MSC ASM QUIZ_1

The bias of an estimator is defined as:

• The range within which the true parameter value lies

• The variability of the estimator across different samples

• The probability of rejecting a true null hypothesis

• 
  The difference between the estimator's expected value and the true value of the parameter

Which of the following statements about a good estimator is true?

• It should have high variability.

• It should be unbiased and consistent.

• It should always equal the true population parameter.

• It should be influenced heavily by outliers.

Which of the following is an example of a point estimator?

• Confidence interval

• Sample mean

• Hypothesis test

• Standard deviation

An estimator is consistent if:

• It is unbiased for all sample sizes

• It has a small standard error

• It converges in probability to the true parameter as the sample size increases

• It is efficient

A statistic is sufficient if:

• It uses all available sample data
  
  

• It provides the best estimate of the population parameter

• It contains all the information needed to estimate the parameter without any loss of information
  

• It is unbiased and consistent

An agricultural scientist is estimating the average yield per acre for a new crop variety. They calculate the sample mean and find it has the smallest variance among all unbiased estimators of the population mean. What property of the estimator does this demonstrate?

• Consistency
  

• Efficiency
  

• Sufficiency
  

• Likelihood

A teacher records the grades of students in a large class on a recent exam. The grades are evenly distributed between 50 and 100. Which probability distribution is most appropriate for modeling the grades?

• Binomial Distribution
  

• Poisson Distribution
  

• Normal Distribution
  

• Uniform Distribution

Rule, formula or function that can help us to approximate value based on data______

• Estimate

• Estimator

• Estimation

• Estimating

Which of the following probability distributions is the odd one out, considering the type of data they model?

• Binomial Distribution
  

• Poisson Distribution
  

• Gamma Distribution
  

• Geometric Distribution

Which of the following is an example of an unbiased estimator?

• 
  Sample variance for population variance without correction

• Sample median for population mean

• Sample mean for population mean

• 
  Population mean for sample mean