**What is a scatterplot and how does it help us?**

A) A scatterplot is a formula that fits a straight line to data points, which helps plot the data.

B) A scatterplot is a graph of paired (x, y) quantitative data. It provides a visual image of the data plotted as points, which helps show any patterns in the data.

C) A scatterplot is a table of paired (x, y) quantitative data sorted from least to greatest, which helps show the range of the data.

D) A scatterplot is a graph of paired (x, y) qualitative data. It provides an organized display of the data, which helps show patterns in the data.

**Answer Explanation**

**Scatter Plot**

The scatter plot is a chart type that is normally used to observe and visualize relationships between variables. The dots represent the values of the variables. Scatter plots make use of Cartesian coordinates to display the values of the variables in a data set. The positioning of the dots on the vertical and horizontal axis inform the value of the respective data point. Scattered plots are also known as scattergrams, scatter graphs, or scatter charts.

Using scatter plots, you can visually observe and analyze the relationship between variables. Scattergrams, scatter graphs, and scatter charts are other terms for scattergrams. On a scatter plot, data points or dots represent the individual values for each data point. They are also used to identify patterns when analyzed holistically. Scattered plots are commonly used to display the relationship between two variables and observe the nature of this relationship. Observed relationships can be positive or negative, non-linear or linear, and/or strong or weak.

Data points are plotted on a scatterplot using the x-axis and y-axis for each set of data, with the y-axis representing the other set of data. We can use scatterplots to visualize the relationship between two data sets. They can be used to identify patterns, trends, and correlations. In this way, we can see, for example, that as one set of data increases, the other set increases as well, or if the two sets of data have a strong positive or negative correlation. We can also identify any outlying data points that might be influencing the overall trend of the data by using scatterplots.

Scientific and statistical studies as well as financial and business data can all be analyzed using scatterplots. The relationship between two variables is often explored using them, such as the relationship between income and education, or the relationship between a company’s sales and its advertising budget.

An analysis of scatterplots can provide insight into trends in the data, such as positive correlations (where one variable increases, the other variable tends to decrease) and negative correlations (where one variable increases, the other variable tends to decrease). Aside from helping identify outliers, they can also help identify data points that differ significantly from the rest of the data and may be affecting the overall trend in a negative way.

Scatterplots can also be used to predict future data as well as to identify trends and correlations. We may be able to predict that increasing the advertising budget will increase sales if we see a strong positive correlation between the advertising budget and the company’s sales. As a visual and analytical tool, scatterplots help us visualize and analyze data, and they can aid in understanding the relationships between variables.

**Importance of Scatterplot**

- It is easier to see the correlation between two variables using a scatterplot. Using the x-axis and y-axis, it is easier to see the relationship between the variables.
- An outlier or anomaly in the data can be identified by scatterplots. If a point stands out from the rest, it can be investigated further.
- An upward trend in the data may indicate that there is a positive correlation between the variables, as can be seen in a scatterplot.
- A scatterplot can be used to make educated guesses about future values by understanding the relationships between variables.
- A scatterplot provides the ability to compare multiple data sets by creating multiple scatterplots on the same graph. This allows one to see how the relationships between variables differ across different data sets.

**Applications of Scatterplot **

- By plotting income on the y-axis and education level on the x-axis, a scatterplot can help visualize the relationship between income and education level in a population.
- By plotting weight loss on the y-axis and exercise on the x-axis, it is possible to see if there is a positive correlation between exercise and weight loss.
- By plotting blood pressure on the y-axis and age on the x-axis, scatterplots can be used to visualize the relationship between age and blood pressure.
- By plotting respiratory illness on the y-axis and air pollution on the x-axis, it can be seen if the two variables are positively correlated.
- A scatterplot can be used to visualize the relationship between time spent studying and grades on a test by plotting grades on the y-axis and studying time on the x-axis.