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3 years ago

I need help with this please help!!!!!

Mathematics

1 answer:

Ann [662]3 years ago

4 0

Answer:

88.53

Step-by-step explanation:

put n=7 and solve it

the answer will be 88.5271......

round off to nearest hundredth so 88.53

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NEED IT FAST PLEASE Which is the graph of the linear equation x – 2y = 6? On a coordinate plane, a line goes through points (neg

koban [17]

Y= (x-6)/2. Plug that for of first equation into;

Answer:

Math is fun dot com. All one word. (With .)

For other straight lines, I’m assuming you are supposed to graph the intersections, just use the two point form to get the rise and run. The rise / run is the slope. Usually called ‘m’ in formula form. Plug each Straight line formula into the Same web page above and it will graph the line for you. Be sure each line is in the [Y = mX+b ]

Format. Y is the up, X is the over, m is the slope. (Change in Y divided by change in X) (like stairs), and ‘b’ is the Y intercept. That means where the line crosses the Y (up) axis.

Step-by-step explanation:

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3 years ago

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I have to solve each problem and round to the nearest tenth.

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Answer:

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Step-by-step explanation:

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3 years ago

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 $\sigma^2$

$E(s^2) = \sigma^2$

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3 years ago

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2 years ago

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Anni [7]

Answer:

perhaps 60%?

Step-by-step explanation:

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3 years ago