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:
There are a lot of turning point in the history of algebra one of those is the discovery of the plain and the quadrants by Rene Descartes. This discovery paved way to a lot of knowledge which was later on use in solving other complicated mathematical problems.
Step-by-step explanation:
Answer:
-21 = 6t
Step-by-step explanation:
3t - 7 = 5t
Subtract 3t from each side
3t-7-3t = 5t-3t
-7 = 2t
Multiply each side by 3 to get 6t
-7*3 = 2t*3
-21 = 6t
Answer: y=54(lb)x+170(lb)
Step-by-step explanation: that's the function for it but I tried. You need to include how much weight the elevator can hold though
Answer:
-1
Step-by-step explanation:
sub in the values of x, y and z into the equation
you get:
(-3)(-4)/(-2)(6)
= 12/-12
= -1
