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2 years ago

The diagrams show a quadrilateral ABCD. Is AB parallel to DC? you must give your reasoning.

Mathematics

1 answer:

Sati [7]2 years ago

6 0

Answer:

yes AB is parallel to DC

Step-by-step explanation:

because AB and DC are lines which will never touch each other even if they go a long way they will not touch each other

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Janie walks 1 mile to get to a running track.she then runs at a speed of 3.5 miles per hour.Which linear models represents the t

MrMuchimi

Answer:

d = 3.5t + 1

Step-by-step explanation:

The linear function would have to multiply the speed she runs at the track by the number of hours that she spent running. Then it should add this amount to the 1 mile that she walked to get to the track. If we use the variable d as the total distance that she ran and walked, and the variable t to represent time then we would create the following linear function/model.

d = 3.5t + 1

3 0

3 years ago

I NEED HELP WITH THIS ASAP! ITS DUE IN 20 MINS

amm1812

Answer:

Step-by-step explanation:

I pretty sure it b can u plz mark as brlainlest sorry if wrong try b

3 0

2 years ago

Find the value of x to the nearest tenth. 10.0 6.0 9.3 4.0

SVETLANKA909090 [29]

Suppose that the value of other ratio is equal to 6/3 then,

20/3x-8 = 6/3
18x-48 = 60
18x = 60+48
18x = 108
x = 6

7 0

3 years ago

Read 2 more answers

Rewrite the expression with rational exponents as a radical expression.

SpyIntel [72]

I think it’s the last one but I’m not sure. Let me know if you get it right.

3 0

1 year ago

Suppose the weights of Farmer Carl's potatoes are normally distributed with a mean of 8.0 ounces and a standard deviation of 1.1

svet-max [94.6K]

Answer:

a) 0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

b) 0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be 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 normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .