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# FM Categorical Variable

## 2.4 Scatterplots and Association between Numerical Variables

### Scatterplots

• Scatterplots are used to visualise data with explanatory and response variables.
• They consist of an x-y axis with each datapoint represented as a dot above its x-value and to the right of its y-value.
• Scatterplots can be used to see relationships between variables. These relationships can be described in terms of form, direction and strength.

Example

### Form

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## 2.3 Relationships between Numerical and Categorical Variables

### Discussing Relationships between Numerical and Categorical Variables

• Begin with context: what does the data represent?
• Compare frequencies between the categories of the categorical dataset.
• Compare the numerical data corresponding to each category on the basis of shape, spread, centre and presence of outliers.

Note: if you cannot remember how to choose appropriate measures for centre and spread, revise the notes for 1.6 Describing Numerical Distributions.

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## 2.2 Relationships between two Categorical Variables

### Discussing Associations between Categorical Datasets

• Remember to begin with context: what does the data represent?
• When analysing categorical datasets, try to find correlation, or lack of, between categories.
• You must also consider what this means in the context of the data. Does one cause the other? Do they tend to occur together? Is this the result of poor sampling practices?
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## 2.1 Response and Explanatory Variables

### Explanatory Variable

• The explanatory variable (EV) is the variable used to explain or predict another variable (the response variable).
• By convention, the explanatory variable is plotted along the x-axis of a graph, if it is numerical.

### Response Variable

• The response variable (RV) is the variable which is explained or predicted by the explanatory variable.
• By convention, the response variable is plotted along the y-axis of a graph, if it is numerical.

Note: both explanatory and response variables can be either categorical or numerical variables.

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