Terms and definitions from all courses

Set(): A function that takes an iterable as an argument and returns a new set object


shape: A NumPy attribute used to check the shape of an array


Shrinkage: (Refer to learning_rate)


Simple random sample: A probability sampling method in which every member of a population is selected randomly and has an equal chance of being chosen Silhouette analysis: The comparison of different models’ silhouette scores Silhouette score: The mean of the silhouette coefficients of all the observations in a model Simple linear regression: A technique that estimates the linear relationship between one independent variable, X, and one continuous dependent variable, Y Simple random sample: A probability sampling method in which every member of a population is selected randomly and has an equal chance of being chosen


Single: The minimum pairwise distance between clusters
Slicing: A method for breaking information down into smaller parts to facilitate efficient examination and analysis from different viewpoints
Slope: The amount that y increases or decreases per one-unit increase of x
Snowball sample: A method of non-probability sampling that involves researchers recruiting initial participants to be in a study and then asking them to recruit other people to participate in the study
Sorting: The process of arranging data into a meaningful order for analysis
Standard deviation: A statistic that calculates the typical distance of a data point from the mean of a dataset
Standard error: The standard deviation of a sample statistic


Standard error of the mean: The sample standard deviation divided by the square root of the sample size
Standard error of the proportion: The square root of the sample proportion times one minus the sample proportion divided by the sample size Standardization: The process of putting different variables on the same scale