\sqrt{144}} = 0.0167

What is the probability that the mean volume of a random sample of 144 bottles is less than 12 oz

This is the pvalue of Z when X = 12

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{12 - 12.01}{0.0167}

Z = -0.6

Z = -0.6 has a pvalue of 0.2743.

So there is a 27.43% probability that the mean volume of a random sample of 144 bottles is less than 12 oz.

4 0
3 years ago
The graph of g(x) is the graph of f(x) = x^2 shifted 4 units left, vertically streched by a factor of 3, then shifted 5 units up
Papessa [141]
I think it would be (x)=2x2
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4 years ago
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