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Power Pivot can scale to process very large datasets in memory, which allows users to analyze datasets that would otherwise surpass Excel's limit of one million rows. [9] Power Pivot allows for importing data from multiple sources, such as databases (SQL Server, Microsoft Access, etc.), OData data feeds, Excel files, and other sources ...
The entity–relationship model proposes a technique that produces entity–relationship diagrams (ERDs), which can be employed to capture information about data model entity types, relationships and cardinality. A Crow's foot shows a one-to-many relationship. Alternatively a single line represents a one-to-one relationship. [4]
Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).
A pivot table is a table of values which are aggregations of groups of individual values from a more extensive table (such as from a database, spreadsheet, or business intelligence program) within one or more discrete categories. The aggregations or summaries of the groups of the individual terms might include sums, averages, counts, or other ...
P-Values: The p-value is a measure of the probability that the observed data would occur by chance if the null hypothesis were true. In replication studies p-values help us determine whether the findings can be consistently replicated. A low p-value in a replication study indicates that the results are not likely due to random chance. [6]
In order to do this one can use information theory concepts, which gain the information only from the distribution of probability, which can be expressed easily from the contingency table by the relative frequencies. A pivot table is a way to create contingency tables using spreadsheet software.
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, [1] [2] where all data are represented in terms of tuples, grouped into relations.
The function (,) is the Student's t-statistic for a new value , to be drawn from the same population as the already observed set of values . Using x = μ {\displaystyle x=\mu } the function g ( μ , X ) {\displaystyle g(\mu ,X)} becomes a pivotal quantity, which is also distributed by the Student's t-distribution with ν = n − 1 ...