you graph the points going downwards
A scatter plot that shows no correlation displays points that are randomly distributed without any discernible pattern, indicating that there is no relationship between the two variables. In contrast, a scatter plot that shows a negative correlation features points that trend downward from left to right, suggesting that as one variable increases, the other tends to decrease. The absence of a clear trend in a no-correlation plot contrasts with the consistent directional relationship observed in a negative correlation plot.
Can you split the name of this up somehow when you resubmit your question, so that an answerer can attempt to use the search facility on photobucket.com?
Positive correlation = the slope of the scattered dots will rise from left to right (positive slope) Negative correlation = the slope of the scattered dots will fall from left to right (negative slope) No correlation = no real visible slope, the dots are too scattered to tell.
A scatter plot shows a correlation when there is a discernible pattern in the distribution of data points, indicating a relationship between the two variables. If the points trend upward from left to right, it suggests a positive correlation, while a downward trend indicates a negative correlation. The strength of the correlation can be assessed by how closely the points cluster around a line or curve. If there is no apparent pattern, the variables are likely not correlated.
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.
A correlation exists in a scatter plot if there is a general trend in the outputs as inputs increase. If the outputs generally increase in value, then there is a positive correlation. If the outputs generally decrease in value, then there is a negative correlation.
A scatterplot with no correlation means that there is no relation between the two categories, a negative correlation means that the two categories have a relationship that as one gets greater the other gets smaller
Can you split the name of this up somehow when you resubmit your question, so that an answerer can attempt to use the search facility on photobucket.com?
A scatter plot.A scatter plot.A scatter plot.A scatter plot.
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Positive correlation = the slope of the scattered dots will rise from left to right (positive slope) Negative correlation = the slope of the scattered dots will fall from left to right (negative slope) No correlation = no real visible slope, the dots are too scattered to tell.
If Y increases as X increases, you are referring to a positive correlation. However, if Y falls as X increses, you have a negative correlation.
A scatter plot shows a correlation when there is a discernible pattern in the distribution of data points, indicating a relationship between the two variables. If the points trend upward from left to right, it suggests a positive correlation, while a downward trend indicates a negative correlation. The strength of the correlation can be assessed by how closely the points cluster around a line or curve. If there is no apparent pattern, the variables are likely not correlated.
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.
In a scatter plot, a positive correlation is indicated by points that trend upwards from left to right, suggesting that as one variable increases, the other does as well. A negative correlation is shown by points that trend downwards from left to right, indicating that as one variable increases, the other decreases. If the points are scattered randomly without any discernible pattern, it suggests no correlation between the variables. The strength and direction of the correlation can also be visually assessed by how closely the points cluster around an imaginary line.
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.
Scatter-plot shows correlation between two different variables (one on the y-axis, the other on x-axis). If there is linear correlation, the scatter-points form a straight line from zero (origo) to some direction. The more cloud-like distribution the scatter-plot does have, the less those variables in question have correlation or dependence with each other.