QUESTION IMAGE
Question
question 7
1 pts
consider the following r output, which models dissolved oxygen levels based on water temperature.
r
slr_model <- lm(dissolved_oxygen ~ temperature)
slr_model
##
call:
lm(formula = dissolved_oxygen ~ temperature)
##
coefficients:
(intercept) temperature
14.4636 -0.2227
predict the dissolved oxygen when water temperature is 21°c, using the regression model. round your answer to 4 decimal places.
question 8
1 pts
consider the following r output, which models dissolved oxygen levels based on water temperature.
r
slr_model <- lm(dissolved_oxygen ~ temperature)
slr_model
##
call:
lm(formula = dissolved_oxygen ~ temperature)
##
coefficients:
(intercept) temperature
14.4636 -0.2227
the dissolved oxygen level of water at 21°c is found to be 9.0 mg/l. calculate the residual using the regression model. round your answer to 4 decimal places.
⚡ Using what you learned: regression, residuals, and model fit
Step 1: Formulate the Regression Equation
From the R output, the coefficients are:
- Intercept (\(b_0\)): \(14.4636\)
- Slope for temperature (\(b_1\)): \(-0.2227\)
The regression equation is:
Step 2: Predict Dissolved Oxygen for Question 7
Substitute \(x = 21\) into the equation:
Step 3: Calculate the Residual for Question 8
Using the actual value \(y = 9.0\) and the predicted value \(\widehat{y} = 9.7869\):
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Question 7:
9.7869
Question 8:
-0.7869