Statistics: Types of Data

Continuous Data

• Continuous data represents measurements that can be divided into smaller and smaller units.
• Examples of continuous data include:
  • Height
  • Temperature
  • Time
  • Distance
• Continuous data allows for mathematical operations, such as addition.
• Statistical techniques can be used to analyze continuous data.

Categorical or Qualitative Data

• Qualitative data describes qualities or characteristics that are non-numerical.
• It consists of categories or labels that represent different groups or characteristics.
• Examples of qualitative data include:
  • Colors
  • Types of animals
  • Survey response options
• Qualitative data cannot be ordered or mathematically measured.
• It can be organized into categories for analysis.
• This type of data deals with characteristics that are observed subjectively, such as smell or taste.

Nominal Data

• Nominal data labels variables without a numerical value.
• It is classified without any order or rank.
• It is the lowest level of measurement in statistics.
• It is often represented using pie charts.

Ordinal Data

• Ordinal data represents categories that have a natural order or ranking.
• It is a higher level of measurement than nominal data.
• Examples of ordinal data include:
  • Levels of agreement (Strongly disagree, Disagree, Neutral, Agree, Strongly Agree)
  • Educational attainment (High school diploma, Bachelor's degree, Master's degree, Doctoral degree)

Primary Data Collection Methods

• Primary data is obtained directly from the original source.
• Common primary data collection methods include:
  • Surveys
  • Interviews
  • Observations
  • Experiments
  • Focus groups
  • Questionnaires
  • In-depth Interviews
  • Case studies
  • Diaries or journals
  • Photography and video
  • Surveillance and Sensor data
  • GPS (Geospatial Data)

Secondary Data Collection Methods

• Secondary data is information collected by someone other than the user.
• Examples of secondary data include:
  • Magazine articles
  • Newspaper articles
  • Books
  • Journals
  • Government publications
  • Historical documents.

Data Collection Tools

• Common data collection tools include:
  • Questionnaires
  • Surveys
  • Interviews
  • Focus groups

Questionnaires

• Questionnaires collect data through a series of questions and prompts, providing a response from individuals or groups.
• Pros of questionnaires:
  • Cost-effective
  • Can be used in large numbers
  • Easy to visualize and analyze
  • Respondent identity is not revealed
  • Covers all areas of topics
• Cons of questionnaires:
  • Answers may not be honest
  • Does not produce qualitative data
  • May be incomplete
  • Respondent may have a hidden agenda
  • All questions cannot be analyzed

Forming a Questionnaire

• The number of questions should be as few as possible.
• Questions should be simple to understand.
• Questions should be arranged logically.
• Answers to the questions should be short.
• Questions regarding personal matters should be avoided.
• Clarifications should be provided as footnotes for any questions requiring them.
• Necessary instructions should be given to respondents.
• Questions requiring mathematical rigors should be avoided.
• Questionnaires should be visually appealing.
• Questions should be framed to allow cross-checking the validity of the information provided.

Types of Questionnaires

• Close-ended questions require a "yes" or "no" answer or have a limited set of answers.
• Open-ended questions cannot be answered with a "yes" or "no" response and allow respondents to provide detailed answers.

Surveys

• Surveys are used to measure information and insights from individuals or groups.
• They can be conducted online, via phone, through paper forms, or in person.
• Survey data is information gathered from a sample of respondents who completed a survey.
• Pros of surveys:
  • Accuracy is very high
  • Easily accessible information
• Cons of surveys:
  • Problems with evaluation
  • Difficulty in understanding

Research Journals

• Research journals are scholarly publications containing articles written by researchers, professors and other experts.
• They are intended for an academic or technical audience.

Interviews

• Interviews are face-to-face conversations between two individuals with the purpose of collecting information for research purposes.
• They are a common way to gather qualitative data and gain deeper insights from individuals or groups.
• Interviews involve engaging in direct conversation with participants to explore their experiences, opinions, and perspectives on specific topics.
• Pros of interviews:
  • In-depth information
  • Freedom of flexibility
  • Accurate data
• Cons of interviews:
  • Time-consuming
  • Expensive to collect

Types of Interviews

• Structured interviews: Verbally administered questionnaires with a set of questions and answers.
• Semi-structured interviews: Include key questions to cover areas of exploration, with some flexibility to deviate from the questions.
• Unstructured interviews: Offer in-depth exploration, allowing for a wide range of information collection.

Focus Groups

• Focus groups are a qualitative research method involving facilitated group discussions to gather insights, perceptions, and opinions on a specific topic.
• This method captures group dynamics and interactions among participants.
• Focus groups are a preferred technique in marketing, library science, social science, and user research.
• Pros of focus groups:
  • Detailed information
  • Cost-effective compared to one-on-one interviews
  • Speed and efficiency in results
• Cons of focus groups:
  • Limited depth in covering details
  • Potential for bias
  • Requires interviewer training
  • Researcher has limited control over outcome
  • A few vocal voices can dominate the discussion
  • Difficulty in assembling a fully inclusive group