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Census and bias - Designing Studies

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Census and bias


A census is the procedure of conducting experiments to figure out information about members of a given population.
Doesn’t necessarily have to be human!

Explanatory Variables and Response Variables:
A response variable is the outcome of the experiment. This is typically the sort of outcome the experiment is concerned with finding. Think of it as the “response” of the experiment.

The explanatory variable is the variable that affects the response variable. Think of it as the “explanation” to the response variable.

There may be many explanatory variables in an experiment; typically it is better to find the single most relevant explanatory variable.

2 errors in conducting a census:
Sampling error and bias

Poorly implemented sampling techniques can lead a wide variety of Bias. A Bias is when the selection of a sample results in an unfair proportion of the sample having a tendency to favour certain outcomes.
i.e. Trying to decide what proportion of the population likes ice cream, but only asking kids

Sources of Bias:
There are many different ways in which a sample could result in bias, here are only a few of the most common sources of bias:

Response Bias:
In general people will not want to have unpopular opinions, so they may respond untruthfully when being face to face with an interviewer or if they were not anonymous for the survey. A good way to solve this issue is to ensure that all participants of a survey remain anonymous.
e.g. Doctors asking patients if they are following their orders (people will be tempted to lie to the doctor to maintain image or not incur the doctors wrath)

Selection Bias:
When selecting people for a survey make sure that your selection process doesn’t favour any of the population that has a specific preference for an outcome in your experiment. When collecting samples think about how you are gathering your data and make sure that it is fully randomized.
e.g. When polling the amount of families in an area it would be a selection bias to poll all the people entering a toy store (as more families will shop at a toy store).

Non-response Bias:
Sometimes individuals chosen for the sample in a census may be unwilling or unable to participate. A non-response bias is the bias that results when there are very low response rates and it becomes unclear what part of the population is participating in this survey.
e.g. If a mail survey was conducted asking people about what sorts of car they drive it is likely that few people would respond and it would be hard to know what proportion of the population this represents.

Voluntary Response Bias:
If individuals offer to participate in a survey they may have very strong feelings one way or the other about a specific matter.
e.g. A radio DJ asks his listeners to call in if they think Segway scooters are stupid and should be outlawed. This may encourage a small proportion of the population who hates Segway scooters to call in.

So basically make sure to choose your sample well using a good sampling technique and make sure there is no bias!
  • 1.
  • 2.
    Determining Response Variables and Explanatory Variables
    Classify the response variables and the explanatory variables from the following experiments:
  • 3.
    Classifying Bias
    For each of the following experiments below determine the sort of bias may be present , and provide a solution to overcoming the bias:
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Census and bias

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