Description: df [10 x3] FRTDAY CHECKUP1 GENHLTH 1 1.00 2 1 2 3 4 569 1.00 1 2.00 2 1 1.00 1 1.00 1 1 0.02 4 7 0.71 3 1 00 8 9 10 1-10 of 10 rows 1.00 1.00 1.00 11 N 1 2 1
### Q8: Create a regression predicting general health based on both number of fruits consumed per day and the length of time since last checkup (in that order). Analyze the summary of the model. How would you assess this model? Store the summary of the standardized regression coefficients in `Q8.`
Hint: The resulting summary output should look like this:
```
Call:
[...]
Residuals:
Min 1Q
<value> <value> <value> <value> <value>
Coefficients:
Estimate Standardized Std. Error t value Pr(>|t|)
(Intercept) 2.672440 <value> <value> <value> <value>
FRTDAY -0.107117 <value> <value> <value> <value>
[...]2 <value> <value> <value> <value> <value>
[...]3 <value> <value> <value> <value> <value>
[...]4 <value> <value> <value> <value> <value>
[...]8 <value> <value> <value> <value> <value>
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: <value> on <value> degrees of freedom
Multiple R-squared: <value>, Adjusted R-squared: <value>
F-statistic: <value> on <value> and <value> DF, p-value: < <value>
``` Use brf_part1 data attached as a pic.Give R-code
![Description: df [10 x3]
FRTDAY
CHECKUP1
GENHLTH
<dbl>
<dbl>
1
1.00
2
<dbl>
1
2 3 4 569
1.00
1
2.00
2
1
1.00
1
1.00
1
1
0.02
4
7
0.71
3
1
00
8
9
10
1-10 of 10 rows
1.00
1.00
1.00
11 N
1
2
1](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6622839c-edf1-4b58-b49c-cfb0d3c1ae38%2F41b22374-8d3a-408f-b3c0-8a20f69eb27a%2Flyrgrln_processed.png&w=3840&q=75)
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