24 Questions
Why is a well-designed sample survey more advantageous than a census when the population is large?
All of the above
What is a crucial factor in ensuring the generalizability of study findings to a larger population?
Random selection of participants.
What is the primary advantage of experiments over observational studies in investigating causal relationships?
They allow for random assignment of subjects to treatment groups.
What is the purpose of conducting a sample survey?
To estimate the value of a population attribute.
What is the relationship between a sample statistic and a population parameter?
A sample statistic is an estimate of a population parameter.
Which type of study is more suitable for investigating causal relationships?
Experiment.
What is a major limitation of observational studies in terms of generalizability?
They lack random selection.
In a sample survey, what is the goal of selecting observations from a population?
To estimate the value of a population attribute.
What is the main reason why a census is not practical in most studies?
The cost and/or time required is too high.
What is the purpose of an experiment in data collection?
To understand cause-and-effect relationships.
Which method of data collection involves obtaining data from a subset of a population?
Sample survey
What is the main difference between a census and a sample survey?
The data is collected from every member of the population versus a subset of the population.
What is the purpose of determining the sample size in data collection?
To ensure that the sample is representative of the population.
Which method of data collection is used to estimate population attributes?
Sample survey
What is the benefit of using experiments in data collection?
It provides a controlled environment to study cause-and-effect relationships.
What is the importance of knowing how the data were collected in data analysis?
To know the method(s) of data collection, and the necessary screening on the data that has taken place.
What is a key difference between cluster sampling and stratified sampling?
Cluster sampling includes elements only from sampled clusters, while stratified sampling includes elements from each stratum.
What is the main characteristic of systematic random sampling?
The sample is selected from a list of every member of the population.
What is the purpose of an experiment in data collection?
To test whether a causal relationship exists between variables.
What is an independent variable in an experiment?
A variable that is manipulated by the experimenter.
What is the main advantage of multistage sampling?
It allows for the use of different sampling methods at different stages.
What is the main difference between probability sampling and non-probability sampling?
Probability sampling involves selecting a sample using a random method, while non-probability sampling involves selecting a sample based on the researcher's expertise.
What is the purpose of stratified sampling?
To select a sample that represents the population in terms of key characteristics.
What is a treatment in an experiment?
A combination of factor levels.
Study Notes
Data Collection
- The purpose of simulation models is to collect data, analyze it, and gain insights into the system being simulated.
Methods of Data Collection
- There are four main methods of data collection: • Census: A study that obtains data from every member of a population. • Sample survey: A study that obtains data from a subset of a population to estimate population attributes. • Experiment: A controlled study that attempts to understand cause-and-effect relationships. • Observational study: A study that attempts to understand cause-and-effect relationships without controlling the assignment of subjects to groups.
Pros and Cons of Data Collection Methods
- Resource advantage: Sample surveys have a big resource advantage over censuses when the population is large.
- Generalizability: Generalizability refers to the appropriateness of applying findings from a study to a larger population, which requires random selection.
- Causal inference: Experiments are the best method for investigating causal relationships due to random assignment of subjects to groups.
Sampling Survey Methods
- Sampling method: The way observations are selected from a population to be in the sample for a sample survey.
- Population parameter: The true value of a population attribute.
- Sample statistic: An estimate, based on sample data, of a population parameter.
Types of Sampling
- Cluster sampling: A sample includes elements only from sampled clusters.
- Stratified sampling: A sample includes elements from each stratum.
- Multistage sampling: A combination of different sampling methods, such as cluster sampling and simple random sampling.
Systematic Random Sampling
- A list of every member of the population is created, and then the first sample element is randomly selected from the first k elements on the population list.
- Every kth element on the list is then selected.
Experiments Method in Data Collection
- A researcher manipulates one or more variables, while holding all other variables constant, to test for a causal relationship.
Parts of an Experiment
- Independent variable (factor): An explanatory variable manipulated by the experimenter, with two or more levels (values).
- Dependent variable (response variable): A variable affected by the independent variable.
- Experimental units: The subjects or items being studied.
Learn about the four main methods of data collection in simulation models, including census, sample survey, and experiment.
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