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Why do methods for data collection that do not rely on chance result in untrustworthy conclusions?
Non-random data collection can introduce bias, leading to results that are not representative of the population, which in turn produces untrustworthy conclusions.
What is a population in statistics?
A population consists of all items or subjects of interest in a study.
What is a sample in statistics?
A sample is a subset of the population selected for study.
What defines an observational study?
In an observational study, treatments are not imposed. Instead, data is examined retrospectively or collected prospectively without manipulating variables.
What is a sample survey?
A sample survey is a type of observational study that collects data from a sample to learn about the population from which the sample was taken.
How is an experiment different from an observational study?
In an experiment, treatments are assigned to experimental units to observe the effects, allowing for the investigation of cause-and-effect relationships.
When is it appropriate to generalize findings from a sample to a population?
Generalization is appropriate when the sample is randomly selected or otherwise representative of the population.
Why can a sample only be generalized to the population from which it was selected?
A sample reflects the characteristics of the population it was drawn from, so generalizations are only valid within that population.
Can causal relationships be determined from observational studies?
No, observational studies do not establish causation; they only suggest associations.
What is the difference between sampling with replacement and without replacement?
Sampling with replacement allows an item to be selected more than once, while sampling without replacement does not.
What is a simple random sample (SRS)?
A simple random sample is a sample in which every group of a given size has an equal chance of being chosen.
What is a stratified random sample?
A stratified random sample involves dividing a population into homogeneous groups (strata) and selecting a simple random sample from each stratum.
What is a cluster sample?
A cluster sample involves dividing the population into heterogeneous groups (clusters), randomly selecting clusters, and collecting data from all individuals within the chosen clusters.
What is a systematic random sample?
A systematic random sample selects members from a population using a random starting point and a fixed, periodic interval.
What is a census?
A census includes all items or subjects in a population.
What is bias in sampling?
Bias occurs when certain responses are systematically favored over others, leading to unrepresentative results.
What is voluntary response bias?
Voluntary response bias occurs when a sample is comprised entirely of volunteers, leading to a non-representative sample.
What is undercoverage bias?
Undercoverage bias occurs when part of the population has a reduced chance of being included in the sample.
What is nonresponse bias?
Nonresponse bias occurs when individuals who cannot be reached or refuse to respond differ systematically from those who do respond.
What is response bias?
Response bias occurs due to problems in the data collection process, such as confusing or leading questions.
Why are non-random sampling methods potentially biased?
Non-random sampling methods, like convenience or voluntary response sampling, do not use chance and may not represent the population accurately.
What are experimental units?
Experimental units are the individuals or objects to which treatments are assigned in an experiment.
What is an explanatory variable in an experiment?
An explanatory variable is a variable that is intentionally manipulated in an experiment to observe its effect.
What is a response variable?
A response variable is an outcome measured in an experiment after treatments have been applied.
What is a confounding variable?
A confounding variable is one that is related to both the explanatory and response variables, potentially misleading the results.
What key features should a well-designed experiment include?
A well-designed experiment should include comparisons, random assignment, replication, and control of confounding variables.
What is a completely randomized design?
In a completely randomized design, treatments are assigned to experimental units entirely by chance.
What are some methods for random assignment in experiments?
Methods include using a random number generator, drawing chips, or using a table of random values.
What is a single-blind experiment?
In a single-blind experiment, either the subjects or the researchers know which treatment is being administered, but not both.
What is a double-blind experiment?
In a double-blind experiment, neither the subjects nor the researchers know which treatment is being administered.
What is a control group?
A control group consists of experimental units that either receive no treatment or receive a placebo to compare against other treatments.
What is the placebo effect?
The placebo effect occurs when subjects experience a response to an inactive treatment.
What is a randomized complete block design?
In this design, treatments are randomly assigned within blocks, where each block consists of similar experimental units.
What is blocking in an experiment?
Blocking involves grouping similar experimental units together to reduce variability due to confounding variables.
What is a matched pairs design?
A matched pairs design is a special randomized block design where similar units are paired, and each pair receives both treatments.
How do experimental design choices impact results?
The choice of design depends on the research question, resources, and nature of the experimental units, influencing the reliability and scope of conclusions.
What is statistical inference
Statistical inference involves drawing conclusions about a population based on data collected from a sample.
Why is random assignment important in experiments?
Random assignment reduces the influence of confounding variables, allowing researchers to attribute differences in responses to the treatments.
What does it mean if a difference is statistically significant?
A statistically significant difference is one that is unlikely to have occurred by chance alone.
When can results from an experiment be generalized to a larger population?
Results can be generalized if the experimental units are representative of the larger population, which is more likely if they are randomly selected.
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