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3 years ago

How to find and interpret intercept in linear regression.

1 answer:

7 0

Answer:Here's the definition: the intercept (often labeled the constant) is the expected mean value of Y when all X=0. Start with a regression equation with one predictor, X. If X sometimes equals 0, the intercept is simply the expected mean value of Y at that value.

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Where can we put parentheses in 19 - 3 times 5 to make it equivalent to 80

notsponge [240]

Answer:

(19-3)*5 = 80

Step-by-step explanation:

(19-3)*5 = 80

Parentheses first

16*5 = 80

3 0

3 years ago

Read 2 more answers

Can the sides of a triangle have lengths 1, 7, and 11? Explain

Airida [17]

Given 3 sides of a triangle, the sum of any 2 sides must be greater than the third side.

Consider the 3 given sides 1, 7 and 11

7 + 11 = 18 > 1

1 + 11 = 12 > 7

1 + 7 < 11 ⇒ not valid

Hence these sides do not form a triangle

6 0

3 years ago

How many solutions does the following equation have?

Evgesh-ka [11]

Answer:

no solution

Step-by-step explanation:

There are no values of x that make the equation true.

No solution

6 0

3 years ago

Write an expression for the sum of four consecutive odd integers where 2n +1 represents the smallest odd integer.

7nadin3 [17]

8n+16
the four odd numbers are 2n+1, 2n+3, 2n+5, 2n+7
2n+1+2n+3+2n+5+2n+7=8n+16

5 0

3 years ago

The table below gives the completion percentage and interception percentage for five randomly selected NFL quarterbacks. Based o

Lina20 [59]

The regression equation is y = -0.42647x + 29.11471 and the correlation coefficient is -0.9607

<h3>How to determine the regression equation?</h3>

The table of values is given as:

Completion Percentage 57 59 62 63 64

Interception Percentage 5 3.5 3 2.5 1.5

Next, we enter the above values in a graphing calculator.

From the graphing calculator, we have the following summary:

Sum of X = 305
Sum of Y = 15.5
Mean X = 61
Mean Y = 3.1
Sum of squares (SSX) = 34
Sum of products (SP) = -14.5
r = -0.9607

Regression Equation = ŷ = bX + a

b = SP/SSX = -14.5/34 = -0.42647

a = MY - bMX = 3.1 - (-0.43*61) = 29.11471

So, the regression equation is

y = -0.42647x + 29.11471

And the correlation coefficient is -0.9607