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svetlana [45]
3 years ago
15

Find MN , i need it please and thanks

Mathematics
1 answer:
jeka943 years ago
4 0
I think it’s 6
I did 32-26 and got it
That’s all I got
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(3, -2), slope - 1/6
Reika [66]
-2=-1/6(3)+b 
-2=-0.5+b
-1.5+b
y=-1/6 -0.5
7 0
3 years ago
How do you write 5,621 divided by 23 word problem
Alona [7]
Five thousand six hundred and twenty one divided by twenty three equals a repeated number.
6 0
3 years ago
Read 2 more answers
Which is the equation of the line with slope 0 passing through the point (-3,-1)?
madreJ [45]

When a line has a slope of zero it means that it is horizontal. This means that all the x values have the same y values. In this case it means that the y value is always -1.

The equation for this line is...

y = -1

Hope this helped!

~Just a girl in love with Shawn Mendes

3 0
3 years ago
Read 2 more answers
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
1. find the balance after one year if you deposit all the money into an account that pays $2.50 in simple interest each month (t
Naddika [18.5K]

1. Balance after 1 year with simple interest= 600 + (2.5 x 12) = 600 + 30 = $630

2. Balance after 1 year with compounded interest = P ( 1 + \frac{r}{n})^{nt}

= 600 ( 1 + \frac{0.05}{12})^{12}= 600 (1.0511) = $630.66 = approx. $630

6 0
3 years ago
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