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fomenos
4 years ago
6

What is s10 for 1 + 2 + 4 + 8+... 256 511 1023 2047

Mathematics
1 answer:
andrew11 [14]4 years ago
8 0

Answer:

1023

Step-by-step explanation:

S_n = \dfrac{a(1 - r^n)}{1 - r}

a = first term

r = common ratio

n = number of terms

Here we have

a = 1

r = 2

n = 10

S_{10} = \dfrac{1(1 - 2^{10})}{1 - 2}

S_{10} = \dfrac{1 - 1024}{-1}

S_{10} = \dfrac{-1023}{-1}

S_{10} = 1023

Of course, since 10 is not such a large number of terms, you can simply do this:

1 + 2 + 4 + 8 + 16 + 32 + 64 + 128 + 256 + 512 = 1023

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Answer:

(1) The cost formula is: <em>y</em> = $19,050 + $12·<em>x</em><em>.</em>

(2) The cost of moving materials if 340 moves are made is $23,130.

(3) 82.81% of the variability in moving cost is explained by the number of moves.

Step-by-step explanation:

The computer output for the regression analysis of 80 data points is as follows:

Intercept:  $19,050

Slope: 12

Coefficient of correlation: 0.91

Standard error:  $220

(1)

The general formula of regression equation is:

<em>y</em> = <em>a</em> + <em>b</em>·<em>x</em>

Here,

<em>a</em> = intercept

<em>b</em> = slope

The cost formula is:

<em>y</em> = $19,050 + $12·<em>x</em>

(2)

Predict the cost of moving materials if 340 moves are made as follows:

y = 19050 + 12\cdot x\\=19050+12\times 340\\=19050+4080\\=23130

Thus, the cost of moving materials if 340 moves are made is $23,130.

(3)

The coefficient of determination R² specifies the percentage of the variance in the dependent variable (Y) that is forecasted or explained by linear regression and the forecaster variable (X, also recognized as the independent-variable).

The coefficient of determination R² can be computed by squaring the correlation coefficient value.

R^{2}=(r)^{2}=(0.91)^{2}=0.8281

Thus, 82.81% of the variability in moving cost is explained by the number of moves.

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