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Ainat [17]
3 years ago
9

(7•7•7•7•7)•6•6•6•6•6•6. Write your answer using a exponent.

Mathematics
2 answers:
Zepler [3.9K]3 years ago
7 0

Answer:

<h2>7⁵ x 6⁶</h2>

Step-by-step explanation:

We have 5 7's and 6 6's.

I'm always happy to help :)

Mama L [17]3 years ago
3 0

Answer:

Step-by-step

In the exponent we write how many times the number is repeated.

7^{5} x 6^{6}

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Step-by-step explanation:

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(3 x (6 + 4) - 22] x 2 = ?
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16

Step-by-step explanation:

[3 x (6 + 4) - 22] x 2

[3 x 10 - 22] x 2

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8 x 2 = 16

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3 years ago
Rewrite this equation into slope-intercept form. State the slope and y-intercept.<br> -7x+9y=18
a_sh-v [17]

Answer:

9y = 18 + 7x

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A sample of 5 buttons is randomly selected and the following diameters are measured in inches. Give a point estimate for the pop
Helen [10]

Answer:

s^2 = \frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}

But we need to calculate the mean with the following formula:

\bar X = \frac{\sum_{i=1}^n X_I}{n}

And replacing we got:

\bar X = \frac{ 1.04+1.00+1.13+1.08+1.11}{5}= 1.072

And for the sample variance we have:

s^2 = \frac{(1.04-1.072)^2 +(1.00-1.072)^2 +(1.13-1.072)^2 +(1.08-1.072)^2 +(1.11-1.072)^2}{5-1}= 0.00277\ approx 0.003

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance \sigma^2

E(s^2) = \sigma^2

Step-by-step explanation:

For this case we have the following data:

1.04,1.00,1.13,1.08,1.11

And in order to estimate the population variance we can use the sample variance formula:

s^2 = \frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}

But we need to calculate the mean with the following formula:

\bar X = \frac{\sum_{i=1}^n X_I}{n}

And replacing we got:

\bar X = \frac{ 1.04+1.00+1.13+1.08+1.11}{5}= 1.072

And for the sample variance we have:

s^2 = \frac{(1.04-1.072)^2 +(1.00-1.072)^2 +(1.13-1.072)^2 +(1.08-1.072)^2 +(1.11-1.072)^2}{5-1}= 0.00277\ approx 0.003

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance \sigma^2

E(s^2) = \sigma^2

3 0
3 years ago
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