In a population, the correlation coefficient between family income and child IQ is 0.30. The mean family income was $60,000. The standard deviation in income is $20,000. IQ is measured on a scale such that the mean is 100, and the standard deviation is 15.

(a) Using this information, predict the expected IQ of a child whose family income is $70,000
(b) How reliable do you expect this prediction to be? Why? (your answer should be a property of correlation, not an about IQ)
(c) The family income now rises does the correlation predict that the child will have a higher IQ? Why? opinion

Step-by-step explanation:

Solution A:

regression eq is

y=a+bx

IQ=a+b*Income

where b=r*sy/sx

=0.3*15/20000

=0.000225

a=ybar-bxbar

a=100-0.000225*60000

a=86.5

y=a+bx

y=86.5+0.000225*x

IQ=86.5+0.000225*income

For given income of 70000 we need to predict IQ

substitute income =70000 in regression equation obtained above we get

IQ=86.5+0.000225*70000

predicted IQ=102.25

Solution b:

since r=0.30

r sq=0.30*0.30

=0.09

=0.09*100

=9%

that is explained variance by regression eq is

9%

unexplained variance=100-9=91%

9% variance in IQ is explained by regression equation.

Solution-c:

correlation does not imply causation with correlation cannot predict that the child will have a higher IQ

we can get only the relationship between two variable with correlation,but we cant predict

no

step-by-step explanation:

2-7=-5

7-2=5

when you combing like terms for ech expression, 5 and -5. these numbers are not equal to each other.

step-by-step explanation:

ok one would be money, and the other would be refreshments or something similar. if each bag of popcorn is 5.00 and each drink is half of that that means drinks are 2.50 the proper way to do that would to look and see how much of each you can buy without exceeding a limit of 30.00