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Andre45 [30]
3 years ago
15

What is the answer for 2/3 plus 4 equals 7 make this into an equation

Mathematics
1 answer:
Readme [11.4K]3 years ago
4 0
The answer is 4 2/3 minus 2 

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Regression analysis is a statistical procedure for developing a mathematical equation that describes how
Mila [183]

Answer: Regression analysis is a statistical procedure for developing a mathematical equation that describes how the dependent variable (y) is related to the independent variable(x).

Step-by-step explanation:

REGRESSION ANALYSIS

Regression analysis is a statistical method used to determine the relationship between two or more variables of interest way. It is a way of sorting out variables which have impact mathematically. It is a more sophisticated way of examining the relationship between two (or more) variables than is correlation. The major differences between correlation and regression are:

Regression can investigate the relationships between two or more variables.

It determines the direction of causality, from the explanatory variable (or variables) to the dependent variable.

The impact of each explanatory variable on the dependent variable is measured.

Regression analysis explains this causal relationship by fitting a straight line drawn through the data, which best summarises them. It is sometimes called ‘the line of best fit’ for this reason.

Regression analysis gives answers to such questions as:

Which factors matters most?

Which factors can be ignored?

How do these factors interact with each other?

Does the growth rate influence a country’s birth rate?

If the growth rate increases, by how much might a country’s birth rate be expected to fall?

Are other variables important in determining the birth rate?

In regression analysis, factors are called Variables. There are two (2) types of variables.

1. Dependent variables: This is the main factor you are trying to predict

2. Independent variables: This is the factor you suspect has an impact on the dependent variable.

The equation of the sample regression line may be written as

Zi = a + bXi

Where;

Zi is the predicted value of Y for observation

Xi is the value of the explanatory variable for observation

a is the bare fixed coefficients to be estimated. It measures the intercept of the regression line on the Y-axis

b measures its slope.

The regression analysis equation describes how the dependent variable (y) is related to the independent variable(x). It allows you to predict the outcome of a relatively small amount of error.

3 0
3 years ago
A college is currently accepting students that are both in-state and out-of-state. They plan to accept three times as many in-st
densk [106]

Answer:

\[y < = 300\]

Step-by-step explanation:

Let x = number of out-of-state students at the college

Let y = number of in-state students at the college

As per the given problem, the constraints are as follows:

\[x < = 100\]    --------- (1)

\[y = 3 * x\]      --------- (2)

From the given equations (2), \[ x = y/3 \]

Substituting in (1):

\[y/3 < = 100\]

Or, \[y < = 300\] which is the constraint representing the incoming students.

7 0
3 years ago
Read 2 more answers
A large pizza at palanizo pizzeria costs 6.80$ plus 0.90$ for each topping. The cost of a large cheese pizza at guido’s pizza is
r-ruslan [8.4K]

we are going to create a table in excel and we will assign different values ​​of topping to know when the price is equal in both pizzerias

 

see the attached figure

 

the answer is

5 toppings from palanzio’s pizzeria

6 toppings from guido’s pizza

cost palanzio’s pizzeria----> 6.80+0.90*5-----> $11.30

cost <span>guido’s pizza------> 7.40+0.65*6----------> $11.30</span>

 

5 0
3 years ago
Look at the drawing below.
Ratling [72]

Answer:

\small\mathfrak\green{2x + 10 + 46 = 180 \:   = linear \: pair} \\  \\ \small\mathfrak\red{hope  it  helps...}

8 0
3 years ago
and are independent Gaussian (Normal) random Variables. has mean 13.9 and variance 5.2; has mean 6.9 and variance 3.8. . (a) Cal
omeli [17]

This question is incomplete, the complete question is;

X and Y are independent Gaussian (Normal) random Variables. X has mean 13.9 and variance 5.2; Y has mean 6.9 and variance 3.8. . (a) Calculate P( W> 10)

Answer:

P( W> 10) is 0.1587

Step-by-step explanation:

Given that;

X ⇒ N( 13.9, 5.2 )

Y ⇒ N( 6.9, 3.8 )

W = X - Y

Therefore

E(W) = E(X) - E(Y)

= 13.9 - 6.9 = 7

Var(W) = Var(X) + Var(Y) -2COV(X.Y)

[ COV(X,Y) = 0 because they are independent]

Var(W) = 5.2 + 3.8 + 0

= 9

Therefore

W ⇒ N( 7, 9 )

so

P( W > 10 )

= 1 - P( W ≤ 10 )

= 1 - P( W-7 /3   ≤   10-7 /3 )

= 1 - P( Z ≤ 1 )           [ Z = W-7 / 3 ⇒ N(0, 1)  ]

from Standard normal distribution table, P( Z ≤ 1 )  = 0.8413

so

1 - P( Z ≤ 1 )  = 1 - 0.8413 = 0.1587

Therefore P( W> 10) is 0.1587

8 0
3 years ago
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