In which of the following do you expect the correlation coefficient to be closest to 1?

Mathematics

1 answer:

Mashutka [201]3 years ago

4 0

Answer:

The answer is c

Step-by-step explanation:

Answer is c sorry not explanation

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What is the volume (in cubic units) of a sphere with a radius of 6 units? Assume that π = 3.14 and round your answer to the near

abruzzese [7]

Answer: 904.32 cubic units.

Step-by-step explanation:

The formula for a sphere's volume is V = $V = \frac{4}{3}\pi r^{3} \\$

Substitute pi for 3.14 and radius for 6. 6^3 = 216

$\\V = \frac{4}{3}\ (3.14)( 216) \\\\$

Multiply them together, the answer is 904.32 cubic units.

8 0

3 years ago

please can someone help me with this question? i will mark brainliest and i would also really appreciate it! :)

Sloan [31]

Answer:

y ≤ 3x- 1

Step-by-step explanation:

The line is solid, so your answer must have a ≤ or ≥ symbol. And the area below the line is shaded so you would also know you answer must have a ≤ or < symbol.

8 0

2 years ago

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In Applied Life Data Analysis (Wiley, 1982), Wayne Nelson presents the breakdown time of an insulating fluid between electrodes

ale4655 [162]

Answer:

The sample mean is $\bar{x}=14.371$ min.

The sample standard deviation is $\sigma = 18.889$ min.

Step-by-step explanation:

We have the following data set:

$\begin{array}{cccccccc}0.15&0.82&0.81&1.44&2.70&3.28&4.00&4.70\\4.96&6.49&7.25&8.03&8.40&12.15&31.89&32.47\\33.79&36.80&72.92&&&&&\end{array}$

The mean of a data set is commonly known as the average. You find the mean by taking the sum of all the data values and dividing that sum by the total number of data values.

The formula for the mean of a sample is

$\bar{x} = \frac{{\sum}x}{n}$

where, $n$ is the number of values in the data set.

$\bar{x}=\frac{0.15+0.82+0.81+1.44+2.7+3.28+4+4.7+4.96+6.49+7.25+8.03+8.4+12.15+31.89+32.47+33.79+36.80+72.92}{19}\\\\\bar{x}=14.371$

The standard deviation measures how close the set of data is to the mean value of the data set. If data set have high standard deviation than the values are spread out very much. If data set have small standard deviation the data points are very close to the mean.

To find standard deviation we use the following formula

$\sigma = \sqrt{ \frac{ \sum{\left(x_i - \overline{x}\right)^2 }}{n-1} }$