# How to create a boxplot with multiple variables in r

### How do you make a multiple Boxplot in R?

We can

**draw multiple boxplots**in a single**plot**, by passing in a list, data frame or**multiple**vectors. Let us consider the Ozone and Temp field of airquality dataset. Let us also generate normal distribution with the same mean and standard deviation and**plot**them side by side for comparison.### How do you make a side by side Boxplot in R?

**How to Make**a**Side-By-Side Boxplot in R**- main – the main title of the breath.
- names – labels for each of the data sets.
- xlab – label before the x-axis,
- ylab – label for the y-axis.
- col – color of the
**boxes**. - border – color of the border.
- horizontal – determines the orientation to
**graph**. - notch – appearance of the
**boxes**.

### How do you make a comparative Boxplot in R?

- If you’d like to compare two sets of data, enter each set separately, then enter them individually into the
**boxplot**command. x=c(1,2,3,3,4,5,5,7,9,9,15,25) y=c(5,6,7,7,8,10,1,1,15,23,44,76)**boxplot**(x,y) - You can easily compare three sets of data.
- You can use the argument horizontal=TRUE to lay them out horizontally.

### How do I add color to a Boxplot in R?

We can

**add**fill**color**to**boxplots**using fill argument inside aesthetics function aes() by assigning the variable to it. In this example, we fill**boxplots**with**colors**using the variable “age_group” by specifying fill=age_group. ggplot2 automatically uses a default**color**theme to fill the**boxplots**with**colors**.### How do you do side by side Boxplots in R studio?

### How do I label a Boxplot in R?

The common way to put

**labels**on the axes of a plot is by using the arguments xlab and ylab. As you can see from the image above, the**label**on the Y axis is place very well and we can keep it. On the other hand, the**label**on the X axis is drawn right below the stations**names**and it does not look good.### What are side-by-side Boxplots good for?

**Side-By-Side boxplots**are used to display the distribution of several quantitative variables or a single quantitative variable along with a categorical variable.

### How do side-by-side Boxplots compare?

**Guidelines for**

**comparing boxplots****Compare**the respective medians, to**compare**location.**Compare**the interquartile ranges (that is, the box lengths), to**compare**dispersion.- Look at the overall spread as shown by the adjacent values.
- Look for signs of skewness.
- Look for potential outliers.

### How do you explain side-by-side Boxplots?

As its name implies, the

**side-by-side boxplot**is constructed by placing single**boxplots**adjacent to one another on a single scale. A**side-by-side boxplot**has all the advantages of a single**boxplot**(which can be seen here) with the added benefit of providing clear comparisons between levels in: Range. Variance.### When should a set of side-by-side Boxplots be used to explore the relationship between two variables?

If there are

**two**categorical**variables**a**two**-way table**will**be**used**. Also if one**variable**is categorical and the other quantitative,**side**-by**side boxplots will**be**used**.### What do box plots tell us?

**Box plots**divide the data into sections that each contain approximately 25% of the data in that set.

**Box plots**are useful as they provide a visual summary of the data enabling researchers to quickly identify mean values, the dispersion of the data set, and signs of skewness.

### What are box and whisker plots used for in real life?

**Box and whisker plots**are ideal for comparing distributions because the centre, spread and overall range are immediately apparent. A

**box and whisker plot**is a way of summarizing a set of data measured on an interval scale. the ends of the

**box**are the upper and lower quartiles, so the

**box**spans the interquartile range.

### What does it mean if a Boxplot is positively skewed?

**Positively Skewed**: For a distribution that is

**positively skewed**, the

**box plot**will show the median closer to the lower or bottom quartile. A distribution is considered “

**Positively Skewed**”

**when mean**> median. It

**means**the data constitute higher frequency of high valued scores.

### What are the advantages of a box plot?

**Advantages**of

**Boxplots**

Graphically display a variable’s location and spread at a glance. Provide some indication of the data’s symmetry and skewness. Unlike many other methods of data display, **boxplots** show outliers.

### Why is a box plot better than a histogram?

Although

**histograms**are**better**in determining the underlying distribution of the data,**box plots**allow you to compare multiple data sets**better than histograms**as they are less detailed and take up less space. It is recommended that you**plot**your data graphically before proceeding with further statistical analysis.### What is a disadvantage of a box plot?

**Boxplot Disadvantages**:

Hides the multimodality and other features of distributions. Confusing for some audiences. Mean often difficult to locate. Outlier calculation too rigid – “outliers” may be industry-based or case-by-case.

### What are the advantages and disadvantages of using a box plot?

**Advantages**&**Disadvantages**of a**Box Plot**- Handles Large Data Easily. Due to the five-number data summary, a
**box plot**can handle and present a summary of a large amount of data. - Exact Values Not Retained.
- A Clear Summary.
- Displays Outliers.

### What are the disadvantages of histogram?

**Histograms**have many benefits, but there are two

**weaknesses**. A

**histogram**can present data that is misleading. For example, using too many blocks can make analysis difficult, while too few can leave out important data.

### When should we use a histogram?

When to

**Use a Histogram** Analyzing whether a process can meet the customer’s requirements. Analyzing what the output from a supplier’s process looks like. Seeing whether a process change has occurred from **one** time period to another. Determining whether the outputs of two or more processes are different.

### What is the purpose of using a histogram?

A

**histogram**is used to summarize discrete or continuous data. In other words, it provides a visual interpretation. This requires focusing on the main points, factsof numerical data by showing the number of data points that fall within a specified range of values (called “bins”). It is similar to a vertical**bar graph**.### What are the benefits of using a histogram?

**Histograms**allow viewers to easily compare data, and in addition, they work well with large ranges of information. They are also provide a more concrete from of consistency, as the intervals are always equal, a factor that allows easy data transfer from frequency tables to

**histograms**.

### What are the pros and cons of a histogram?

**Pros and cons**

- Histograms are useful and easy, apply to continuous, discrete and even unordered data.
- They use a lot of ink and
**space**to display very little information. - It’s difficult to display several at the same time for comparisons.