The (x,y) points can be approximated by a linear equation.
The (x,y) points are almost linearly related.
A scatter plot is commonly used to determine whether there is a relationship or trend between paired data. In a scatter plot, individual data points are plotted on a two-dimensional axis, with one variable represented on each axis. By observing the pattern of points, one can discern if there is a correlation, trend, or relationship between the variables. A clear pattern, such as a line or curve, indicates a potential relationship, while a random distribution suggests no significant correlation.
To accurately describe the type of relationship shown by a scatter plot, I would need to see the plot itself. Generally, scatter plots can depict various relationships such as positive, negative, or no correlation. A positive relationship indicates that as one variable increases, the other also increases, while a negative relationship shows that as one variable increases, the other decreases. If the points are randomly scattered without any discernible pattern, it suggests no correlation.
The line given to the values of y on a scatter plot is called the "line of best fit" or "regression line." This line represents the relationship between the variables and minimizes the distance between itself and the data points in the scatter plot. It helps to visualize trends and make predictions based on the data.
Correlation is an estimate of a linear relationship between two variables and takes no account of non-linear relationship. If the relationship is quadratic and the domain is symmetric about some point, the correlation will be zero. It is, thus possible for the points on the scatter plot to lie exactly on a parabola while the calculated correlation is zero. In such a case, it is easy to make a prediction despite no correlation.
A scatter chart displays individual data points on a Cartesian plane, showing the relationship between two continuous variables, while a line chart connects these points with lines to illustrate trends over time or ordered categories. Scatter charts are used to identify correlations or distributions, whereas line charts emphasize the progression and continuity of data points. In essence, scatter charts focus on the distribution of data, while line charts emphasize trends and changes.
A scatter plot
Points slope down as it moves to the right
It is called the line of best fit
A scatter plot.A scatter plot.A scatter plot.A scatter plot.
A scatter plot is commonly used to determine whether there is a relationship or trend between paired data. In a scatter plot, individual data points are plotted on a two-dimensional axis, with one variable represented on each axis. By observing the pattern of points, one can discern if there is a correlation, trend, or relationship between the variables. A clear pattern, such as a line or curve, indicates a potential relationship, while a random distribution suggests no significant correlation.
To accurately describe the type of relationship shown by a scatter plot, I would need to see the plot itself. Generally, scatter plots can depict various relationships such as positive, negative, or no correlation. A positive relationship indicates that as one variable increases, the other also increases, while a negative relationship shows that as one variable increases, the other decreases. If the points are randomly scattered without any discernible pattern, it suggests no correlation.
The line given to the values of y on a scatter plot is called the "line of best fit" or "regression line." This line represents the relationship between the variables and minimizes the distance between itself and the data points in the scatter plot. It helps to visualize trends and make predictions based on the data.
a graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present. Scatter plots are similar to line graphs in that they use horizontal and vertical axes to plot data points. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation .
Correlation is an estimate of a linear relationship between two variables and takes no account of non-linear relationship. If the relationship is quadratic and the domain is symmetric about some point, the correlation will be zero. It is, thus possible for the points on the scatter plot to lie exactly on a parabola while the calculated correlation is zero. In such a case, it is easy to make a prediction despite no correlation.
A scatter chart displays individual data points on a Cartesian plane, showing the relationship between two continuous variables, while a line chart connects these points with lines to illustrate trends over time or ordered categories. Scatter charts are used to identify correlations or distributions, whereas line charts emphasize the progression and continuity of data points. In essence, scatter charts focus on the distribution of data, while line charts emphasize trends and changes.
scatter plot. A scatter plot visually represents the relationship between two variables by displaying data points on a Cartesian plane, with one variable plotted along the x-axis and the other along the y-axis. This allows for easy identification of trends, correlations, or patterns between the sets of data. Additionally, a trend line can be added to further illustrate the relationship.
There is no such thing as a general pattern. Depending on the variables and the relationship between them, you can have points all over the plot, exactly on a straight line or a curve, or close to such a line or curve.