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rosijanka [135]
3 years ago
15

What words don’t describe? Super easy question!!!❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️

Mathematics
1 answer:
Mazyrski [523]3 years ago
4 0

Answer:

1 - b

2 - d

3 - d

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20. solve the equation by completing the square. round to the nearest hundredth if necessary. x^2+10x=18 a. -11.56, 1.56 b.11.56
larisa86 [58]

The answer was A but  i am found

1.557, -11.557

and hope that helps you

8 0
3 years ago
There are about 320 million people living in the United States. Of these, how many would you predict wear corrective lenses
tiny-mole [99]

Answer:

240 million

Step-by-step explanation:

Google said that three out of four people wear corrective lenses which is also 75%. So whats 75% out of 320 million? <u>Half of 320 million is 160 million</u>. <u>Half of 160 million is 80 million, 160 million plus 80 million is </u><u>240 million.</u>

8 0
3 years ago
Read 2 more answers
How much will Paul save per year
yan [13]

Answer:

paul will spend 33

Step-by-step explanation:

66-43

6 0
3 years ago
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} }

The mean of a sample is  \bar{x}=14.371.

Create the below table.

Find the sum of numbers in the last column to get.

\sum{\left(x_i - \overline{X}\right)^2} = 6422.0982

\sigma = \sqrt{ \frac{ \sum{\left(x_i - \overline{x}\right)^2 }}{n-1} }       = \sqrt{ \frac{ 6422.0982 }{ 19 - 1} } \approx 18.889

7 0
3 years ago
Consider the following hypothesis test: H0: μ1 - μ2 = 0 Ha: μ1 - μ2 ≠ 0 There are two independent samples taken from the two pop
nlexa [21]

Answer:

The value of the test statistic is z = 1.78

Step-by-step explanation:

Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.

Central Limit Theorem

The Central Limit Theorem establishes 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}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Subtraction between normal variables:

When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

Sample 1:

\mu_1 = 110, s_1 = \frac{7.2}{\sqrt{81}} = 0.8

Sample 2:

\mu_2 = 108, s_2 = \frac{6.3}{\sqrt{64}} = 0.7875

The test statistic is:

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

In which X is the sample mean, \mu is the value tested at the null hypothesis, and s is the standard error.

0 is tested at the null hypothesis:

This means that \mu = 0

Distribution of the difference:

X = \mu_1 - \mu_2 = 110 - 108 = 2

s = \sqrt{s_1^2+s_2^2} = \sqrt{0.8^2+0.7875^2} = 1.1226

What is the value of the test statistic?

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

z = \frac{2 - 0}{1.1226}

z = 1.78

The value of the test statistic is z = 1.78

5 0
3 years ago
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