A ratio table is more like a pattern, where a data table has graphs.
A ratio table is more like a pattern, where a data table has graphs.
A data table is a list of statistics - a graph is a physical representation of the data.
Data comes in various sizes and shapes. Two of them are Interval and Ratio. Interval is a measurement where the difference between two values is meaningful and follows a linear scale. For example: in physics, temperature 0.0 on either F or C does not mean 'no temperature'; in biology, a pH of 0.0 does not mean 'no acidity'. Interval data is continuous data where differences are interpretable, ordered, and constant scale, but there is no 'natural' zero. Ratio is the relation in degree or number between two similar things or a relationship between two quantities, ordered, constant scale, with natural zero. Ratio data is interpretable. Ratio data has a natural zero. A good example is birth weight in kg. The distinctions between interval and ratio data are slight. Certain specialized statistics, such as a geometric mean and a coefficient of variation can only be applied to ratio data.
difference between Data Mining and OLAP
standard normal is for a lot of data, a t distribution is more appropriate for smaller samples, extrapolating to a larger set.
A ratio table is more like a pattern, where a data table has graphs.
A data table is a list of statistics - a graph is a physical representation of the data.
a table shows lists of data, a figure represents data in graphic form
A data table is a list of statistics - a graph is a physical representation of the data.
table is used to store the data where tablespace is a logical group of datafiles in a database sreedevimuddhu
Data comes in various sizes and shapes. Two of them are Interval and Ratio. Interval is a measurement where the difference between two values is meaningful and follows a linear scale. For example: in physics, temperature 0.0 on either F or C does not mean 'no temperature'; in biology, a pH of 0.0 does not mean 'no acidity'. Interval data is continuous data where differences are interpretable, ordered, and constant scale, but there is no 'natural' zero. Ratio is the relation in degree or number between two similar things or a relationship between two quantities, ordered, constant scale, with natural zero. Ratio data is interpretable. Ratio data has a natural zero. A good example is birth weight in kg. The distinctions between interval and ratio data are slight. Certain specialized statistics, such as a geometric mean and a coefficient of variation can only be applied to ratio data.
A chart is graphical, like a pie chart or a bar chart or a column chart. A table is an organised set of figures laid out in a table. You might use figures in the table to make a chart.
Interval Data: Temperature, Dates (data that has has an arbitrary zero) Ratio Data: Height, Weight, Age, Length (data that has an absolute zero) Nominal Data: Male, Female, Race, Political Party (categorical data that cannot be ranked) Ordinal Data: Degree of Satisfaction at Restaurant (data that can be ranked)
projecting: manipulating data to eliminate columns in a table. Joining: manipulating data to combine two or more tables.
A table is a collection of data that is organized into rows and columns. An index is a data structure that improves the performance of data fetch operations on a table. A table can exist as a standalone component but an index cannot. Indexes are built on top of tables and cannot exist without tables.
Normalizing data means eliminating redundant information from a table and organizing the data so that future changes to the table are easier. Denormalization means allowing redundancy in a table. The main benefit of denormalization is improved performance with simplified data retrieval and manipulation.
Delete statement deletes only the data from the table but you can apply some condition and only part of the data can be deleted. Truncate empties entire table. Drop deletes the table itself.