Relative sizing is a technique in Agile Estimation where the size of a user story is compared to other stories to determine its level of complexity. It assumes that estimating the size for each story individually is harder than comparing them with one another. Relative sizing uses a points system, often composed of the Fibonacci Sequence, T-shirt sizes, or powers of 2 to allocate relative weight to each story. Teams can use this method during backlog refinement meetings to ensure accurate estimations, prioritize work, and improve capacity planning. It encourages open discussions and relies on the collective wisdom of the team, fostering team collaboration and knowledge-sharing.

Planning Poker is a consensus-based estimation technique where team members independently estimate effort or complexity of user stories by playing numbered cards. The deck represents the Fibonacci sequence, T-shirt sizes, or powers of 2. First, the product owner presents a user story, and after discussing it, each member selects a card representing their estimate. All cards are revealed simultaneously, and the outliers need to explain their rationale. Discussions help team members refine their understanding of the story, and the process is repeated until a consensus is established. Planning Poker promotes unbiased estimations, reduces groupthink, and uncovers hidden complexities or misunderstandings about the requirements.

The Wideband Delphi method is a structured, iterative group estimation technique that aims to produce accurate and unbiased estimates for the effort required to complete tasks. Team members anonymously estimate story sizes in several rounds, with feedback and discussion between each round. As the group shares knowledge and narrows the range of estimates, the resulting consensus tends to be more accurate than individual estimates. The method highlights differing perspectives and leverages group wisdom. It focuses on overcoming estimation biases, encourages input from all team members, and fosters better understanding of requirements by identifying risks and unidentified activities.

Affinity Estimation is a technique used to estimate the size of a large backlog quickly and collaboratively. It involves the whole team, which initially reviews and discusses the entire backlog. Then, team members sort user stories into groups or columns based on their relative sizing without assigning specific numbers yet. Each column represents a size such as small, medium, or large. Team members can move stories between columns until a consensus is reached. At the end, numeric point values are assigned to each level. Affinity Estimation enables the entire team to estimate work effort collectively, provides high-level sizing for long-term planning, and promotes shared understanding of the backlog contents and priorities.

T-Shirt Sizing is a simple and intuitive technique used to estimate the relative size of tasks or user stories. It uses clothing sizes – XS, S, M, L, XL, XXL – to represent the level of complexity or effort required to complete a given story. Larger sizes represent more significant work, and smaller sizes represent less effort. Teams can assign numerical values to these sizes for a more quantitative analysis. T-Shirt Sizing is particularly useful for high-level, long-term planning and gathering quick estimates. It fosters conversation among team members, creates a shared understanding of the work scope, and avoids getting bogged down in detailed estimates that might require adjustments later.

Story Points is an abstract measure used to size user stories based on their overall complexity, unknowns, and effort required to complete the task. The higher the number of story points, the more complex and time-consuming the work is. Story points are an essential part of Agile Estimation as they allow the team to compare the tasks' difficulty levels and allocate their capacity accordingly. They are not tied to specific hours or days but provide an overall sense of effort involved, encouraging better discussions around the work and collaboration within the team.

Ideal Days is a time-based estimation unit used in Agile to measure the effort needed to complete a task or user story by assuming that the team member faces no distractions or obstacles. This unit provides an estimation of how long it would take in terms of perfect working days to finish the job. Implicit uncertainties are considered while assigning ideal days, making it more precise for capacity planning. Ideal Days help the team members allocate their efforts and time collaboratively while taking into account their knowledge and skills, thus enabling better collaboration within the Agile team.

Bucket System is an Agile estimation technique in which team members collaboratively assign tasks or user stories into predefined 'buckets' based on size, complexity, or effort. Each bucket represents a level or an estimate range (e.g., small, medium, large). The team compares user stories to one another and places them into the appropriate buckets. This process is a group activity, promoting discussions and aligning the team's understanding of work complexity and effort. The Bucket System provides a consistent and efficient way of bridging the estimation gap while avoiding typical biases found in other estimation methods.

Probabilistic Forecasting is a technique used in Agile estimation to predict the number of tasks or user stories that can be completed within a specified timeframe based on historical data and trends. This forecasting approach combines multiple probability distributions showing different possible outcomes rather than relying on a single fixed estimate (e.g., average velocity). Probabilistic Forecasting considers variations in team performance and external factors and provides more realistic, data-driven expectations. By using this forecast, Agile teams can account for uncertainties, minimize risks, and make more informed decisions for planning and prioritization.

Agile Analogies involves comparing the requirements and complexity of a new user story with those of previously completed stories in order to estimate effort. This method facilitates a quick, yet effective estimation by identifying similarities among tasks. Agile teams draw from their own collective memory and experiences to perform these comparisons. Analogy-based estimation provides a consistent framework for the team, allowing them to leverage their knowledge effectively. However, it requires continuous refinement, as new tasks and challenges arise in projects, and the team needs to remain up-to-date in order to ensure accurate estimations.

The Agile Estimation Scale is a key concept that establishes a common language within the team to estimate the size and effort required for tasks or stories. Some popular scales include linear, Fibonacci, or exponential scales. A linear scale assigns incremental increases in estimation (e.g., 1, 2, 3), while the Fibonacci sequence (e.g., 1, 2, 3, 5, 8) and exponential scales (e.g., 1, 2, 4, 8) assign estimation values that grow steadily. The choice of a scale should be based on the team's preferences and estimation capabilities. Agile teams should continuously refine the estimation scale to accommodate any updates on the project's requirements and better represent their estimation efforts.

In Agile Estimation, Confidence Levels provide an indicator of the team's certainty on the accuracy of their estimates. They represent a percentage value that reflects the likelihood of realizing a user story, task, or milestone within the estimated time and effort. This concept enables teams to communicate risks and uncertainties more effectively, allowing stakeholders and team members to make better-informed decisions about tasks and priorities. Confidence Levels can be calculated through past experiences, known risks, and issues that may affect the project's completion. It is essential for organizations to promote a culture of transparency and openness in order to ensure that Confidence Levels are used proactively and constructively.

Estimation Re-calibration is the iterative process of refining and adjusting the estimates provided for tasks or stories based on the latest information, changes in requirements, or team performance trends. This Agile Estimation concept is crucial for ensuring that the team adapts to new challenges that may emerge and aligns its expectations with the current project situation. Agile teams should regularly review and re-calibrate their estimations, leveraging retrospectives, stand-up meetings, and other forums to discuss and incorporate any learnings from completed iterations. Estimation Re-calibration ensures that the entire team is on the same page, embraces continuous learning, and improves its ability to provide more accurate estimations over time.