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Westkost [7]
4 years ago
8

How does the position of the decimal point in a quotient as you divide by increasing powers of 10

Mathematics
1 answer:
Digiron [165]4 years ago
4 0
The value decimal point is changing going to the right as you divide a number by 10. For example => 2000.3 / 10 notice the decimal point => 200.013, the value of decimal numbers increases as the value of whole number decreases.Let’s divide again => 200.013 / 10 => 20.0013 , now we already have 4 digits in our decimals. So, simply as we divide the given number by 10, the decimal point moves to the left making the value of whole number decreases and making the number of digits of decimal increase.
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Im pretty sure the answer is A
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3 years ago
In a study relating the degree of warping, in mm, of a copper plate (y) to temperature in °C (x), the following summary statisti
kipiarov [429]

Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation Y=mx +b, where y is the dependent variable, x the independent variable, m the slope and b the intercept.

For this case we have the following info given:

\sum_{i=1}^n (x_i -\bar x)^2 =98775

\sum_{i=1}^n (y_i -\bar y)^2 =19.4

\bar x =26.36

\bar y =0.5188

n= 40  represent the sample size

\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y) =796.94

The total sum of squares is given by this formula:

SST= \sum_{i=1}^n (y_i -\bar y)^2 =19.4

And from the formulas for a simple regression, we need to calculate the slope for the regression like this:

m=\frac{\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)}{\sum_{i=1}^n (x_i -\bar x)^2}

And if we replace the values given we have:

m=\frac{796.94}{98775}=0.008068

We have another useful equation in order to find the sum of squares for the regression, given by:

SSR=m* \sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)=0.008068*796.94=6.430

And we know this equivalence:

SST= SSR+SSE

And solving for the sum of squares for the error we have:

SSE=SST-SSR=19.4-6.430=12.97

So then we have the final solutions:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

6 0
3 years ago
Tony is trying to find the solution of the system 2x - 4y +12 using elimination 3x + 4y = 48 He wrote these steps to solve the p
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Answer: Solution: (12, 3)

Step-by-step explanation:

2x - 4y = 12

3x + 4y = 48

Add both equations

5x = 60

Divide both sides by 5

x = 12

We can use the value of x to find y

3x + 4y = 48

3 (12) + 4y = 48

36 + 4y = 48

Subtract 36 from both sides

4y = 12

Divide both sides by 4

y = 3

Solution: (12, 3)

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The points plotted below are on the graph of a polynomial. Some of the roots to this polynomial are integers. Which of the follo
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Answer:

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Step-by-step explanation:

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Please help me..please
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