Collecting-Data gcse Edexcel

You should be familiar with different methods of collecting data

You can use direct observation to collect data

• This means observing the things you are interested in and recording what you observe

  • For example to study pedestrians’ use of mobile phones you might observe people walking past a certain spot in a town and tally the numbers who are or aren’t looking at a mobile phone while they walk

• You will need an appropriate data collection sheet for recording your data

  • This will usually be a table or tally chart, with appropriate rows or columns for the data you are collecting

  • For the example above you could use a tally chart, with rows for ‘looking at a mobile phone’ and ‘not looking at a mobile phone’

• An advantage of observation can be not affecting the natural behaviour of the things you are observing

  • But a possible disadvantage is not having any control over the things you are studying

You can also conduct an experiment to collect data

• This is done to see how changes in one variable (the explanatory or independent variable) affect another variable (the response or dependent variable)

• It is important to control extraneous variables (see the ‘Extraneous Variable’ spec point)

• Different types of experiment (laboratory experiments, field experiments, and natural experiments) have different advantages and disadvantages

  • including different levels of control for extraneous variables

• Sometimes a pre-test will be used before starting on a full experiment

  • The intended experiment is run on a small sample

  • This may reveal any problems with the design of the experiment

  • And allow the problems to be fixed before the experiment is run for real

Simulation can be used to model events in the real world

• Data is collected from the model to predict what would happen in the real world

• This may be easier or cheaper than collecting real world data

• Random processes may be involved (including the use of random numbers)

  • For example say 23% of the UK population possesses a certain genetic marker

  • A two-digit random number generator could serve as a model ‘person’

  • A number from 00 to 22 means the ‘person’ has the genetic marker, and a number from 23 to 99 means they don’t

You can gather data from individuals using questionnaires or interviews

• These need to be used carefully to avoid bias or other possible issues

  • See the ‘Questionnaires & Interviews’ spec point

You can also use reference sources to collect secondary data

• e.g., government census data, online sources, etc.

  • Remember that the source of secondary data needs to be acknowledged

• See the ‘Types of Data’ revision note

You should know the advantages of different types of experiment for collecting data

Laboratory experiments

• Conducted in a controlled environment (it doesn’t have to happen in an official laboratory!)

  • For example studying people’s sleep patterns in a special room where lighting, temperature, bedding materials, etc. are all under the researchers’ control

• Advantages include

  • Easy to control extraneous variables

  • Easy to repeat the experiment under exactly the same conditions

• Disadvantages include

  • Test subjects may not behave naturally in the controlled environment

Field experiments

• Conducted in the subject’s usual environment, but with the researcher controlling the situation and certain variables

  • For example studying people’s sleep patterns in their own beds at home, but with the researchers providing specific types of pillow and deciding what time subjects should go to bed

• Advantages include

  • More likely than a laboratory experiment to show usual or natural behaviour

• Disadvantages include

  • Can’t control all extraneous variables

  • Harder to repeat the experiment under exactly the same conditions

Natural experiments

• Conducted in the subject’s usual environment, without the researcher controlling the situation or variables

  • For example studying people’s sleep patterns in their own beds at home, with the subjects using their own beds and bedding, going to sleep at their usual times, etc.

• Advantages include

  • More likely than a laboratory experiment to show usual or natural behaviour

• Disadvantages include

  • Can’t control any extraneous variables

  • Harder to repeat the experiment under exactly the same conditions

We say that data is reliable when repeated measurements give similar results

• i.e. if you collected the data again under similar circumstances you would get similar results

  • For example, using a scale to weigh some samples

  • It should give the same result if the same sample is weighed again

• The reliability of collected data is the extent to which this is true

We say that data is valid if it measures what it was intended to measure

• i.e. the data should be telling you what you think it is telling you

  • For example, using a questionnaire to assess participants’ stress levels

  • To be valid, scores from the questionnaire should agree with other accepted ways of measuring stress

• The validity of collected data is the extent to which this is true

Reliability and validity are both very important for collected data

• The more reliable and valid data is, the more we can trust any predictions or conclusions made from it

A questionnaire contains a set of questions that are used to collect data

• A person who completes a questionnaire is known as a respondent

You should know the difference between open and closed questions

An open question has no suggested answers, and a respondent can answer anything at all to them

• For example, ‘How do you think the current town council is doing?’

