Weight : as height increases, weight tends to increase as well The value of Y increases as the value of X increases.Į.g Temperature vs Ice Cream Sales: on hot days, ice cream sales tend to be higherĮ.g Height vs. ![]() Weight: as height increases, weight tends to increase as well The value of Y increases slightly as the value of X increases.Į.g Height vs. ![]() Scatter Diagram Correlation Patterns Correlation Pattern Scatter diagrams are often used in regression analysis to visually assess the relationship between variables and check assumptions. Comparing data sets: When you have two sets of data, plotting them on the same scatter diagram can help to visually compare their relationships.Checking assumptions: Scatter diagrams are commonly used in regression analysis to check assumptions, such as linearity and homoscedasticity (constant variance of residuals).Identifying patterns: By observing the distribution of data points on the plot, you can identify any underlying patterns, clusters, or trends in the data.Outliers can have a substantial impact on statistical analyses and might require special consideration. Detecting outliers: Scatter diagrams can quickly reveal outliers, which are data points that deviate significantly from the general pattern.If the points on the plot tend to form a pattern, it indicates that the variables may be correlated. Visualizing correlation: Scatter plots help to assess the strength and direction of the relationship between two variables.Here are some common reasons why we use scatter plots: ![]() The main purpose of using scatter diagrams is to identify the nature of the relationship between two variables.
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