Final answer:
When assessing a continuous predictor variable in univariate analysis, it is important to examine its distribution, central tendency, dispersion, outliers, and relationship with outcomes.
Step-by-step explanation:
When assessing a continuous predictor variable in univariate analysis, there are several key factors to examine:
- Distribution: Analyze the distribution of the variable to understand its shape and spread. This can be done through visualizations such as histograms or box plots.
- Central tendency: Explore measures of central tendency such as mean, median, and mode to understand the typical or average value of the variable.
- Dispersion: Look at measures of dispersion like standard deviation, range, or interquartile range to assess the spread of the variable's values.
- Outliers: Identify any extreme values or outliers that may significantly impact the analysis or skew the results.
- Relationship with outcomes: Assess how the continuous predictor variable relates to the outcome variable. This can be done through correlation analysis or by examining the variable's effect in statistical models.