18 Questions
What is the term for collecting data for an entire population?
Census
Define what a sample is.
The data you have.
Why is collecting data for an entire population often not feasible?
It is too expensive or difficult to identify the entire population.
What is the purpose of randomly selecting a sample from a population?
To ensure the validity and representativeness of the data collected.
How can biases, such as selection bias or response bias, impact data collection?
They can skew the results and lead to erroneous conclusions.
Explain the concept of sampling techniques in data collection.
Sampling techniques involve selecting a subset of individuals or data points from a larger population.
What is the difference between simple random sampling and systematic sampling?
Simple random sampling involves randomly selecting individual items from the population, whereas systematic sampling involves selecting every nth item from the population.
How does stratified sampling differ from cluster sampling?
Stratified sampling involves dividing the population into subgroups based on certain characteristics and then sampling from each subgroup, while cluster sampling involves dividing the population into groups and randomly selecting entire groups for sampling.
Why is it important to consider the type of variables in statistical analysis?
The type of variables (categorical, ordinal, continuous) influences the choice of statistical techniques used for analysis, ensuring appropriate and accurate results.
Give an example of when cluster sampling would be more practical than simple random sampling.
Cluster sampling would be more practical when the population is geographically dispersed and it is easier to select entire clusters rather than individual elements.
Explain why systematic sampling may introduce bias if not implemented correctly.
Systematic sampling may introduce bias if there is a pattern in the arrangement of the population that aligns with the sampling interval, leading to a non-representative sample.
How does stratified sampling help ensure representation of different subgroups in the population?
Stratified sampling ensures representation by dividing the population into subgroups based on characteristics, allowing for targeted sampling from each subgroup to capture diversity.
Explain when to use a Z-test and when to use a T-test.
Z-test is used when sample size > 30 and pop. std. dev. is known. T-test is used when sample size < 30 and pop. std. dev. is unknown.
What is the formula for the Z-test?
Z = (X̅-µ)/(s/√n)
Explain when to use a Chi-Square test.
Chi-Square test is used to determine association or relationship between two categorical variables.
What is the formula for the Chi-Square test?
X² = (O-E)² / E
Describe the purpose of ANOVA.
ANOVA examines variability between and within groups to assess differences in means.
What is the test statistic used in ANOVA?
F-statistic
Learn about the concept of sampling in data collection, the reasons behind using samples instead of collecting data for the entire population, and how to ensure that a sample accurately represents the population of interest.
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