## Review: Basic Statistics

#### Basic Concepts

• Stats for characterizing collections of something - Descriptive statistics
• Variables or constants: instances
• A random variable is a numerical outcome of an experiment in which we measure an entity
• Accuracy, precision, resolution and significant digits: A result is considered accurate if it is consistent with the true or accepted value for that result. The precision of a result is an indication of how sharply it is defined. Accuracy is a measure of reliability, and is the difference between the True Value of a measured quantity and the Most Probable Value which has been derived from a series of measures. Precision is a measure of repeatability, i.e. the degree of agreement between individual measurements of a set of measurements, all of the same quantity. Resolution. This is the smallest interval measurable by an instrument.
• Independence of datapoints, Pseudoreplication,
• Degrees of freedom
• match Distributions and VariableTypes
• Parametric statistics make assumptions about distributions. They are more powerful as long as the asumtptions are not violated
• Central Tendency: Mean
• Dispersion: variance, standard deviation, standard error
• Shape: Kurtosis, Skewness
• Non-parametric statistics do not make assumptions about the distribution.
• Central tendency: median
• Dispersion: minimum, maximum, range, quartiles, interquartile range, quantiles, percentiles