Planning Poker is an agile estimating and planning technique that uses consensus-based forecasting. Team members make estimates by playing numbered cards face-down on the table, instead of speaking them aloud. Once everyone has completed their estimates, the cards are revealed. If discrepancies occur, the high and low estimators explain their estimates, followed by another round of estimation. Eventually, convergence towards the 'correct' estimate happens. This method increases team interaction and reduces influences during the estimate.

T-Shirt Sizes is an effective technique used for relative sizing. The sizes are usually XS, S, M, L, XL, and tasks are grouped according to the size they most identify with. It aims at making the estimation process quicker and focuses on comparative order of magnitude, rather than on exact values. While it might not provide mathematical precision, it streamlines discussions, encourages teamwork, and reduces analysis-paralysis.

The Bucket System is a fast estimation technique. In this method, items are placed into 'buckets' or categories, which represent ranges of sizes. Examples might be sizes '1, 2, 4, 8' and so on. It is useful when you need to estimate a large number of items in a short time. The bucket system encourages comparative estimating where items are compared to each other and sized relative to each other based on their complexity, effort or size.

Relative Mass Valuation is a method that helps teams compare and estimate the size of user stories. All stories are placed in one group, with each subsequent story compared to the ones already inspected, and placed above (if larger), below (if smaller), or in-between. The process continues until all stories are ordered according to their size. This facilitates a more refined comparison, promoting a better understanding of the work involved and more accurate estimates.

Affinity Estimating is a technique that allows teams to quickly categorize a large amount of backlog items using a collaborative approach. The items will be grouped into categories that represent similar levels of effort or complexity. This technique helps to make the abstract concept of story points more concrete. During the process, the team discusses the stories, identifies potential risks or unknowns, and takes a consensus about the relative size.

The Fibonacci Sequence is an estimation method referencing a math sequence where each number is the sum of the two preceding ones, usually starting with 0 and 1. In Scrum, it's used as a way to estimate complexity or size. It provides a set of predefined values that the team can use to estimate story points. This technique acknowledges that the further out the prediction, the more uncertainty there is. Tasks that are considered larger in complexity and time are generally assigned a number from the Fibonacci sequence.

Dot Voting is a simple technique. Every team member gets a set number of 'dots' or votes that they can use to vote on user stories. Stories getting maximum votes are considered to have the highest priority or complexity. This method allows every individual of the team to participate actively and provide their input about the complexity, risk, or uncertainty involved with any user story. The higher the dot count, the larger the story point estimation becomes.

This is an anonymous, consensus-based estimation technique. It was developed by the RAND Corporation in 1940s and then adapted to software estimation in the 1970s (Barry Boehm). Steps included in this technique are: defining the requirements of work to be estimated, presenting the work for estimation, individual estimation, discussion of estimations, and repeating estimation till a consensus is achieved. It provides a way to combine expert opinions efficiently and anonymously while mitigating the possible influence or bias.

This technique is also called 'top-down estimating', and it requires a similar past work to make estimates for the current work. The comparison is made between the similar work and current work based on the size, weight, complexity, and duration. Even though it's not highly accurate, this technique is quickly conducted and less costly. This method works best when the team members doing the estimation have the experience with the tasks being estimated.

The Three Point Estimating technique is a statistical method which involves the use of multiple estimates to build a cost or schedule model for the project work. The team estimates with three points: Optimistic estimate (O), Most Likely (M), and Pessimistic (P). The project estimate can be calculated with a simple average or weighted average. This approach helps in getting more realistic estimates by reflecting the risk and uncertainty in the estimation process.