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julsineya [31]
3 years ago
13

Which scatter plot most likely has a line of best fit represented by y = 3x + 1 ?

Mathematics
1 answer:
mylen [45]3 years ago
8 0

Answer:

i need help too

Step-by-step explanation:

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kifflom [539]
1: positive
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3 0
3 years ago
If the die were to be rolled 6000 times, would we expect to obtain exactly 1000 '2's? explain your answer.
ludmilkaskok [199]
The probability of that occurring is 0%. There are 6 sides in a typical dice, which means the probability of rolling a 2 is 1/6th. (1/6)^1000 will give you the probability of rolling a 2 exactly 1000 times. (1/6)^1000 equates to 0%.
7 0
2 years ago
Sandra is making decorations for the school dance out of construction paper. Each decoration uses 223 2 2 3 sheets of paper. San
scoundrel [369]

Answer:

Step-by-step explanation:

CACA POOP

7 0
3 years ago
How do you solve for "r" in the literal equation "I=Prt"
Mrac [35]
R=I/Pt
hopefully this helps
8 0
2 years ago
The body temperatures of adults are normally distributed with a mean of 98.6degrees° F and a standard deviation of 0.60degrees°
Schach [20]

Answer:

97.72% probability that their mean body temperature is greater than 98.4degrees° F.

Step-by-step explanation:

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

Normal probability distribution:

Problems of normally distributed samples 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 random variable X, with mean \mu and standard deviation \sigma, the sample means with size n of at least 30 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 = 98.6, \sigma = 0.6, n = 36, s = \frac{0.6}{\sqrt{36}} = 0.1

If 36 adults are randomly​ selected, find the probability that their mean body temperature is greater than 98.4degrees° F.

This is 1 subtracted by the pvalue of Z when X = 98.4. So

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

By the Central Limit Theorem

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

Z = \frac{98.4 - 98.6}{0.1}

Z = -2

Z = -2 has a pvalue of 0.0228

1 - 0.0228 = 0.9772

97.72% probability that their mean body temperature is greater than 98.4degrees° F.

6 0
3 years ago
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