An algorithm is a specific set of steps to perform a task. Design pattern is basically a recurring solution of same problem for a software application in a particular context which is somehow not related with algo, because algorithm is the step by step instructions to solve the problem.

In mathematics, a sequence. A sequence is an ordered list of numbers (or other elements like geometric objects), that often follow a specific pattern or function. Sequences can be both finite and infinite.

The sequence number is the byte number of the first byte of data in the TCP packet sent (also called a TCP segment). The acknowledgement number is the sequence number of the next byte the receiver expects to receive. The sequence number is always valid.

Pattern Rules. A numerical pattern is a sequence of numbers that has been created based on a formula or rule called a pattern rule. Pattern rules can use one or more mathematical operations to describe the relationship between consecutive numbers in the pattern. Descending patterns often involve division or subtraction …

Pattern recognition is the process of recognizing patterns by using machine learning algorithm. Pattern recognition can be defined as the classification of data based on knowledge already gained or on statistical information extracted from patterns and/or their representation.

two kinds

Ways to group (classify) patterns according to their traits, such as:

1. symmetry (for example, seventeen planar symmetry types)
2. layout type (diamond, drop, gradation, grid, spot, etc.)
3. layout arrangement (allover, foulard, etc.)
4. pattern directions (one-way, two-way, undirectional, etc.)

There are six main theories of pattern recognition: template matching, prototype-matching, feature analysis, recognition-by-components theory, bottom-up and top-down processing, and Fourier analysis. Each of the theories applies to various activities and domains where pattern recognition is observed.

A pattern is a series of data that repeats in a recognizable way. It can be identified in the history of the asset being evaluated or other assets with similar characteristics. Patterns often include the study of sale volume, as well as price.

There are three main types of trends: short-, intermediate- and long-term.

The main types of data patterns are level or horizontal, trend, seasonality and cycles.

These four components are:

• Secular trend, which describe the movement along the term;
• Seasonal variations, which represent seasonal changes;
• Cyclical fluctuations, which correspond to periodical but not seasonal variations;
• Irregular variations, which are other nonrandom sources of variations of series.

A pattern can be called a pattern only if it has been applied to a real world solution at least three times.

ANSWER. Study of data patterns. ANALYTICS. Collection and study of data (10) STATISTICS.

We often collect data so that we can find patterns in the data, like numbers trending upwards or correlations between two sets of numbers. Depending on the data and the patterns, sometimes we can see that pattern in a simple tabular presentation of the data.

Data Trends allow you to assess how your response data has changed over time. For example, you can use the same customer satisfaction survey for a year and create a new Collector each time you send it out. From Analyze Results, click the Data Trends tab, between Question Summaries and Individual Responses. …

Data can be either positively or negatively skewed. There are statistical techniques available which help us find out the probability distributions of skewed data too. However such techniques are not very well developed. This is because most of the sample data being collected usually follows the normal distribution.

Histograms and box plots can be quite useful in suggesting the shape of a probability distribution. Here, we’ll concern ourselves with three possible shapes: symmetric, skewed left, or skewed right.

The four ways to describe shape are whether it is symmetric, how many peaks it has, if it is skewed to the left or right, and whether it is uniform. A graph with a single peak is called unimodal. A single peak over the center is called bell-shaped. And, a graph with two peaks is called bimodal.

Uniform – The data is spread equally across the range. There are no clear peaks in these graphs, since each data entry appears the same number of times in the set.