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ehidna [41]
3 years ago
15

What does a residual value of –4.5 mean in reference to the line of best fit?

Mathematics
2 answers:
Sonbull [250]3 years ago
8 0

Answer:

The actual or observed data point is below the line of best fit.

Step-by-step explanation:

Since we know that residual is the difference between the observed value of the dependent variable (y) and the predicted value (ŷ) of a regression model. Residual tells us that how far the data falls from the regression line.

\text{Residual}=\text{Observed value- Predicted value}  

  • If we have a positive value for residual, this means dependent variable's actual value is greater than its predicted value.
  • If we have a negative value for residual, this means dependent variable's actual value is less than its predicted value.
  • For data points above the line, the residual is positive, and for data points below the line, the residual is negative.

-4.5=\text{Observed value- Predicted value}  

\text{ Predicted value}-4.5=\text{Observed value}  

Since our given residual value is -4.5, therefore, observed or actual value of dependent variable is 4.5 less than its predicted value and it is below line of best fit.


Step2247 [10]3 years ago
7 0

Answer:

The residual value is the difference between the observed value (from the scatter plot) and the predicted value (from the line of best fit).


Step-by-step explanation:

The residual value is the difference between the observed value (from the scatter plot) and the predicted value (from the line of best fit).

Residual Value = Observed Value - Predicted Value

<em>Since the residual value of -4.5 is negative, we can say the predicted value is larger than the observed value. In other words, the line of best fit is "above" the scatter plot point in that specific point.</em>

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emmasim [6.3K]

Step-by-step explanation:

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= Solution ,

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= Solution,

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Hence, the required probability = 0.628

5 0
3 years ago
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