WGU D772 STATISTICAL DATA LITERACY EXAM
COMPLETE QUESTIONS AND CORRECT ANSWERS
(PASS GUARANTEE)
300 QUESTIONS AND ANSWERS
1. Q: What is statistics?
A: Statistics is the science of collecting, organizing, analyzing, interpreting, and
presenting data to make informed decisions and draw conclusions about
populations based on sample data.
2. Q: What is the difference between a population and a sample?
A: A population is the entire group of individuals or objects being studied,
while a sample is a subset of the population selected to represent the whole
population.
3. Q: What are the two main types of statistics?
A: Descriptive statistics (summarizing and describing data) and inferential
statistics (making predictions or inferences about populations based on sample
data).
4. Q: Define variable in statistics.
A: A variable is a characteristic or attribute that can take on different values
among the subjects being studied.
5. Q: What is the difference between qualitative and quantitative
variables?
A: Qualitative (categorical) variables describe qualities or categories (e.g.,
color, gender), while quantitative (numerical) variables represent measurable
quantities (e.g., height, weight).
6. Q: What are the two types of quantitative variables?
,A: Discrete variables (countable whole numbers, like number of children) and
continuous variables (can take any value within a range, like height or
temperature).
7. Q: What are the four levels of measurement?
A: Nominal (categories with no order), Ordinal (ordered categories), Interval
(ordered with equal intervals but no true zero), and Ratio (ordered with equal
intervals and a true zero point).
8. Q: Give an example of nominal data.
A: Eye color, gender, race, or brand names - categories that cannot be ranked or
ordered.
9. Q: Give an example of ordinal data.
A: Survey ratings (poor, fair, good, excellent), education levels (high school,
bachelor's, master's), or military ranks.
10. Q: Give an example of interval data.
A: Temperature in Celsius or Fahrenheit, calendar years, or IQ scores - data
with equal intervals but no meaningful zero point.
11. Q: Give an example of ratio data.
A: Height, weight, age, income, or number of items - data with equal intervals
and a meaningful zero point.
12. Q: What is a parameter?
A: A parameter is a numerical value that describes a characteristic of a
population (e.g., population mean μ).
13. Q: What is a statistic?
A: A statistic is a numerical value that describes a characteristic of a sample
(e.g., sample mean x̄).
14. Q: What is sampling error?
A: Sampling error is the difference between a sample statistic and the
corresponding population parameter, occurring because the sample may not
perfectly represent the population.
15. Q: What is bias in statistics?
,A: Bias is a systematic error that consistently causes statistics to differ from
parameters in a particular direction, often due to flawed data collection
methods.
16. Q: What is random sampling?
A: Random sampling is a method where each member of the population has an
equal chance of being selected for the sample, helping to ensure
representativeness.
17. Q: What is systematic sampling?
A: Systematic sampling involves selecting every nth item from a population
after randomly choosing a starting point.
18. Q: What is stratified sampling?
A: Stratified sampling divides the population into distinct subgroups (strata) and
then randomly samples from each stratum.
19. Q: What is cluster sampling?
A: Cluster sampling involves dividing the population into clusters, randomly
selecting some clusters, and then including all members of selected clusters in
the sample.
20. Q: What is convenience sampling?
A: Convenience sampling involves selecting subjects that are easily accessible
or available, which may not represent the entire population.
21. Q: What is the difference between census and sampling?
A: A census collects data from every member of the population, while sampling
collects data from only a subset of the population.
22. Q: What is data?
A: Data are individual pieces of information, usually numerical, that describe
characteristics of individuals or objects.
23. Q: What is the difference between primary and secondary data?
A: Primary data is collected firsthand by the researcher for a specific purpose,
while secondary data has been collected by someone else for another purpose.
24. Q: What is experimental design?
, A: Experimental design is a method of data collection where researchers
manipulate one or more variables to observe their effect on another variable.
25. Q: What is observational study?
A: An observational study observes and measures characteristics without
manipulating any variables or imposing treatments.
26. Q: What is the difference between correlation and causation?
A: Correlation indicates a statistical relationship between variables, while
causation means one variable actually causes changes in another variable.
27. Q: What is confounding?
A: Confounding occurs when the effect of one variable on the outcome is mixed
up with the effect of another variable.
28. Q: What is a control group?
A: A control group is a group in an experiment that does not receive the
treatment being tested, serving as a baseline for comparison.
29. Q: What is randomization in experiments?
A: Randomization is the process of randomly assigning subjects to different
treatment groups to minimize bias and confounding.
30. Q: What is replication in statistics?
A: Replication means repeating an experiment or study to verify results and
increase confidence in the findings.
31. Q: What is a double-blind experiment?
A: A double-blind experiment is one where neither the subjects nor the
researchers know which treatment group subjects are in, reducing bias.
32. Q: What is a placebo?
A: A placebo is an inactive treatment given to a control group that appears
identical to the actual treatment being tested.
33. Q: What is the placebo effect?
A: The placebo effect is when subjects show improvement simply because they
believe they are receiving treatment, even when receiving an inactive placebo.
