Well this was the class that i took some year back, a three day R studio Tutorial classes.

# Things We will Study today

```
- Intro To R
- How to use Rstudio
- Mean
- Median
- Mode
- Range
- Quartile Deviation
- Standard Deviation
```

**To View the Datasets available by default**

`library(help="datasets")`

So Basically We are using a **Dataset** Cars which is by default present in the RStudio which basically consists of 50 rows:

`nrow(cars)`

`## [1] 50`

and 2 columns:

`ncol(cars)`

`## [1] 2`

**head()** gives the first 6 rows of the dataset so that we can make an idea about the dataset

`head(cars)`

```
## speed dist
## 1 4 2
## 2 4 10
## 3 7 4
## 4 7 22
## 5 8 16
## 6 9 10
```

**To access a particular column**

`cars$speed`

```
## [1] 4 4 7 7 8 9 10 10 10 11 11 12 12 12 12 13 13 13 13 14 14 14 14
## [24] 15 15 15 16 16 17 17 17 18 18 18 18 19 19 19 20 20 20 20 20 22 23 24
## [47] 24 24 24 25
```

**Similarly,**

`cars$dist`

```
## [1] 2 10 4 22 16 10 18 26 34 17 28 14 20 24 28 26 34
## [18] 34 46 26 36 60 80 20 26 54 32 40 32 40 50 42 56 76
## [35] 84 36 46 68 32 48 52 56 64 66 54 70 92 93 120 85
```

**For mean**

`mean(cars$dist) `

`## [1] 42.98`

**Median, run :**

`median(cars$dist)`

`## [1] 36`

**Quantile , run : **

`quantile(cars$dist)`

```
## 0% 25% 50% 75% 100%
## 2 26 36 56 120
```

**Variance , run : **

`var(cars$dist)`

`## [1] 664.0608`

**Standard Deviation , run : **

`sd(cars$dist)`

`## [1] 25.76938`

To do all the things we have done at once we use a function **summary()**

`summary(cars)`

```
## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
## Max. :25.0 Max. :120.00
```

# GRAPHS

We can also embed plots, for example:

A **histogram** of the speed of the Cars using **hist()** function

**Scatterplot**

`plot(cars,xlab="Speed",ylab = "Distance",main = "Scatter plot of Speed and distance covered")`

**Barplot** Similarly for barplot

`barplot(cars$dist)`

Note that the `echo = FALSE`

parameter was added to the code chunk to prevent printing of the R code that generated the plot.

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