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Kazeer [188]
3 years ago
11

Explain how comparing 645 and 738 is different from comparing 645 and 649

Mathematics
1 answer:
Phantasy [73]3 years ago
6 0
Its different because when u add 645 and 738 it equals 1,382 and when u add  645 and 649 it equals 1,294 so 1,382 is the greater number and its different from 1,294<span />
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Which expression is equivalent to –2(5x – 0.75)?
Zinaida [17]

Answer:

5(5x - 0.34

Step-by-step explanation:

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Please help me out with this problem!!!
Ronch [10]

Answer:

y = 3x - 2

Step-by-step explanation:

The equation is linear and expressed in slope- intercept form

y = mx + c ( m is the slope and c the y- intercept )

Given (0, - 2 ) then c = - 2

Calculate the multiplier using the slope formula

m = (y₂ - y₁ ) / (x₂ - x₁ )

with (x₁, y₁ ) = (0, - 2) and (x₂, y₂ ) = (1,1) ← 2 ordered pairs from the table

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6 0
3 years ago
2 to 36 to 64 what did Tina do wrong
pantera1 [17]
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7 0
3 years ago
suppose you performed a regression analysis. you were given four observations of the target at [1.0, 1.5, 2.8, 3.7], and you pre
Arlecino [84]

Suppose you performed a regression analysis. The mse for this scenario is 0.105

Regression is a statistical method used in finance, making an investment, and different disciplines that attempt to determine the electricity and man or woman of the relationship between one established variable (commonly denoted through Y) and a sequence of different variables (called independent variables).

We are able to say that age and peak can be described through the usage of a linear regression version. because someone's peak will increase as age will increase, they have got a linear courting. Regression fashions are commonly used as statistical proof of claims regarding regular statistics.

"Regression" comes from "regress" which in turn comes from Latin "regresses" - to head returned (to something). In that feel, regression is the approach that permits "to head again" from messy, hard-to-interpret data, to a clearer and more significant version.

y ypred (y-ypred)^2

1 1.1 0.01

1.5 1.3 0.04

2.8 3.2 0.16

3.7 3.7 0

The error sum of the square is given by

ESS = (y- )

ESS=0.21

The mean square error is given by

ESS MSE = ESS/dfe

MSE = \frac{0.21}{2}

MSE = 0.105

Learn more about regression here brainly.com/question/26755306

#SPJ4

6 0
2 years ago
Can you please help me
kvv77 [185]

Answer:

7. 7.1+5.4+2.9=15.7

10.3+5.4=15.7

8. 373.4 - 152.9 = 220.5

373.4 - 153 = 220.4

220.4 - 0.1 = 220.5

9. 18.25 + 7.99 + 4.75 = 30.99

10. 1.05 + 3 + 4.28 + .95 = 9.28

11. 302.504

12 50.5

5 0
3 years ago
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