• Every answer can be different

  • so it can be hard to summarise or analyse the data as a whole

A closed question offers the respondent a number of answers to choose from

• For example, ‘The current town council is doing a great job. Choose one: ☐ Agree ☐ Disagree’

• It is possible to record how many people choose each response

  • This makes it easier to summarise and analyse the data

• Closed questions will often use an opinion scale

  • For example offering the options ‘strongly agree’, ‘agree’, disagree’ and ‘strongly disagree’

  • A problem with opinion scales is that most people tend to choose responses ‘in the middle’, so the data collected might be biased towards those middle values

There are a number of things to consider when creating a questionnaire

• Avoid leading questions

  • These are questions that suggest a particular answer

  • For example ‘How delighted are you with our awesome new product?’

    • This is ‘leading’ the respondent to give a positive answer

    • The responses collected are likely to be biased

• Make sure that options offered cover all possibilities

  • For example, ‘How many time per day do you use our app? ☐ 1 time ☐ 2 times ☐ 3-5 times’

    • This doesn’t offer ‘0’ or ‘more than 5’ as options

  • You may need to include options like ‘never’, ‘other’ or ‘I don’t know’

• Make sure any intervals given do not overlap

  • For example, ‘How much do you spend per month on widgets? ☐ £0 to £5 ☐ £5 to £10 ☐ More than £10’

    • ‘£5’ is included in the first and second options!

• Be sure to be specific about time frames

  • For example, ‘How many text messages do you send per week?’ is better than ‘How many text messages do you send?’

• Keep questions short

  • and use language that is simple and easy to understand

• Be careful about asking sensitive questions

  • i.e. questions about personal matters (age, etc.) or about things people may not want to discuss (‘How many times have you stolen things from shops?’)

    • People may not answer the questions

    • Or they may not answer them honestly

Sometimes a pilot survey will be used before giving the questionnaire to all the respondents in the intended survey

• The questionnaire is first given to a smaller sample of people

• This may reveal any problems with the design of the questionnaire

• And allow the problems to be fixed before the questionnaire is used for real

In interviews an interviewer asks the questions to the respondents and records their responses

• This can be done in person or by phone

• Advantages of interviews:

  • The response rate is higher

    • i.e. every person interviewed will tend to answer the questions

  • The interviewer can explain questions (if necessary)

  • The respondent can explain their answers

    • This avoids unclear or ambiguous answers being recorded

  • A good interviewer can help respondents feel more comfortable when answering sensitive questions

• Disadvantages of interviews:

  • Conducting interviews can take a lot of time

    • So interviews can take longer and be more expensive

  • The sample size will usually be smaller than when using questionnaires

    • This can make the sample less representative

  • Respondents may be less likely to be honest or to answer sensitive questions in an in-person interview

    • Or respondents may try to boast or to give the answers they think the interviewer wants to hear

  • There may be interviewer bias

    • This is when the opinions or expectations of the interviewer affect the answers given by the respondent

    • For example the interviewer may ask a question in a way that leads the respondent towards giving a particular answer

    • This can lead to biased results

Questionnaires will normally be given to people to fill in anonymously

• This can be a printed form or a form accessible online

• Advantages of questionnaires:

  • Respondents can answer questions in their own time

    • This can make the survey quicker and cheaper to run

  • Questionnaires can be sent to a large sample

    • This can make the sample more representative

  • Respondents may be more likely to be honest and to answer sensitive questions in an anonymous questionnaire

  • There is no interviewer bias

• Disadvantages of questionnaires:

  • The response rate is lower

    • People may not answer all the questions, or may not complete or return the questionnaire at all

  • A respondent may not understand the questions

  • A respondent’s answers may be unclear or ambiguous

Even in an anonymous questionnaire, people may not be willing to give honest answers to sensitive questions

• The random response method is a way to get better responses for these sorts of questions

• It uses some sort of random event (for example a coin flip) to determine how a question will be answered

For example, say you wanted to collect data on people using handheld phones while driving

• This is illegal in the UK

• So people may not be willing to admit that they have done it

You could ask the question in this form:

• “Have you ever driven while using a handheld phone?
  Flip a coin.
  If you get heads, then answer Yes.
  If you get tails, then answer honestly.”

• There is no way to know if a person answering yes really did drive while using a handheld phone, or whether they only answered yes because they flipped the coin and got heads

To estimate the response rate for a random response question:

• Estimate the number of people who answered a certain way because of the random event

  • For example, with a coin flip about half the people will get heads and half will get tails

• Remove that many responses from the data set

  • For the example used above, say 1000 people responded to the question

  • We would expect half of them to answer yes because they got heads on the coin

  • So remove 500 yes answers from the data set

• Perform your analysis on the remaining items in the data set

• See the Worked Example