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We need to find the difference between plots that show a strong correlation and plots that show a weak correlation.
The point of creating a scatter plot is to determine if there is a correlation. Correlation means the relationship between two quantities. For example, there is a correlation between how much a person studies and the grade they get on a test, but there is no correlation between how much money a person earns and what pets they own. In mathematics, correlation between data means that the points follow a pattern and go in the same direction. There are two types of correlation:
Positive: the trend is rising from left to right
Negative: the trend is decreasing from left to right
If the dots on the scatter plot do not follow a pattern, there is no correlation.
All correlations have two properties: strength and direction. The strength of the correlation is determined by its numerical value. The direction of the correlation is determined by whether the correlation is positive or negative.
The strength of the correlation indicates how strong the relationship is between the two variables. The strength is determined by the numerical value of the correlation. A correlation of 1, whether +1 or -1, is a perfect correlation. In perfect correlations, the data points lie directly on the fit line. The further the data is from the fit line, the weaker the correlation. A correlation of 0 means there is no correlation
If the value of correlation coefficient is nearer to to 1 or -1 , then there exist a strong correlation.
If the value of correlation coefficient is nearer to to 0 , then there exist a weak correlation.
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The data points are a little closer for a weak correlation, and you can see that there is some sort of relationship between these factors.
Data points for a strong correlation are in close proximity to one another, making it possible to build a line by imitating their pattern.
A statistic called correlation gauges how much two variables change in connection to one another.
Correlation and diversification, the idea that certain types of risk can be reduced by investing in assets that are not connected, are closely related concepts.
Correlation cannot determine whether x causes y or vice versa, or whether a third component is responsible for the association.
A scatter plot may make it easier to spot correlation, particularly when the variables have a non-linear but nevertheless significant association.
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