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inysia [295]
3 years ago
6

The best description of a dilation of a figure is?

Mathematics
1 answer:
klemol [59]3 years ago
8 0

Answer:

an enlargement or a reduction of the figure

a slide of the figure

a turning of the figure about some fixed point

a mirror image of the figure

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(8.75-2.16)÷7.1+(4.5+1.3)÷4.3
kirill [66]

Answer:

2.27700622339

Step-by-step explanation:

Calculated your welcome

7 0
3 years ago
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A school is buying 35 new computers. If the price of each computer is $1,099,
dolphi86 [110]

Answer:

$38,465

Step-by-step explanation:

35 x 1,099 = 38,465

6 0
3 years ago
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A. X=3 m<br> B. X=5 m<br> C. X=6 m<br> D. X=9 m
enyata [817]

Answer:

ok so we can divide 15 by 5 to get 3

so we know the building is 3 times bigger

so we multiply 3 by 3 to get 9

so the answer is D

8 0
3 years ago
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What is the equation of the line that passes through the point (-5,5) and has a slope of -1
max2010maxim [7]

Answer:

y - 5 = -(x + 5)

y - 5 = -x - 5

y = -x

7 0
4 years ago
Question 1 (10 points). (a) Explain the difference between linear and logistic regression. (Explain at least two differences and
cricket20 [7]

Answer:

(a) <em>Linear regression</em> is used to estimate dependent variable which is continuous by using a independent variable set. <em>Logistic regression</em> we predict the dependent variable which is categorical using a set of independent variables.

(b) Finding the relationship between the Number of doors in the house vs the number of openings. Suppose that the number of door is a dependent variable X and the number of openings is an independent variable Y.

Step-by-step explanation:

(a) Linear regression is used to estimate dependent variable which is continuous by using a independent variable set .whereas In the logistic regression we predict the dependent variable which is categorical using a set of independent variables. Linear regression is regression problem solving method while logistic regression is having use for solving the classification problem.

(b) Example: Finding the relationship between the Number of doors in the house vs the number of openings. Suppose that the number of door is a dependent variable X and the number of openings is an independent variable Y.

If I am to predict that increasing or reducing the X will have an effect on the input variable X or by how much we will make a regression to find the variance that define the relationship or strong relationship status between them. I will run the regression on any computing software and check the stats result to measure the relationship and plots.

3 0
3 years ago
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