WGU D582 Intro to Stats for Research | Study Guide |
Helpful Tips | 2025 Update with complete solutions.
1. What is the difference between a population and a sample?
Answer: A population includes all members of a defined group that we are studying or
collecting information on, while a sample is a subset of the population selected for
analysis.
2. Define descriptive statistics.
Answer: Descriptive statistics summarize and organize characteristics of a data set,
including measures like mean, median, mode, and standard deviation.
3. What is inferential statistics?
Answer: Inferential statistics use data from a sample to make inferences or predictions
about a population.
4. Explain the term 'variable' in statistics.
Answer: A variable is any characteristic, number, or quantity that can be measured or
quantified.
5. Differentiate between qualitative and quantitative variables.
Answer: Qualitative variables describe non-numeric characteristics or categories, while
quantitative variables represent numeric values.
6. What is a nominal scale?
Answer: A nominal scale classifies data into distinct categories without any order or
ranking.
7. Define ordinal scale.
Answer: An ordinal scale classifies data into categories that have a meaningful order but
unknown intervals between categories.
8. What is an interval scale?
Answer: An interval scale has ordered categories with known and equal distances
between them but lacks a true zero point.
,9. Explain a ratio scale.
Answer: A ratio scale has all the properties of an interval scale, and also includes a true
zero point, allowing for the calculation of ratios.
10. What is the mean of a data set?
Answer: The mean is the average of all data points, calculated by summing them up and
dividing by the number of points.
11. Define median.
Answer: The median is the middle value in a data set when the numbers are arranged in
order.
12. What is the mode?
Answer: The mode is the value that appears most frequently in a data set.
13. Explain range in statistics.
Answer: The range is the difference between the highest and lowest values in a data set.
14. What is variance?
Answer: Variance measures the average squared deviation of each number from the mean
of a data set.
15. Define standard deviation.
Answer: Standard deviation is the square root of the variance and indicates how spread
out the numbers in a data set are.
16. What is a frequency distribution?
Answer: A frequency distribution is a summary of how often different values occur in a
data set.
17. Explain the purpose of a histogram.
Answer: A histogram is a graphical representation of the distribution of numerical data,
showing the frequency of data within certain ranges.
18. What is a normal distribution?
, Answer: A normal distribution is a bell-shaped curve where most of the data points are
concentrated around the mean, and it is symmetric about the mean.
19. Define skewness.
Answer: Skewness measures the asymmetry of the distribution of values in a data set.
20. What does a positive skew indicate?
Answer: A positive skew indicates that the tail on the right side of the distribution is
longer or fatter than the left side.
21. What does a negative skew indicate?
Answer: A negative skew indicates that the tail on the left side of the distribution is
longer or fatter than the right side.
22. Define kurtosis.
Answer: Kurtosis measures the "tailedness" of the distribution; high kurtosis indicates
heavy tails, while low kurtosis indicates light tails.
23. What is probability?
Answer: Probability is a measure of the likelihood that an event will occur, expressed as a
number between 0 and 1.
24. Explain the difference between independent and dependent events.
Answer: Independent events are those whose outcomes do not affect each other, while
dependent events have outcomes that are influenced by each other.
25. What is a probability distribution?
Answer: A probability distribution shows how probabilities are distributed over the
values of a random variable.
26. Define discrete random variable.
Answer: A discrete random variable is one that has countable outcomes, such as the
number of heads in a series of coin flips.
27. What is a continuous random variable?
Answer: A continuous random variable can take any value within a given range, such as
height or weight.
Helpful Tips | 2025 Update with complete solutions.
1. What is the difference between a population and a sample?
Answer: A population includes all members of a defined group that we are studying or
collecting information on, while a sample is a subset of the population selected for
analysis.
2. Define descriptive statistics.
Answer: Descriptive statistics summarize and organize characteristics of a data set,
including measures like mean, median, mode, and standard deviation.
3. What is inferential statistics?
Answer: Inferential statistics use data from a sample to make inferences or predictions
about a population.
4. Explain the term 'variable' in statistics.
Answer: A variable is any characteristic, number, or quantity that can be measured or
quantified.
5. Differentiate between qualitative and quantitative variables.
Answer: Qualitative variables describe non-numeric characteristics or categories, while
quantitative variables represent numeric values.
6. What is a nominal scale?
Answer: A nominal scale classifies data into distinct categories without any order or
ranking.
7. Define ordinal scale.
Answer: An ordinal scale classifies data into categories that have a meaningful order but
unknown intervals between categories.
8. What is an interval scale?
Answer: An interval scale has ordered categories with known and equal distances
between them but lacks a true zero point.
,9. Explain a ratio scale.
Answer: A ratio scale has all the properties of an interval scale, and also includes a true
zero point, allowing for the calculation of ratios.
10. What is the mean of a data set?
Answer: The mean is the average of all data points, calculated by summing them up and
dividing by the number of points.
11. Define median.
Answer: The median is the middle value in a data set when the numbers are arranged in
order.
12. What is the mode?
Answer: The mode is the value that appears most frequently in a data set.
13. Explain range in statistics.
Answer: The range is the difference between the highest and lowest values in a data set.
14. What is variance?
Answer: Variance measures the average squared deviation of each number from the mean
of a data set.
15. Define standard deviation.
Answer: Standard deviation is the square root of the variance and indicates how spread
out the numbers in a data set are.
16. What is a frequency distribution?
Answer: A frequency distribution is a summary of how often different values occur in a
data set.
17. Explain the purpose of a histogram.
Answer: A histogram is a graphical representation of the distribution of numerical data,
showing the frequency of data within certain ranges.
18. What is a normal distribution?
, Answer: A normal distribution is a bell-shaped curve where most of the data points are
concentrated around the mean, and it is symmetric about the mean.
19. Define skewness.
Answer: Skewness measures the asymmetry of the distribution of values in a data set.
20. What does a positive skew indicate?
Answer: A positive skew indicates that the tail on the right side of the distribution is
longer or fatter than the left side.
21. What does a negative skew indicate?
Answer: A negative skew indicates that the tail on the left side of the distribution is
longer or fatter than the right side.
22. Define kurtosis.
Answer: Kurtosis measures the "tailedness" of the distribution; high kurtosis indicates
heavy tails, while low kurtosis indicates light tails.
23. What is probability?
Answer: Probability is a measure of the likelihood that an event will occur, expressed as a
number between 0 and 1.
24. Explain the difference between independent and dependent events.
Answer: Independent events are those whose outcomes do not affect each other, while
dependent events have outcomes that are influenced by each other.
25. What is a probability distribution?
Answer: A probability distribution shows how probabilities are distributed over the
values of a random variable.
26. Define discrete random variable.
Answer: A discrete random variable is one that has countable outcomes, such as the
number of heads in a series of coin flips.
27. What is a continuous random variable?
Answer: A continuous random variable can take any value within a given range, such as
height or weight.
