Statistics Quiz

Which of the following best defines a parameter in statistics?

• A numerical value that describes a sample

• A numerical value that describes a population

• A numerical value that changes randomly

• A numerical value computed from a dataset

What is a statistic in statistical analysis?

• A numerical measure that describes a sample

• A numerical measure that describes a population

• A constant value derived from a census

• A parameter calculated from a survey

Which of the following statements is true about a parameter?

• It is always known and fixed

• It varies from sample to sample

• It is an estimate of a sample statistic

• It describes an entire population

The process of drawing conclusions about a population based on a sample is called:

• Descriptive Statistics

• Inferential Statistics

• Population Analysis

• Data Mining

Which of the following is an example of a parameter?

• The mean height of students in a randomly chosen class

• The average test score of all students in a school

• The proportion of defective items in a batch sampled from a factory

• The median age of 100 randomly selected people in a city

A sampling distribution is the distribution of:

• The population parameters

• The sample data points

• A statistic computed from all possible samples of a given size

• The raw data collected from different samples

What happens to the variability of a sampling distribution as the sample size increases?

• Increases

• Decreases

• Stays the same

• Becomes unpredictable

According to the Central Limit Theorem, the sampling distribution of the sample mean approaches a normal distribution as:

• The population becomes more uniform

• The sample size increases

• The standard deviation increases

• More samples are discarded

The standard deviation of a sampling distribution is also known as:

• Population Standard Deviation

• Sample Variance

• Standard Error

• Sampling Bias

If a statistic is an unbiased estimator of a parameter, it means that:

• It always gives the exact value of the parameter

• It consistently underestimates the parameter

• The expected value of the statistic equals the parameter

• It cannot be used for inference