Collecting Data 1 Flashcards
Why is data important in statistics?
Data is fundamental in statistics as it allows us to perform analyses, make decisions, and draw conclusions based on empirical evidence.
What are the two main ways of obtaining data?
The two main ways of obtaining data are:
- Primary Data Collection: Collecting data yourself.
- Secondary Data Collection: Using data collected by someone else.
What is primary data?
Primary data is information gathered directly through your own research efforts, where you control the data collection process.
What are the advantages of collecting primary data?
The advantages include:
- Control over what data is collected and how it is collected.
- The ability to tailor data collection to meet specific needs and objectives.
- Reliable and accurate
- Up to date
What are some methods of collecting primary data?
Methods include:
- Questionnaires: Surveys where participants answer a series of questions.
- Observations: Recording information based on direct observation.
- Experiments: Conducting experiments to observe outcomes under controlled conditions.
- Interviews
- Focus groups
What are the challenges associated with collecting primary data?
Challenges include:
- Cost: It can be expensive in terms of time, money, and resources.
- Planning: Requires proper planning to ensure useful data collection. Poor planning can lead to inadequate data and potentially necessitate re-collection.
- Time-consuming
- Non-Responses: Ignoring or excluding certain responses can skew the data and lead to inaccurate conclusions.
What is secondary data?
Secondary data is information that has already been collected by others and made available for use.
What are some common sources of secondary data?
Sources include:
- Large Organizations: Research data in areas like demographics and medicine.
- Governments: Public data on health, economics, transportation, etc.
- Academic Journals and Books: Traditionally accessed through libraries, now widely available online.
What are the advantages of using secondary data?
Advantages include:
- Accessibility: Easier to obtain and often either freely available or inexpensive.
- Time-Saving: Eliminates the time required to collect data yourself.
What challenges might you face when using secondary data?
Challenges include:
- Data Relevance: The data may not perfectly suit your needs due to unknown assumptions, different questions asked, and handling of non-responses.
- Quality and Credibility: It is essential to verify the reliability of the data source, especially with vast information available online.
How can you ensure the quality of the data you use?
To ensure data quality, you should focus on:
- Validity: Ensure the data accurately represents what you aim to measure.
- Reliability: Ensure the data collection process is consistent and repeatable.
- Relevance: Ensure the data is pertinent to your research questions.
- Transparency: Clearly document and understand the methodology used in data collection.
What are the 4 key stages in statistical investigation?
- Pose a question
- Collect relevant data
- Analyse the data
- Interpret the results
How do you pose a question?
By first identifying:
* What the data is wanted for
* what data is needed
* the best way to collect it
Why is it important to have a well-defined research question?
A well-defined question narrows the scope of the investigation, ensuring that the subsequent stages are focused and relevant. It also ensures the data collected is pertinent to the problem, saving time and resources.
What are the two main types of data collection?
The two main types are primary data and secondary data. Primary data is collected firsthand by the researcher through experiments, surveys, or observational studies. Secondary data is gathered from existing sources like databases, reports, and academic publications.
