Spartial data shows specific location of geographical phenomena in terms of coordinates whilst attribute data is non-spatial in that it does not use coordinates but only show what is on a point, line and polygon.
by Wilkins Nyamangunda at Midlands State University(2:1)
Both graphs are used to summarize data. Pareto chart is used to establish differences between different groups of data and will assign relative importance to the different groups of data. Histogram is a data distribution graph that will determine if the particular set of data is symmetric or not.
A sample consists of a small portion of data when a population is taken from a large amount.
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Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.
In a database management system (DBMS), an attribute may describe a component of the database, such as a table or a field, or may be used itself as another term for a field. Commonly we can say that an attribute is a "propety" of a database field or its a characteristic or facet of the data field..
Metadata describes the characteristics of data, such as its format, source, and creation date, while attribute data provides specific values and properties of the data, such as the size, color, or location. Metadata is essentially data about the data, providing context and information on how to interpret and use the data, while attribute data is the actual content or values within the dataset.
Internal data refers to data generated, stored, and managed within an organization, such as sales figures or employee records. External data, on the other hand, is data obtained from outside sources, such as market research reports or social media analytics. Internal data is typically more specific to the organization itself, while external data provides broader industry or market insights.
Spatial data shows specific location of geographic phenomena in terms of coordinate whilst attribute data is non-spatial in that it does use coordinates but show what is on a point, line and polygon.
Attribute data refers to data that is qualitative in nature and can be categorized or classified into different groups based on characteristics or attributes. This type of data is typically non-numeric and includes traits such as colors, sizes, or categories. Example of attribute data include hair color, car type, or blood type.
difference in differences uses panel data to measure the differences
Operational data is used to run day-to-day business operations and is typically structured, detailed, and transactional. Decision support data, on the other hand, is used to analyze trends, patterns, and make strategic decisions. Decision support data is often aggregated, summarized, and historical.
difference in differences uses panel data to measure the differences
Range
An attribute describes something. A variable is something that can take on many values. An example in statistics for an attribute could be for a set of data the diameter. The attribute of the data could be the mean is 5 and standard deviation is 1/2. This describes the data. An example of a variable in statistics for the same set of data above is the diameter reading itself. The diameter will vary and is measured for each member of the population or sample, and may be 4.9, 5.1, 4.95, 5.05, etc. The value can vary on each part.
A cell attribute is the way in which the data inside the cell is displayed e.g. currency or percentage.
Primary data is data that is collected by the researcher. Secondary data is information that has been collected by someone other than the user.
So you can see the differences between each pease of data.