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Questions and Answers
What is the purpose of biological research that involves experimentation?
What is the purpose of biological research that involves experimentation?
What does a correlation coefficient of 0 indicate?
What does a correlation coefficient of 0 indicate?
In the context of variable relationships, what is positive correlation?
In the context of variable relationships, what is positive correlation?
Which statistical type is the reaction time of an experiment considered?
Which statistical type is the reaction time of an experiment considered?
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What type of variables are blood type and test grade considered?
What type of variables are blood type and test grade considered?
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Which visualization tool is commonly used to represent correlations between variables?
Which visualization tool is commonly used to represent correlations between variables?
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What is the strength of a correlation with a coefficient of -0.8 interpreted as?
What is the strength of a correlation with a coefficient of -0.8 interpreted as?
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In a controlled experiment, what is the purpose of treatment and control groups?
In a controlled experiment, what is the purpose of treatment and control groups?
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What is the purpose of using a control group in an experiment?
What is the purpose of using a control group in an experiment?
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What distinguishes an independent variable from a dependent variable in an experiment?
What distinguishes an independent variable from a dependent variable in an experiment?
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In a double-blind study, who is oblivious to the assignment of subjects to treatment or control groups?
In a double-blind study, who is oblivious to the assignment of subjects to treatment or control groups?
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What is the role of control variables in an experiment?
What is the role of control variables in an experiment?
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Why is blinding important in experimental design?
Why is blinding important in experimental design?
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Which of the following best defines a dependent variable?
Which of the following best defines a dependent variable?
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What are extraneous variables, and how should they be treated in an experiment?
What are extraneous variables, and how should they be treated in an experiment?
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How does an independent variable (IV) differ from other variables in an experiment?
How does an independent variable (IV) differ from other variables in an experiment?
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What is the purpose of holding control variables constant in an experiment?
What is the purpose of holding control variables constant in an experiment?
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Which of the following best describes quantitative variables?
Which of the following best describes quantitative variables?
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What defines a continuous quantitative variable?
What defines a continuous quantitative variable?
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Which of the following is an example of a discrete quantitative variable?
Which of the following is an example of a discrete quantitative variable?
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In experimental design, which type of variable is manipulated to observe its effect on the dependent variable?
In experimental design, which type of variable is manipulated to observe its effect on the dependent variable?
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Which of the following describes an extraneous variable?
Which of the following describes an extraneous variable?
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What distinguishes an ordinal variable from a nominal variable?
What distinguishes an ordinal variable from a nominal variable?
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What is a characteristic of categorical variables?
What is a characteristic of categorical variables?
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Study Notes
Experimental Design
- Researchers can determine the extent to which an experimental outcome is attributable to a manipulated variable by comparing results between a treatment group and a control group.
- Single-blind study: Subjects don't know if they're in the treatment or control group.
- Double-blind study: Neither subjects nor researchers know group assignments.
- Blinding helps prevent bias caused by human expectations.
- Placebos are used in control groups to further reduce bias.
Experimental Variables
- An experimental variable is any factor that can change in an experiment.
- An independent variable (IV) is a factor that is purposefully manipulated by a researcher to determine its effect on another variable.
- IVs are explanatory or predictor variables, as their variation explains and/or predicts change in another variable.
- A dependent variable (DV) is a factor measured to observe the experiment's outcome.
- DVs are also called outcome or response variables, and changes typically occur after manipulation of the IV.
- Control variables are factors that could affect the DV, but are held constant by the researcher. They help ensure that changes in the DV are due only to manipulations of the IV.
Types of Experimental Variables
- Quantitative variables have numerical values representing quantities (e.g., length or count).
- Categorical variables have values assigned to distinct categories based on characteristics (e.g., blood type or educational level).
- Continuous quantitative variables can assume an infinite number of numerical values (e.g., height).
- Discrete quantitative variables take on specific numerical values determined by counting (e.g., number of vertebrae).
- Nominal categorical variables are simply categories without any inherent order (e.g., blood type).
- Ordinal categorical variables have categories with a specific order (e.g., educational level).
Relationships Among Variables
- Biological research primarily investigates relationships among variables, particularly cause-and-effect relationships.
- Correlation is a linear relationship between variables where they change together at a uniform rate.
- Positive correlation exists when both variables change in the same direction.
- Negative correlation exists when one variable changes in the opposite direction to the other.
- Correlation coefficient ranges from -1 to +1, representing the strength of the correlation.
- 0 indicates no linear relationship.
- Scatterplots are used to visualize correlations between variables.
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Description
Test your knowledge on experimental design, including key concepts like treatment groups, blinding techniques, and the roles of independent and dependent variables. Understand how these elements contribute to minimizing bias and accurately measuring experimental outcomes.