PLEASE EXPLAIN YOUR ANSWER

Solve by factoring: 2x2 - 5x - 12 = 0

Zepler [3.9K]

Step-by-step explanation:

$2 {x}^{2} - 5x - 12$

$2 {x}^{2} - 8x + 3x - 12$

$2x(x - 4) + 3(x - 4)$

$2x + 3 = 0 \: \: x - 4 = 0$

$x = \frac{ - 3}{2} \: \: x =4$

5 0

3 years ago

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The following data pairs represent the average temperature x (in degrees Fahrenheit) and electricity

elena55 [62]

Answer:

<u>The correct answer is C. r = 0 because is most likely the closest to the correlation coefficient of the data.</u>

Step-by-step explanation:

Using Excel, we captured the data provided for the 12 different homes for calculating the correlation coefficient manually, this way:

n = 12

∑x = 904

∑y = 2,169

∑xy = 167,532

∑x² = 69,552

∑y² = 404,615

r = [n *∑xy - (∑x * ∑y)]/[√(n * ∑x² - (∑x)²) * (n * ∑y² - (∑y)²)]

Replacing with the real values, we have:

r = [12 * 167,532 - (904 * 2,169)]/[√(12 * 69,552 - 904²) * (12 * 404,615 - 2,169²)]

r = [2'010,384 -1'960,776]/[√(834,624 - 817,216) * (4'855,380 - 4'704,561]

r = 49,608/√17,408 * 150,819

r = 49,608/ 51'239.215

r = 0.00097

<u>The correct answer is C. r = 0 because is most likely the closest to the correlation coefficient of the data.</u>

4 0

3 years ago

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I just need help at this point.

Greeley [361]

Answer:

Step-by-step explanation:you take the 740 and divide it by 40 to get the hourly wage then times that by the 32 and theirs your answer

4 0

3 years ago

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Find the mean, variance &a standard deviation of the binomial distribution with the given values of n and p.

MrMuchimi

A random variable following a binomial distribution over $n$ trials with success probability $p$ has PMF

$f_X(x)=\dbinom nxp^x(1-p)^{n-x}$

Because it's a proper probability distribution, you know that the sum of all the probabilities over the distribution's support must be 1, i.e.

$\displaystyle\sum_xf_X(x)=\sum_{x=0}^n\binom nxp^x(1-p)^{n-x}=1$

The mean is given by the expected value of the distribution,

$\mathbb E(X)=\displaystyle\sum_xf_X(x)=\sum_{x=0}^nx\binom nxp^x(1-p)^{n-x}$
$\mathbb E(X)=\displaystyle\sum_{x=1}^nx\frac{n!}{x!(n-x)!}p^x(1-p)^{n-x}$
$\mathbb E(X)=\displaystyle\sum_{x=1}^n\frac{n!}{(x-1)!(n-x)!}p^x(1-p)^{n-x}$
$\mathbb E(X)=\displaystyle np\sum_{x=1}^n\frac{(n-1)!}{(x-1)!((n-1)-(x-1))!}p^{x-1}(1-p)^{(n-1)-(x-1)}$
$\mathbb E(X)=\displaystyle np\sum_{x=0}^n\frac{(n-1)!}{x!((n-1)-x)!}p^x(1-p)^{(n-1)-x}$
$\mathbb E(X)=\displaystyle np\sum_{x=0}^n\binom{n-1}xp^x(1-p)^{(n-1)-x}$
$\mathbb E(X)=\displaystyle np\sum_{x=0}^{n-1}\binom{n-1}xp^x(1-p)^{(n-1)-x}$

The remaining sum has a summand which is the PMF of yet another binomial distribution with $n-1$ trials and the same success probability, so the sum is 1 and you're left with

$\mathbb E(x)=np=126\times0.27=34.02$

You can similarly derive the variance by computing $\mathbb V(X)=\mathbb E(X^2)-\mathbb E(X)^2$ , but I'll leave that as an exercise for you. You would find that $\mathbb V(X)=np(1-p)$ , so the variance here would be

$\mathbb V(X)=125\times0.27\times0.73=24.8346$

The standard deviation is just the square root of the variance, which is

$\sqrt{\mathbb V(X)}=\sqrt{24.3846}\approx4.9834$

7 0

3 years ago

100 divided by 32 will give brainliest

Paha777 [63]

Answer: 3.125

Step-by-step explanation:

5 0

3 years ago

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