Predict the number of days in the past 30 days that mental health was not good from marital status. - Your output should match the value included in the summary below. This value is given to you as a check to make sure you are on the right track. - Keep in mind that one of the possible answers to "how many days" is 0, not just 1-30. - Make sure you know what type of variable MARITAL is. You'll need to consider this when determining how to do linear regression with it. - Assign the summary of the model to Q5. Note: the general instructions say to round all output but the summary() of a model is not able to be rounded. Your output should look something like this: ``` Call: lm(formula = ~ , data = ) Residuals: Min 1Q Median 3Q Max [value] [value] [value] [value] [value] Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) [value] [value] [value] [value] *** MARITAL2 2.26240 [value] [value] [value] *** MARITAL3 [value] [value] [value] [value] *** MARITAL4 [value] [value] [value] [value] *** MARITAL5 [value] [value] [value] [value] *** MARITAL6 [value] [value] [value] [value] ***
Predict the number of days in the past 30 days that mental health was not good from marital status. - Your output should match the value included in the summary below. This value is given to you as a check to make sure you are on the right track. - Keep in mind that one of the possible answers to "how many days" is 0, not just 1-30. - Make sure you know what type of variable MARITAL is. You'll need to consider this when determining how to do linear regression with it. - Assign the summary of the model to Q5. Note: the general instructions say to round all output but the summary() of a model is not able to be rounded. Your output should look something like this: ``` Call: lm(formula = ~ , data = ) Residuals: Min 1Q Median 3Q Max [value] [value] [value] [value] [value] Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) [value] [value] [value] [value] *** MARITAL2 2.26240 [value] [value] [value] *** MARITAL3 [value] [value] [value] [value] *** MARITAL4 [value] [value] [value] [value] *** MARITAL5 [value] [value] [value] [value] *** MARITAL6 [value] [value] [value] [value] ***
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Predict the number of days in the past 30 days that mental health was not good from marital status.
- Your output should match the value included in the summary below. This value is given to you as a check to make sure you are on the right track.
- Keep in mind that one of the possible answers to "how many days" is 0, not just 1-30.
- Make sure you know what type of variable MARITAL is. You'll need to consider this when determining how to do linear regression with it.
- Assign the summary of the model to Q5. Note: the general instructions say to round all output but the summary() of a model is not able to be rounded. Your output should look something like this:
```
Call:
lm(formula = ~ , data = )
Residuals:
Min 1Q Median 3Q Max
[value] [value] [value] [value] [value]
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) [value] [value] [value] [value] ***
MARITAL2 2.26240 [value] [value] [value] ***
MARITAL3 [value] [value] [value] [value] ***
MARITAL4 [value] [value] [value] [value] ***
MARITAL5 [value] [value] [value] [value] ***
MARITAL6 [value] [value] [value] [value] ***
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