34. Q: What is statistical significance?
COMPLETE QUESTIONS AND CORRECT ANSWERS
(PASS GUARANTEE)
300 QUESTIONS AND ANSWERS
1. Q: What is statistics?
A: Statistics is the science of collecting, organizing, analyzing, interpreting, and
presenting data to make informed decisions and draw conclusions about
populations based on sample data.
2. Q: What is the difference between a population and a sample?
A: A population is the entire group of individuals or objects being studied,
while a sample is a subset of the population selected to represent the whole
population.
3. Q: What are the two main types of statistics?
A: Descriptive statistics (summarizing and describing data) and inferential
statistics (making predictions or inferences about populations based on sample
data).
4. Q: Define variable in statistics.
A: A variable is a characteristic or attribute that can take on different values
among the subjects being studied.
5. Q: What is the difference between qualitative and quantitative
variables?
A: Qualitative (categorical) variables describe qualities or categories (e.g.,
color, gender), while quantitative (numerical) variables represent measurable
quantities (e.g., height, weight).
6. Q: What are the two types of quantitative variables?
,A: Discrete variables (countable whole numbers, like number of children) and
continuous variables (can take any value within a range, like height or
temperature).
7. Q: What are the four levels of measurement?
A: Nominal (categories with no order), Ordinal (ordered categories), Interval
(ordered with equal intervals but no true zero), and Ratio (ordered with equal
intervals and a true zero point).
8. Q: Give an example of nominal data.
A: Eye color, gender, race, or brand names - categories that cannot be ranked or
ordered.
9. Q: Give an example of ordinal data.
A: Survey ratings (poor, fair, good, excellent), education levels (high school,
bachelor's, master's), or military ranks.
10. Q: Give an example of interval data.
A: Temperature in Celsius or Fahrenheit, calendar years, or IQ scores - data
with equal intervals but no meaningful zero point.
11. Q: Give an example of ratio data.
A: Height, weight, age, income, or number of items - data with equal intervals
and a meaningful zero point.
12. Q: What is a parameter?
A: A parameter is a numerical value that describes a characteristic of a
population (e.g., population mean μ).
13. Q: What is a statistic?
A: A statistic is a numerical value that describes a characteristic of a sample
(e.g., sample mean x̄).
14. Q: What is sampling error?
A: Sampling error is the difference between a sample statistic and the
corresponding population parameter, occurring because the sample may not
perfectly represent the population.
15. Q: What is bias in statistics?
,A: Bias is a systematic error that consistently causes statistics to differ from
parameters in a particular direction, often due to flawed data collection
methods.
16. Q: What is random sampling?
A: Random sampling is a method where each member of the population has an
equal chance of being selected for the sample, helping to ensure
representativeness.
17. Q: What is systematic sampling?
A: Systematic sampling involves selecting every nth item from a population
after randomly choosing a starting point.
18. Q: What is stratified sampling?
A: Stratified sampling divides the population into distinct subgroups (strata) and
then randomly samples from each stratum.
19. Q: What is cluster sampling?
A: Cluster sampling involves dividing the population into clusters, randomly
selecting some clusters, and then including all members of selected clusters in
the sample.
20. Q: What is convenience sampling?
A: Convenience sampling involves selecting subjects that are easily accessible
or available, which may not represent the entire population.
21. Q: What is the difference between census and sampling?
A: A census collects data from every member of the population, while sampling
collects data from only a subset of the population.
22. Q: What is data?
A: Data are individual pieces of information, usually numerical, that describe
characteristics of individuals or objects.
23. Q: What is the difference between primary and secondary data?
A: Primary data is collected firsthand by the researcher for a specific purpose,
while secondary data has been collected by someone else for another purpose.
24. Q: What is experimental design?
, A: Experimental design is a method of data collection where researchers
manipulate one or more variables to observe their effect on another variable.
25. Q: What is observational study?
A: An observational study observes and measures characteristics without
manipulating any variables or imposing treatments.
26. Q: What is the difference between correlation and causation?
A: Correlation indicates a statistical relationship between variables, while
causation means one variable actually causes changes in another variable.
27. Q: What is confounding?
A: Confounding occurs when the effect of one variable on the outcome is mixed
up with the effect of another variable.
28. Q: What is a control group?
A: A control group is a group in an experiment that does not receive the
treatment being tested, serving as a baseline for comparison.
29. Q: What is randomization in experiments?
A: Randomization is the process of randomly assigning subjects to different
treatment groups to minimize bias and confounding.
30. Q: What is replication in statistics?
A: Replication means repeating an experiment or study to verify results and
increase confidence in the findings.
31. Q: What is a double-blind experiment?
A: A double-blind experiment is one where neither the subjects nor the
researchers know which treatment group subjects are in, reducing bias.
32. Q: What is a placebo?
A: A placebo is an inactive treatment given to a control group that appears
identical to the actual treatment being tested.
33. Q: What is the placebo effect?
A: The placebo effect is when subjects show improvement simply because they
believe they are receiving treatment, even when receiving an inactive placebo.
34. Q: What is statistical significance?
