Cluster sampling is a method where the population is divided into groups, or clusters, often based on geographic boundaries. When these clusters are geographic areas (like city blocks or districts), the method is commonly known as area sampling. It is a practical approach when a complete list of individual elements is unavailable.

Random numbers are used to map selections onto a 'random space' or sample space, ensuring that every element has an equal probability of being chosen. This process eliminates selection bias and ensures the resulting sample is representative of the population under study.

In systematic sampling, the population is ordered, and a starting point is selected at random. The sampling interval 'k' is determined by dividing the total population size (N) by the desired sample size (n). Every kth element is then selected from the list to form the sample.

Primary data refers to original information gathered directly by the researcher through methods such as surveys, interviews, or experiments. Since this data is collected specifically for the current investigation, it is considered 'first-hand' information, as opposed to secondary data, which is obtained from existing sources or previously published records.

Data is categorized based on its origin. Primary data is collected firsthand by the researcher for a specific purpose. Secondary data refers to information that has already been collected by someone else for a different purpose and is now being utilized for the current study.

Data generated within an organization for operational or accounting purposes is considered internal data. When this data is used for subsequent analysis or reporting rather than its original primary purpose, it is classified as internal secondary data. It is 'secondary' because it was originally collected for administrative or operational record-keeping.

Primary data refers to information collected by the researcher or agency directly from the source for the purpose of their specific study. Since the agency is using the data they gathered themselves, it remains in its original, primary form.

Data classified by collection method is typically categorized as either primary or secondary data. Since neither 'row data' (likely a typo for raw data), 'grouped data', nor 'quantitative data' refers to the collection method itself, 'None of these' is the correct classification within the provided options.

Primary data refers to original information collected by a researcher specifically for a current study. Since it has not been processed or summarized, it is considered raw and unorganized, unlike secondary data which has been previously collected by others.

Internal secondary data refers to information that already exists within an organization, having been collected for purposes other than the current research project. Examples include sales records, accounting data, and customer databases generated during daily business activities.