Line Graph & Dot Plot Graph—an Ultimate Insight

Analytics is based on historical data. Businesses and corporate sectors conduct business analyses in order to make better decisions and enhance productivity. You gather data called data mining in order to make such in-depth analysis and sound decisions. Graphs are commonly used to illustrate this type of data. We will compare slope and line graphs today in this in-depth article. Let’s learn what the difference is between a line graph and a dot graph. Further, we will explore where these graphs are usefully applied.

What is a Line Graph?

Line graphs, or line charts, are commonly employed to depict the pictorial representation of quantitative data accumulated over a particular niche and period of time. For depicting data flow and fluctuations, a line graph is presented. The line connects the points. Each point is connected by a line. A data point is an observation that is made during a survey or research. There is an x-axis and a y-axis in a line graph.

When to Use Line Graph?

Line graph trends a graphical depiction of the variations that had been presumed over a specific or settled period of time. A line graph is drawn across a horizontal axis called the x-axis and alongside a vertical axis called the y-axis. The x-axis generally lays down a time period over which you come to like to potentialize the quantity of a specific thing or a category in the y-axis. Line graph also assists you to analyse the trend of the stock market, population, inflation, and weather forecast whether the quotient in the y-axis is dwindling or upsurging over a lapse of time. A line graph delivers an elaborative picture of an increasing or a decreasing data trend or category between the two items or things.

Line Graph Example

Line Graph poses practicality when one thing is varying against the changing intervals of time. Keeping in view this let’s explore the example of a line graph. The following example discusses a cookie sale graph in a superstore. The graph explains how a cookie sale tends to increase and decrease during the weekdays. This obviously will help the shop owner to make an appropriate decision.

The above-quoted example represents the nature of line graphs. The data of biscuit sales starts from Monday as starting weekday and Friday as the end weekday. The cookie sold on Monday for one box following Tuesday’s 4 boxes and so on up to Fridays with top highest gross sales—10 boxes.

What Other Factors Should You Use Line Graphs?

Line charts can show continuous data over the intervals of time, set against a common scale, and are therefore great to go for showing trends in data at equal passages of or over time. As a general rule, we should use a line chart when your dataset and values are given in numbers and include non-numeric (category) data. For instance, a store owner wants to analyze the growth of his sales and business over a specific season or time of one year.

Dot Plot Graph

One of the rarely used graphs is the dot line plot. A dot plot gets used to decipher or render information about data in a dot or small circle. The dot plot is represented on a number line (just like the axis) that shows the division of integral variables where a data value is defined by each individual dot or small circle.

The dot plot represents a statistical chart that is composed of data points or small circles that are vertically depicted with dot-like markers. It is usually plotted in the form of a bar graph or histogram in the sense that the height of each dataset of vertical dot points is equal to the number of items in that type interval.

How Dot Plot Graph Works

A dot plot is used to represent any data in the form of dots or small circles. The dot line graph is an otherwise known name to Dot Line that resembles a simplified column graph or a bar graph in terms of the height of the bar towers formed with dotted spots or circles to represent the numerical value of each dataset. Dot plots are also used to show a small quantity of data. For instance, a dot plot can take into account the number of goals scored by a player in a soccer match, which is represented in the following table.

 Key Components of Dot Plots

Key Components of Dot Plots

A dot plot generally contains the following key components as its elements:

  • X-axis is divided into the specified ranges of values for the variable.
  • Dotted height represents the frequency of the observed data values falling within each range.
  • Each Dot represents its effectiveness.
  • Optionally, dot plots can show more than one distribution, letting you compare them.

For the scored goal data, the dot plot depicts that the number of the goals scored by the players appears to be different. The controlled group scored approximately 4 goals on the average daily match and their performance. There also seem to be several match flow frequencies in terms of the score with extremely low score rates as low as 1 goal that the observer should focus on. The soccer club for goal observation has a higher goal value and has a succinct distribution than the control group. A hypothesis score range is required to determine the statistical significance of scored goal differences. Such representation lets you know how all data works to observe the performance of each individual player so that the next election could be decisive for the selection board.

What is the Difference Between a Line Graph & Dot Plot?

The dot plot is considered to be effectively used for the points to go beyond where lines and bars have limitations. Although it seems bizarre, especially for those who learned from their primary school math classes that a line bears an infinite range of points. But in visualization terms, points can go beyond so much more than lines. Here are some major differences that outdo dot line graphs upon line graph, with elaborative depth.

Dot Plot is More Elaborative

Beyond precincts and validity of Line Graphs, the dot plot elaborates a good in-depth insight into both time and frequency of the Data Presentation Paradigm. As shown in the above example and a very interesting fact on scored goal frequency with the number of goals by a player with the time that is shown by a dot. So these dot’s arrangement argues for the substitution for the bars that represent mean values and mean errors by ‘1-dimensional scatter plots in the observation of scored goal data analysis. The main reason for using dot lines is that scattered dots also show the distribution and its particular meaning with outliers and density in the presentation of data points.

Easy to Draw

As opposed to line graphs, a dot plot is easy to construct. This is one of the major differences between the two ones that are lines can deviate while being drawn so does give unrelated meanings. While the dotted arrangement is up to the mark while giving appropriate accurate meanings to the data.

Conclusive Summary

To summarise our discussion we reach the conclusion that a dot plot is a child of a bar graph for representing the scattered distribution of numerical variables where each dot shows a value. We prefer a dot plot over line graphs when a dataset is with scattered values and data shown. So the line graph is limited and complex in context with construction while the dot line graph is easy and elaborative.

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