1. for women age 25–34 in the hanes5 sample, the relationship between height and income can be summarized as follows: average height ≈ 64 inches, sd ≈ 2.5 inches average income ≈ $21,000, sd ≈ $20,000, r ≈ 0.2 the slope of the regression equation is . the y-intercept is the predicted income for a woman who is 67 inches tall is . the predicted income for a woman who is 60 inches tall is . the rms error for these predictions is (round your answer to 2 digits).

Step-by-step explanation:

Data given and  previous concepts

represent the sample mean for the height

represent the sample deviation for the height

represent the sample mean for the income

represent the sample deviation for the income

r=0.2 represent the correlation coefficient

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

And in order to calculate the correlation coefficient we can use this formula:

Solution to the problem

Let's suppose that we have the following linear model:

Where Y is the dependent variable (income) and X the independent variable (height). represent the intercept and the slope.  

In order to estimate the coefficients we can use least squares estimation.  

We have an useful formula in order to estimate the slope for the linear model given by:

Now we can find the intercept for the linear model with the following formula:

And then our linear model would be given by:

We can estimate the RMS with the following formula:

do you have a picture of the table

answer: (yeees, you need a poet.)

//blooming serenity//

beautiful in the morning

mysterious at night

wonderous nature souring

with all it's mystical might

the flower that blooms

to the fox that looms

nocturnal creatures

with various features

a blooming flower soon in sight

as a new little hatchling fears to take flight  

afraid to leave it's calming nest,

but dear little bird, mother knows best

as sure as there are stars in the sky,

life is not about who, where what, when or why-

it's the journey that follows

adventures we swallow

of   nature's deep wonders,

natural disasters and storm's thunders.

blooming serenity

life and nature, truly is heavenly.

-kerstien lehman

step-by-step explanation: