Ateneo De Manila University
bi 232 : Fundamentals of Biostatistics: Lecture 1 - An Overview of Descriptive Statistics
Study Guide , Definitions & Notes
In biostatistics, descriptive statistics are essential tools for summarizing and analyzing data. This
article provides an overview of key descriptive statistical measures, including measures of
central tendency, dispersion, distributions, and use of statistical software.
Central Tendency Measures
When describing a dataset, it is useful to identify a central or typical value. The main measures
of central tendency are the mean, median, and mode.
The arithmetic mean is found by summing all values and dividing by the number of values. It
provides a useful summary but can be swayed by extreme scores.
The median is the middle value when data is arranged numerically. It is less affected by outliers.
For odd-numbered data, it is the actual middle value. For even sets, it is the mean of the two
central values.
The mode is the most frequent value. It is useful for categorical data.
Each measure has advantages and disadvantages. The mean is easily understood but sensitive
to extremes. The median is robust but less precise. The mode only considers frequency.
Dispersion Measures
Dispersion refers to data spread. Common measures include range, interquartile range,
variance, and standard deviation. These quantify variability.
Range is the maximum minus minimum. Interquartile range measures the middle 50%. Variance
uses squared deviations from the mean. Standard deviation is variance's square root.
These indicate data dispersion. Higher values show more variability. Lower values indicate tight
clustering around the central tendency.
Distributions
Distribution shape provides insight. Symmetric distributions have similarly shaped sides.
Skewed are asymmetrically shaped.
bi 232 : Fundamentals of Biostatistics: Lecture 1 - An Overview of Descriptive Statistics
Study Guide , Definitions & Notes
In biostatistics, descriptive statistics are essential tools for summarizing and analyzing data. This
article provides an overview of key descriptive statistical measures, including measures of
central tendency, dispersion, distributions, and use of statistical software.
Central Tendency Measures
When describing a dataset, it is useful to identify a central or typical value. The main measures
of central tendency are the mean, median, and mode.
The arithmetic mean is found by summing all values and dividing by the number of values. It
provides a useful summary but can be swayed by extreme scores.
The median is the middle value when data is arranged numerically. It is less affected by outliers.
For odd-numbered data, it is the actual middle value. For even sets, it is the mean of the two
central values.
The mode is the most frequent value. It is useful for categorical data.
Each measure has advantages and disadvantages. The mean is easily understood but sensitive
to extremes. The median is robust but less precise. The mode only considers frequency.
Dispersion Measures
Dispersion refers to data spread. Common measures include range, interquartile range,
variance, and standard deviation. These quantify variability.
Range is the maximum minus minimum. Interquartile range measures the middle 50%. Variance
uses squared deviations from the mean. Standard deviation is variance's square root.
These indicate data dispersion. Higher values show more variability. Lower values indicate tight
clustering around the central tendency.
Distributions
Distribution shape provides insight. Symmetric distributions have similarly shaped sides.
Skewed are asymmetrically shaped.
