Estimation and Inference
50 questions available
Key Points
- Probability sampling provides equal selection chances and higher reliability.
- Systematic sampling involves selecting every kth member.
- Non-probability sampling includes Convenience and Judgmental sampling.
- Sampling error is the difference between the observed sample statistic and the population parameter.
Key Points
- Stratified sampling increases precision and guarantees representation.
- Bond indexing is a common application of stratified sampling.
- Cluster sampling is cost-effective but generally less accurate.
- One-stage cluster sampling includes all members of the selected clusters.
Key Points
- CLT applies when sample size n is greater than or equal to 30.
- Sampling distribution approaches a normal distribution.
- Standard Error = Population SD / square root of n.
- Standard Error measures the precision of the sample mean estimate.
Key Points
- Bootstrapping draws samples with replacement.
- Jackknife leaves out one observation at a time (n samples for size n).
- Jackknife produces deterministic results; Bootstrap produces random results.
- Both methods rely on repetitive sampling to estimate parameters.
Questions
Which of the following best describes a key characteristic of probability sampling?
View answer and explanationWhich sampling method involves dividing the population into subpopulations and drawing samples from each proportional to their relative size?
View answer and explanationIf a researcher selects every 50th member of a population list to create a sample, which method is being used?
View answer and explanationWhat is the primary advantage of stratified random sampling over simple random sampling?
View answer and explanationIn the context of sampling, what is 'sampling error'?
View answer and explanationWhich sampling technique is most commonly used for bond indexing?
View answer and explanationCluster sampling is considered most advantageous in terms of:
View answer and explanationWhat distinguishes 'two-stage' cluster sampling from 'one-stage' cluster sampling?
View answer and explanationWhich of the following is a risk associated with non-probability sampling?
View answer and explanationAuditors using their professional knowledge to select specific transactions for review is an example of:
View answer and explanationWhich sampling method is most appropriate when the population data is homogeneous?
View answer and explanationAccording to the Central Limit Theorem (CLT), the sampling distribution of the mean will be approximately normal if the sample size is:
View answer and explanationUnder the Central Limit Theorem, the mean of the sampling distribution is equal to:
View answer and explanationIf a population has a standard deviation of 20 and a sample size of 100 is drawn, what is the standard error of the sample mean?
View answer and explanationStandard error is best defined as:
View answer and explanationWhen the population standard deviation is unknown, the standard error is estimated using:
View answer and explanationBootstrapping is a resampling method that involves:
View answer and explanationA key difference between Bootstrapping and Jackknife resampling is that:
View answer and explanationHow many repetitions are usually required for the Jackknife method on a sample of size n?
View answer and explanationIn Bootstrapping, the size of each re-sample is:
View answer and explanationWhich method is also referred to as 'model-free re-sampling' or 'non-parametric re-sampling'?
View answer and explanationIf a sample mean is 50, the population standard deviation is 10, and the sample size is 25, what is the standard error?
View answer and explanationWhich sampling method is prone to 'skewed results' due to the bias of the researcher?
View answer and explanationWhat is a characteristic of Convenience Sampling?
View answer and explanationWhich method is useful when population members cannot be coded or identified?
View answer and explanationIn Stratified Random Sampling, samples from each stratum are drawn:
View answer and explanationWhich of the following statements regarding Cluster Sampling is correct?
View answer and explanationA distribution of all distinct possible values that a statistic can assume when computed from samples of the same size is called:
View answer and explanationThe Central Limit Theorem implies that as the sample size increases, the standard error of the sample mean:
View answer and explanationIf standard error is calculated as s/sqrt(n), what does 's' represent?
View answer and explanationWhich resampling method replaces each item drawn for the next draw?
View answer and explanationIf you are conducting a survey and choose to interview people simply because they are easily accessible at a shopping mall, you are using:
View answer and explanationIn the Jackknife method, if the original sample has 10 observations, how many re-samples are created?
View answer and explanationWhich of the following is true regarding the sample mean in relation to the Central Limit Theorem?
View answer and explanationSample standard deviation (Sx) approaches what value according to the Central Limit Theorem?
View answer and explanationIf we want to find out how precise the estimate of a population parameter from sampled data is, which statistic should be used?
View answer and explanationIn stratified random sampling, all strata are included, but in cluster sampling:
View answer and explanationWhich sampling method guarantees that population subdivisions of interest are represented?
View answer and explanationWhich of the following is a type of non-probability sampling?
View answer and explanationFor a sample size of 64 and a population standard deviation of 16, calculate the standard error.
View answer and explanationWhat is the result of using a systematic sampling plan?
View answer and explanationWhich method involves selecting a sample by handpicking elements based on knowledge?
View answer and explanationThe standard error formula s/sqrt(n) is used when:
View answer and explanationWhich of the following describes 'One-stage cluster sampling'?
View answer and explanationProbability sampling is generally preferred over non-probability sampling because:
View answer and explanationIf a sample size n=49 and sample standard deviation s=14, what is the estimated standard error?
View answer and explanationIn the context of Big Data, bootstrapping is often called:
View answer and explanationWhat is the relationship between the standard deviation of the sampling distribution and the standard error?
View answer and explanationWhich sampling method is noted for having 'level of sampling accuracy could be limited'?
View answer and explanationIf a sample has 100 observations, determining the appropriate number of repetitions for Bootstrapping is:
View answer and explanation