Question
Q: Help in understanding and solving this example on r studio, thanks. Save the data set Lung Capacity into variable b ```{r} ``` Using inline
Q: Help in understanding and solving this example on r studio, thanks.
Save the data set Lung Capacity into variable b ```{r}
``` Using inline code, print the header of the data set.
Using inline code, state the mean age of the data set, medain age, and mode height
Display the box and whisker plot for height ```{r}
```
Display a bar graph for Gender vs Smoker ```{r}
```
Dispaly a scatter plot for Lung Capacity vs Age. The color of the points should be gold ```{r}
```
Using inline code, display the Correlation Coffiecient for a) Lung Capacity vs Age b) Age vs Height.
Display a scatter plot Lung Capacity vs Height a) plot the line regression line b) Female points are -green and Males points are blue ```{r}
```
Gender | Height | Smoker | Age | Lung Capacity |
Male | 70 | no | 47 | 5673 |
Male | 70 | no | 67 | 5632 |
Male | 68 | no | 36 | 5712 |
Male | 71 | no | 68 | 5723 |
Male | 72 | yes | 58 | 5484 |
Male | 69 | yes | 19 | 5308 |
Male | 72 | yes | 40 | 5133 |
Male | 71 | no | 82 | 5550 |
Male | 70 | no | 22 | 5614 |
Male | 71 | yes | 35 | 5415 |
Male | 71 | no | 45 | 5692 |
Male | 69 | no | 21 | 5787 |
Male | 67 | no | 71 | 5518 |
Male | 65 | no | 61 | 5787 |
Male | 70 | no | 65 | 5551 |
Male | 70 | no | 45 | 5625 |
Male | 68 | yes | 39 | 5388 |
Male | 73 | no | 37 | 5861 |
Male | 77 | no | 39 | 6261 |
Male | 66 | yes | 40 | 5205 |
Male | 71 | no | 72 | 5697 |
Male | 72 | no | 42 | 5770 |
Male | 68 | yes | 37 | 5399 |
Male | 64 | yes | 50 | 5042 |
Male | 66 | yes | 59 | 5180 |
Male | 72 | no | 41 | 5764 |
Male | 68 | yes | 54 | 5438 |
Male | 70 | no | 58 | 5557 |
Male | 72 | no | 69 | 5793 |
Male | 67 | yes | 49 | 5254 |
Male | 68 | yes | 30 | 5439 |
Male | 61 | yes | 28 | 4735 |
Male | 76 | no | 69 | 6228 |
Male | 73 | no | 69 | 5929 |
Male | 71 | no | 35 | 5683 |
Male | 71 | no | 46 | 5655 |
Male | 70 | no | 46 | 5555 |
Male | 71 | no | 38 | 5734 |
Male | 65 | yes | 23 | 5132 |
Male | 76 | no | 42 | 6212 |
Female | 72 | no | 54 | 5843 |
Female | 74 | no | 66 | 5959 |
Female | 69 | no | 50 | 5530 |
Female | 70 | no | 32 | 5594 |
Female | 71 | no | 32 | 5655 |
Female | 71 | no | 45 | 5657 |
Female | 69 | yes | 40 | 5463 |
Female | 70 | no | 44 | 5585 |
Female | 68 | yes | 37 | 5397 |
Male | 66 | yes | 59 | 5203 |
Male | 67 | no | 49 | 5093 |
Male | 67 | no | 41 | 5116 |
Male | 70 | no | 35 | 5400 |
Male | 63 | yes | 23 | 4713 |
Male | 63 | yes | 41 | 4644 |
Male | 63 | yes | 42 | 4690 |
Male | 63 | yes | 55 | 4651 |
Male | 67 | no | 58 | 5072 |
Male | 69 | no | 59 | 5285 |
Female | 69 | no | 42 | 5278 |
Female | 70 | no | 46 | 5485 |
Female | 67 | no | 40 | 5122 |
Female | 66 | yes | 51 | 4959 |
Female | 67 | yes | 38 | 4636 |
Female | 64 | no | 67 | 5547 |
Female | 65 | no | 32 | 5484 |
Female | 68 | no | 45 | 5402 |
Female | 65 | no | 36 | 5531 |
Female | 68 | no | 63 | 5164 |
Female | 73 | yes | 46 | 4641 |
Female | 71 | no | 26 | 5530 |
Female | 70 | no | 34 | 5401 |
Female | 68 | no | 73 | 5187 |
Female | 66 | no | 28 | 5010 |
Female | 72 | no | 32 | 5625 |
Female | 65 | yes | 64 | 4945 |
Female | 65 | yes | 50 | 4925 |
Female | 65 | yes | 79 | 4900 |
Female | 65 | yes | 47 | 4874 |
Female | 63 | yes | 58 | 4686 |
Female | 63 | no | 51 | 5152 |
Female | 71 | yes | 54 | 4823 |
Female | 70 | yes | 43 | 4940 |
Female | 70 | no | 43 | 5206 |
Female | 71 | yes | 39 | 4858 |
Female | 68 | no | 40 | 5233 |
Female | 63 | no | 50 | 5776 |
Female | 71 | no | 19 | 5594 |
Female | 67 | no | 50 | 5075 |
Female | 67 | no | 38 | 5101 |
Female | 67 | no | 28 | 5156 |
Female | 64 | yes | 52 | 4783 |
Female | 59 | yes | 33 | 4234 |
Female | 63 | yes | 29 | 4625 |
Female | 65 | yes | 53 | 4906 |
Female | 62 | yes | 54 | 4620 |
Female | 68 | no | 43 | 5187 |
Female | 73 | no | 69 | 5760 |
Female | 62 | yes | 47 | 4553 |
Female | 66 | yes | 55 | 4980 |
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