Which option should you use if your data is approximately symmetric or approximately normal?
Mean and standard deviation
If your data is approximately symmetric or approximately normal, you should use measures of central tendency such as the mean or median, and measures of spread such as the standard deviation or variance.
The mean is often used to describe the central tendency of data that follows a normal or symmetric distribution. The median is also a good option if there are outliers or the data is skewed, as it is less affected by extreme values.
To describe the spread of the data, you can use the standard deviation or variance. The standard deviation is a measure of how much the data deviates from the mean, and is useful for describing the variability of normal or symmetric data.
Additionally, you can also use graphical tools such as histograms or boxplots to visualize the distribution of the data and identify any outliers or deviations from the normal or symmetric pattern.
More Answers:
The Mean: A Comprehensive Guide To Measuring Central TendencyUsing Non-Parametric Tests: Alternatives To Parametric Approaches In Analyzing Skewed Or Outlier-Heavy Data
Central Tendency And Spread: The Role Of Median And Iqr In Box Plots