probability and statistics

Question

1.     Read the given data ‘TIPS.csv’ as a dataframe named Tips and answer the following question.

a) In the tips dataframe, for the variable “total bill” what is the 3rd quartile and maximum value?

b) The range of the variable “TotalBill”?

Note: Please download the dataset TIPS.csv attached in the shared files section for attending the assignment.

2.     From the given below boxplot identify the median value and the outlier.

Answer 1

Note: I will be using R markdown for my answers. I don't have access to the file so I will talk about the process I would go through instead.

1. First we need to load in the data:

```{r}

tips <- read.csv("TIPS.csv")

tips

```

Thus, we can view our dataset.

To answer parts a and b, we can use the quantile function in R to find the major quantiles of a vector, including the 0th quantile, the 3rd quantile, and the 4th quantile. If I were to do it, it would look something like this:

```{r}

quantile(tips[["TotalBill"]])

```

Note: The quantile function cannot work with data frames, so, by putting double square brackets around the column we want to use from the data frame, we turn the data frame into a list of numbers that the quantile function can then work with. This is because a data frame is a list.

2 I will use my own example for this since you have not provided the box plot. Here is a boxplot:

```{r}

boxplot(cars[2],cars[2])

```

So, this boxplot is available from base R and can be viewed in any R by copying just the middle part. The big, bold, black line in the box is the median, the top and bottom of the box are the 1st and 3rd quantiles, and the the lines extending outward the 0th and 4th quantiles. The white dot at the top is the outlier for this boxplot, and it is how base R plotting chooses to display outliers. Thus, we can compare what we know about our variable with our outlier and figure out what value of the variable is an outlier in this case.