Answer:
Residual = 11.462
Since the residual is positive, it means it is above the regression line.
Step-by-step explanation:
The residual is simply the difference between the observed y-value which is gotten from the scatter plot and the predicted y-value which is gotten from regression equation line.
The predicted y-value is given as 20.7°
The regression equation for temperature change is given as;
y^ = 9.1 + 0.6h
h is the observed amount of humidity and it's given to be 23 percent or 0.23.
Thus;
y^ = 9.1 + 0.6(0.23)
y^ = 9.238
Thus:
Residual = 20.7 - 9.238
Residual = 11.462
Since the residual is positive, it means it is above the regression line.
I think you answer should be 51
Answer:
the answer to this question is 52.18
Answer: hey mate i have you answer
Step-by-step explanation: Sample Response: If the data is collected in a biased manner, the graph could be skewed. Also, if the number of observations is too small, the graph can be skewed. To ensure the data is not skewed, collect a large representative unbiased sample
Answer:
189,2$
Step-by-step explanation:
220*0,86=189,2
14% = 14/100 = 0,14
1-0,14 = 0,86
price* factor between 0 and 1, 0 -> item is free, 1 -> full price
