Table of Contents

- 1 How does a graph show the relationship between two variables?
- 2 How does graphing is used to represent data?
- 3 Which of the following is used to show correlation of two variables?
- 4 When the correlation is only studied between two variables is called?
- 5 How are independent and dependent variables plotted on a graph?
- 6 When do you look for relationships between variables?

## How does a graph show the relationship between two variables?

Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation . If the data points make a straight line going from the origin out to high x- and y-values, then the variables are said to have a positive correlation .

**How does a graph show relationship?**

The graphs we’ve discussed so far are called line graphs, because they show a relationship between two variables: one measured on the horizontal axis and the other measured on the vertical axis. Sometimes it’s useful to show more than one set of data on the same axes.

### How does graphing is used to represent data?

Graphs are a common method to visually illustrate relationships in the data. The purpose of a graph is to present data that are too numerous or complicated to be described adequately in the text and in less space. If the data shows pronounced trends or reveals relations between variables, a graph should be used.

**What kind of graph is best for showing the relationship between variables?**

Scatter charts are primarily used for correlation and distribution analysis. Good for showing the relationship between two different variables where one correlates to another (or doesn’t). Scatter charts can also show the data distribution or clustering trends and help you spot anomalies or outliers.

#### Which of the following is used to show correlation of two variables?

A scatterplot is a type of data display that shows the relationship between two numerical variables. Each member of the dataset gets plotted as a point whose x-y coordinates relates to its values for the two variables.

**What is the correlation between the two variables?**

The statistical relationship between two variables is referred to as their correlation. A correlation could be positive, meaning both variables move in the same direction, or negative, meaning that when one variable’s value increases, the other variables’ values decrease.

## When the correlation is only studied between two variables is called?

Correct Answer: Negative correlation. Q.5) When the correlation is only studied between two variables it is called. Positive correlation.

**How to describe the relationship between two graphs?**

Two graphs showing different relationships between two variables. Graph a actually just shows that the relationship between the two variables goes up and down then progressively increases. In general, the relationship is directly proportional. For example, Graph a may show the relationship between profit of a company through time.

### How are independent and dependent variables plotted on a graph?

The independent variable should be plotted on the x-axis. The dependent variable should be plotted on the y-axis. The graph of mass vs. volume places volume on the x-axis and the mass on the y-axis. The value of graphing this relationship is best understood by considering the following equation.

**Which is an example of a graph a?**

Graph a actually just shows that the relationship between the two variables goes up and down then progressively increases. In general, the relationship is directly proportional. For example, Graph a may show the relationship between profit of a company through time.

#### When do you look for relationships between variables?

Relationships between Variables. When you are looking for relationships between variables, what you are really doing is interpreting graphs or data by looking for patterns and trends. When you find the pattern or trend, you should then draw a line of best fit to represent it. The line of best fit is drawn to show the general trend from the data.