BUS1200 (SOPH-0017) Foundations of Statistics - Issues with Performing Experiments – Flash Cards
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BUS1200 (SOPH-0017) Foundations of Statistics - Issues with Performing Experiments – Flash Cards
Question Answer 1. What is bias? Answer Bias is an error caused by the experimental design that leads to measurements that are not representative of the population. It can result in over- or underestimation of the parameters of a population. 2. How does bias affect the outcome of an experiment? Answer Bias can distort the results of an experiment and make them unreliable. It can lead to inaccurate conclusions about the relationship between variables being studied. 3. What are extraneous variables? Answer Extraneous variables are variables that are not controlled or accounted for in the experimental design. They can influence the response variable being studied and cause a misinterpretation of the cause-and-effect relationship between variables. 4. How do extraneous variables impact an experiment? Answer If extraneous variables are not considered, they can introduce error and bias into the results of an experiment. They may confound the relationship between the variables being studied and lead to misleading or incorrect conclusions. 5. What is selection bias? Answer Selection bias occurs when individuals or things are not randomly assigned to groups in an experiment. This can result in under- or overrepresentation of certain characteristics, leading to biased results that may not be representative of the larger population being studied. 6. Give an example of selection bias. Answer An example of selection bias is a telephone poll where only landline numbers are chosen, excluding individuals who only have cell phones. This underrepresentation of a specific group can introduce bias into the results. 7. What is participation bias? Answer Participation bias is a type of selection bias that occurs when participants have a choice of whether to participate in an experiment. Those who choose to participate may have different characteristics from those who choose not to, potentially influencing the results of the experiment. 8. Provide an example of participation bias. Answer An example of participation bias is when individuals are incentivized to participate in a survey with the chance to win a gift card. This incentive may attract individuals with different characteristics than those who are not interested in participating, leading to biased results. 9. What is the relationship between bias and extraneous variables?
BUS1200 (SOPH-0017) Foundations of Statistics - Issues with Performing Experiments – Flash Cards
Question Answer Answer Bias can result from the presence of extraneous variables that were not accounted for in the experimental design. These variables can introduce error and distort the relationship between variables being studied, leading to biased results. 10. Why is it important to consider bias and extraneous variables in the experimental methods process? Answer Considering bias and extraneous variables is crucial because they can significantly impact the validity and reliability of experimental results. Ignoring these factors can lead to misleading or incorrect conclusions about cause-and-effect relationships between variables. 11. Define bias. Answer Bias refers to an error caused by the experimental design that leads to measurements that are not representative of the population, resulting in over- or underestimation of population parameters. 12. Define extraneous variables. Answer Extraneous variables are variables that are not controlled or accounted for in the experimental design but can influence the response variable being studied, potentially causing a misinterpretation of the cause-and-effect relationship between variables. Terms to Know:
1.
Bias: An error caused by the experimental design creating a situation where measurements are not representative of the population, leading to over- or underestimation of population parameters. 2.
Extraneous Variables: Variables that are not controlled or accounted for in the experimental design but can impact the response variable being studied. 3.
Selection Bias: A type of bias that occurs when individuals or things are not randomly assigned to groups in an experiment, resulting in under- or overrepresentation of certain characteristics. 4.
Participation Bias: A special type of selection bias that occurs when participants have a choice of whether to participate in an experiment, leading to potential differences in characteristics between participants and non-participants.
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