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A Classification Table (aka a Confusion Matrix) describes the predicted number of successes compared with the number of successes actually observed. Similarly, it compares the predicted number of failures with the number actually observed.

In a well-designed database, each table stores data about a particular subject, such as employees or products. A table has records (rows) and fields (columns). Fields have different types of data, such as text, numbers, dates, and hyperlinks.

You will see tables in use when shopping for cell phone plans and you will see graphs in use when you research population growth. These are just a few examples of how they are used in the real world. In algebra, both are used as visual representations of functions and data.

8.1. Parts of a Table Header row(s) Column groupings. Body row(s) Header cells. Body cells. Rows. Columns. Footer row(s)

They can be used to make sure tasks that need to be accomplished are achieved. Tables are also a great resource for self-reflection, assessment, and goal setting because they arrange information in a short form that allows one to determine if progress has been made (Tip: using checkboxes increases the benefit of this).

There are many common kinds of tables, including demographic characteristics tables, correlation tables, factor analysis tables, analysis of variance tables, and regression tables.

A classification table, also known as a confusion matrix, is a table that summarizes the performance of a classification model. It displays the number of true positives, false positives, true negatives, and false negatives for a given set of predictions.

Create Classification Tables Right-click the fact table column in the Target View and select Create Classification. The Create Classification dialog displays. Enter a name for the classification table and click OK. The table name must be unique (it cannot be the same as any existing tables in the source database).

Tables are used to organize data that is too detailed or complicated to be described adequately in the text, allowing the reader to quickly see the results.

The statistical tables may further be classified into two broad classes namely simple tables and complex tables. A simple table summarizes information on a single characteristic and is also called a univariate table.

The classification table is a method to evaluate the logistic regression model. In this table the observed values for the dependent outcome and the predicted values (at the selected cut-off value) are cross-classified.

Tables and graphs are a useful tool for organising available data for decision making. They are also a useful way of providing evidence to convince others towards a particular argument. Thinking: Analysing and synthesising data from various sources is an important part of developing arguments and decision making.