Understanding Data Types and Statistics

What are the two main types of data?

• Categorical data and Numerical data

• Static data and Dynamic data

• Primary data and Secondary data

• Qualitative data and Quantitative data

Define an attribute in the context of data types.

• An attribute is a type of data structure.

• An attribute is a characteristic or property of a data type that defines its data type and constraints.

• An attribute is a method used to manipulate data.

• An attribute is a synonym for a variable.

What is a binary attribute?

• A binary attribute is an attribute that can have only two possible values.

• An attribute that can have multiple values

• An attribute that can only be true or false

• An attribute that is always numeric

How do nominal attributes differ from ordinal attributes?

• Nominal attributes have no order, while ordinal attributes have a specific order.

• Nominal attributes are numerical, while ordinal attributes are categorical.

• Ordinal attributes have no order, while nominal attributes have a specific order.

• Nominal attributes can be ranked, while ordinal attributes cannot.

What characterizes numeric attributes?

• Numeric attributes are only used for categorical data.

• Numeric attributes cannot be used in statistical analysis.

• Numeric attributes represent quantitative values and support mathematical operations.

• Numeric attributes are always whole numbers.

Explain the difference between discrete and continuous attributes.

• Discrete attributes have distinct, separate values; continuous attributes can take any value within a range.

• Discrete attributes are always numerical; continuous attributes are always categorical.

• Discrete attributes are used for qualitative data; continuous attributes are used for binary data.

• Discrete attributes can take any value; continuous attributes have fixed values.

What is the mean, and how is it calculated?

• The mean is the smallest number in a set.

• The mean is the total of all numbers in a set.

• The mean is calculated by multiplying all numbers in a set.

• The mean is the average of a set of numbers.

Define median and its significance in data analysis.

• The median is the highest value in a data set, important for ranking data.

• The median is the sum of all values divided by the number of values, significant for its simplicity.

• The median is the middle value of a data set, significant for its robustness against outliers.

• The median is the average of a data set, useful for identifying trends.

What is mode, and when is it most useful?

• The mode is the most frequently occurring value in a data set, and it is most useful for identifying the most common item.

• The mode is the value that appears least frequently in a data set.

• The mode is only useful for numerical data sets.

• The mode is the average of all values in a data set.

Describe the range as a measure of dispersion.

• The range is the average of all values in a dataset.

• The range is the sum of the maximum and minimum values.

• The range is the difference between the maximum and minimum values in a dataset, indicating the extent of dispersion.

• The range is a measure of central tendency, not dispersion.