Overview of the Bone Structure

THE STRUCTURE OF THE SKIN AND FUNCTIONS

WHAT IS A SCATTERPLOT?

What is a scatter plot? 

Scatter plot is a mathematical technique that is used to represent data. Scatter plot is also called a Scatter Graph or Scatter Chart. It uses dots to describe two different numeric variables. The position of each dot on the horizontal and vertical axis indicates values for an individual data point. A scatter plot helps find the relationship between two variables. This relationship is referred to as a correlation.

Types of Scatter Plot

 Based on the correlation, scatter plots can be classified as follows.

• Scatter Plot for Positive Correlation
• Scatter Plot for Negative Correlation
• Scatter Plot for Null Correlation (No correlation)

Scatter Plot for Positive Correlation

A scatter plot with increasing values of both variables can be said to have a positive correlation. In other words, the two variables change in the same direction. As the x-variables increase, the y-variables also increase. For example, as the temperature gets more and more higher in the summer, the amount of ice cream eaten by people increases.

Scatter Plot for Negative Correlation

A scatter plot with an increasing value of one variable and a decreasing value for another variable can be said to have a negative correlation. In other words, as the x-values increase, the y-values decrease.

Scatter Plot for Null Correlation

A scatter plot with no clear increasing or decreasing trend in the values of the variables is said to have no correlation. Here the points are distributed randomly across the graph. 

QUESTION FOR TYHE DAY

Correct answer: Linear association with bivariate data with negative correlation.

Explanation:

We are comparing two variables, one on the 𝑥-axis and the other on the 𝑦-axis. So, this is bivariate data.
We can draw a line coming as close as possible to all points. This is known as the line of best fit or trend line, and it shows us that a linear association is a good fit for the data. As we increase the independent variable, 𝑥-axis, there is a decrease in the dependent variable, 𝑦-axis. A decrease in 𝑦 values as we increase 𝑥 values means that there is a negative correlation between the variables. So, the graph shows a linear association with bivariate data with negative correlation.