the power of statistics coursera weekly challenge 3 answers
Test your knowledge: Introduction to sampling
1. A data professional is conducting an election poll. As a first step in the sampling process, they identify the target population. What is the second step in the sampling process?
- Select the sampling frame
- Choose the sampling method
- Determine the sample size
- Collect the sample data
2. Fill in the blank: In a _____ sample, every member of a population is selected randomly and has an equal chance of being chosen.
- cluster
- snowball
- simple random
- voluntary response
3. Non-probability sampling includes which of the following sampling methods? Select all that apply.
- Systematic random sampling
- Stratified random sampling
- Convenience sampling
- Purposive sampling
Test your knowledge: Sampling distributions
4. A data professional is analyzing data about a population of aspen trees. They take repeated random samples of 10 trees from the population and compute the mean height for each sample. Which of the following statements best describes the sampling distribution of the mean?
- The sampling distribution of the mean is the sum of all the sample means.
- The sampling distribution of the mean is the maximum value of all the sample means.
- The probability distribution of all the sample means
- The average value of all the sample means.
5. The central limit theorem implies which of the following statements? Select all that apply.
- If you take a large enough sample of the population, the sample mean will be roughly equal to the population mean.
- If you take a small enough sample of the population, the sample mean will be roughly equal to the population mean.
- The sampling distribution of the mean approaches a normal distribution as the sample size decreases.
- The sampling distribution of the mean approaches a normal distribution as the sample size increases.
6. What is a standard error?
- An estimate of a population parameter
- The standard deviation of a sample statistic
- A list of all the items in the target population.
- The probability distribution of a sample statistic
Test your knowledge: Work with sampling distributions in Python
7. Which Python function can be used to simulate random sampling?
- pandas.DataFrame.hist()
- pandas.DataFrame.describe()
- pandas.DataFrame.mean()
- pandas.DataFrame.sample()
8. Which of the following statements describe a random seed when specifying random_state in pandas.DataFrame.sample()? Select all that apply.
- Any number can be chosen to fix the random seed.
- The same random seed may be used over again to generate the same set of numbers.
- Only a negative number may be chosen to fix the random seed.
- A random seed is a starting point for generating random numbers.
Weekly challenge 3
9. Fill in the blank: A _____ sample accurately reflects the characteristics of a population.
- nonrepresentative
- very small
- biased
- representative
10. Which of the following activities are stages in the typical sampling process? Select all that apply.
- Perform exploratory data analysis
- Select the sampling frame
- Identify the target population
- Make a point estimate of a population parameter
11. Which of the following statements accurately describes the relationship between probability sampling and non-probability sampling?
- Probability sampling is typically less expensive than non-probability sampling.
- Probability sampling is typically less convenient than non-probability sampling.
- Probability sampling is more biased than non-probability sampling.
- Probability sampling gives data professionals a better chance of generating a representative sample than non-probability sampling.
12. What is a key difference between stratified random sampling and cluster random sampling?
- Stratified sampling is a probability sampling method; cluster sampling is a non-probability sampling method.
- In stratified sampling, you randomly choose some members from each group to be in the sample; in cluster sampling, you choose all members from each group to be in the sample.
- Stratified sampling is a non-probability sampling method; cluster sampling is a probability sampling method.
- In stratified sampling, you randomly choose all members from each group to be in the sample; in cluster sampling, you choose some members from each group to be in the sample.
13. Which of the following scenarios best describe snowball sampling?
- Researchers recruit initial participants to be in a study, then ask them to recruit other people to participate in the study.
- Researchers select members of a population based on random sampling.
- Researchers select participants based on the purpose of their study.
- Researchers select members of a population who are easy to contact or reach.
14. Fill in the blank: Standard error measures the _____ of a sampling distribution.
- mode
- standard deviation
- median
- mean
15. What concept states that the sampling distribution of the mean approaches a normal distribution as the sample size increases?
- Bayes’ theorem
- Sampling frame
- Central limit theorem
- Standard error
16. A data professional is working with data about annual household income. They want to use Python to simulate taking a random sample of income values from the dataset. They write the following code: sample(n=100, replace=True, random_state=230). What is the random seed?
- 230
- 10
- 23
- 100
17. Which of the following statements accurately describe non-probability sampling? Select all that apply.
- Non-probability sampling is often based on convenience.
- Non-probability sampling is often based on the personal preferences of the researcher.
- Non-probability sampling typically uses random selection.
- Non-probability sampling can result in biased samples.
18. A data professional is conducting an employee satisfaction survey. First, they list all the employees alphabetically by first name. Then, they randomly choose a starting point on the list and pick every third name to be in the sample. What sampling method are they using?
- Simple random sampling
- Cluster random sampling
- Systematic random sampling
- Stratified random sampling
19. Which of the following statements accurately describe the standard error of the mean? Select all that apply.
- The lower the standard error, the more precise the sample mean is.
- The higher the standard error, the more precise the sample mean is.
- A larger standard error indicates that, in repeated sampling, the sample means are more spread out.
- The standard error of the mean measures variability among the sample means obtained in repeated sampling.
20. Which of the following statements accurately describe a representative sample? Select all that apply.
- A representative sample reflects the characteristics of the overall population.
- A representative sample helps data professionals make reliable inferences based on sample data.
- A representative sample suffers from sampling bias.
- A representative sample represents some groups in the population but not others.
21. What does the central limit theorem state?
- The sampling distribution of the mean approaches a normal distribution as the sample size increases.
- The sampling distribution of the mean approaches a Poisson distribution as the sample size increases.
- The sampling distribution of the mean approaches a binomial distribution as the sample size increases.
- The sampling distribution of the mean approaches a Bernoulli distribution as the sample size increases.
22. A data professional is working with data about annual household income. They want to use Python to simulate taking a random sample of income values from the dataset. They write the following code: sample(n=100, replace=True, random_state=230). What is the sample size of the random sample?
- 23
- 100
- 230
- 10
23. Which of the following scenarios would benefit from replacing their current sample with a representative sample? Select all that apply.
- A researcher conducts a survey on the experience of high school students. For their sample, they choose students from a variety of academic, social, and cultural backgrounds.
- A researcher conducts an employee satisfaction survey for a company. For their sample, they choose employees who have worked at the company for at least 25 years.
- A researcher conducts a poll for an upcoming national election. For their sample, they choose voters from a single city.
- A researcher conducts a survey on computer skills among university students. For their sample, they choose students who major in computer science.
24. Which sampling method involves choosing members of a population who are easy to contact or reach?
- Purposive sampling
- Voluntary response sampling
- Convenience sampling
- Snowball sampling
25. Fill in the blank: The central limit theorem states that the _____ of the mean approaches a normal distribution as the sample size increases.
- sampling variability
- sampling distribution
- sampling bias
- sampling frame