Which characteristic of a data set makes a linear regression model unreasonable?
Answer: A correlation coefficient close to zero makes a linear regression model unreasonable.
If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important check is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.
Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.
Answer:
A, C, and D:)
Step-by-step explanation:
Just checked I got it right on ed Have a great day!
The function
represents exponential growth with the initial value equal to 1, the decay factor equal to 0.3, and the rate equal to 0.7.
<h3>Population Growth Equation</h3>
The formula for the Population Growth Equation is:

Pf= future population
Po=initial population
r=growth rate
t= time (years)
growth or decay factor = (1 ±r)
When 1+R > 1, the equation represents growth, while 1+R < 1 the equation represents decay.
The question gives:
, then
Pf=y
Po= 1
, thus

r= -70%= -0.7
decay factor= (1-0.7)=0.3
Therefore,
1+R will be = 1+(-0.7)=1 - 0.7 =0.3
When 1+R >1, the function represents exponential growth.
Read more about the exponential function here:
brainly.com/question/8935549
2:3:5
2x+3x+5x=180
10x=180
x=18
2x=36
3x=54
5x=90
I believe it would be 20/15