Which term encompasses methods like linear regression, decision trees, and k-means clustering?

The term that encompasses methods such as linear regression, decision trees, and k-means clustering is "Machine Learning Algorithms." These methods all fall under the category of machine learning because they involve training a model using data to make predictions or classifications based on input features.

Linear regression is a supervised learning algorithm used primarily for regression tasks, where it establishes a relationship between dependent and independent variables. Decision trees are another supervised approach, commonly utilized for both regression and classification problems, enabling the model to make decisions based on feature values. K-means clustering is an unsupervised learning algorithm used for grouping data points into clusters based on their features, without prior labels or outputs.

Other terms like "Data Analysis Techniques," "Statistical Models," and "Predictive Analytics" do not adequately capture the essence of the mentioned methods in the context of learning from data and making predictions based on learned patterns. While these methods can play a role in data analysis and prediction, the specific grouping under machine learning algorithms is what makes this answer the most appropriate choice.