Business Analytics, Jeffrey D. Camm - Chapter 1-4 exam complete
questions and verified answers
1. Descriptive analytics: Encompasses the set of techniques that describes what has happened in the past
2. Data query: A request for information with certain characteristics from a database
3. Data dashboards: Collections of tables, charts, maps, and summary statistics that are updated as new data
become available
4. Predictive analytics: Consists of techniques that use models constructed from past data to predict the future
or ascertain the impact of one variable on another.
5. Optimization models: Models that give the best decision subject to constraints of the situation
6. Simulation optimization: Combines the use of probability and statistics to model uncertainty with
optimization techniques to find good decisions in highly complex and highly uncertain
7. Decision analysis: Used to develop an optimal strategy when a decision maker is faced with several decision
alternatives and an uncertain set of future events
8. Big data: A set of data that cannot be managed, processed, or analyzed with commonly available software in a
reasonable amount of time
9. Hadoop: An open-source programming environment that supports big data processing through distributed
storage and processing over multiple computers
10. MapReduce: A programming model used within Hadoop that performs two major steps: the map step and
the reduce step
11. Data security: The protection of stored data from destructive forces or unauthorized users
12. Data: The facts and figures collected, analyzed, and summarized for presentation and interpretation
13. Variable: A characteristic or a quantity of interest that can take on ditterent values
14. Observation: Set of values corresponding to a set of variables
15. Variation: The ditterence in a variable measured over observations
16. Random variable/uncertain variable: A quantity whose values are not known with certainty.
17. Population: All elements of interest
18. Sample: Subset of the population
19. Random sampling: A sampling method to gather a representative sample of the population data
20. Quantitative data: Data on which numeric and arithmetic operations, such as addition, subtraction,
multiplication, and division, can be performed
21. Categorical data: Data on which arithmetic operations cannot be performed
22. Cross-sectional data: Data collected from several entities at the same, or approximately the same, point
in time
23. Time series data: Data collected over several time periods
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, Business Analytics, Jeffrey D. Camm - Chapter 1-4 exam complete
questions and verified answers
24. Experimental study: Then one or more other variables are identified and controlled or manipulated so
that data can be obtained about how they influence the variable of interest
25. Non-experimental study or observational study: Make no attempt to control the variables
of interest
26. Frequency distribution: A summary of data that shows the number (frequency) of observations in each
of several nonoverlapping classes
27. Relative frequency distribution: It is a tabular summary of data showing the relative frequency for
each bin
28. Percent frequency distribution: Summarizes the percent frequency of the data for each bin
29. Percent frequency distribution: used to provide estimates of the relative likelihoods of ditterent
values of a random variable
30. Frequency Distributions for Quantitative Data: Determine the number of nonoverlapping
bins. Determine the width of each bin. Determine the bin limits.
31. Histogram: common graphical presentation of quantitative data
32. Skewness: an important characteristic of the shape of a distribution
33. Cumulative frequency distribution: A variation of the frequency distribution that provides another
tabular summary of quantitative data
34. Median: Value in the middle when the data are arranged in ascending order
35. Mode: Value that occurs most frequently in a data set
36. Multimodal data: Data contain at least two modes
37. Bimodal data: Data contain exactly two modes
38. Geometric Mean: nth root of the product of n values
39. Range: Found by subtracting the smallest value from the largest value in a data set
40. Drawback: Range is based on only two of the observations and thus is highly influenced by extreme values
41. Variance: Measure of variability that utilizes all the data
42. Standard Deviation: Positive square root of the variance
43. Coefficient of Variation: Measures the standard deviation relative to the mean
44. Percentiles: Value of a variable at which a specified (approximate) percentage of observations are below that
value
45. Quartiles: when the data is divided into four equal parts
46. Z-score: Measures the relative location of a value in the data set
47. Empirical Rule: For data having a bell-shaped distribution
2/5
questions and verified answers
1. Descriptive analytics: Encompasses the set of techniques that describes what has happened in the past
2. Data query: A request for information with certain characteristics from a database
3. Data dashboards: Collections of tables, charts, maps, and summary statistics that are updated as new data
become available
4. Predictive analytics: Consists of techniques that use models constructed from past data to predict the future
or ascertain the impact of one variable on another.
5. Optimization models: Models that give the best decision subject to constraints of the situation
6. Simulation optimization: Combines the use of probability and statistics to model uncertainty with
optimization techniques to find good decisions in highly complex and highly uncertain
7. Decision analysis: Used to develop an optimal strategy when a decision maker is faced with several decision
alternatives and an uncertain set of future events
8. Big data: A set of data that cannot be managed, processed, or analyzed with commonly available software in a
reasonable amount of time
9. Hadoop: An open-source programming environment that supports big data processing through distributed
storage and processing over multiple computers
10. MapReduce: A programming model used within Hadoop that performs two major steps: the map step and
the reduce step
11. Data security: The protection of stored data from destructive forces or unauthorized users
12. Data: The facts and figures collected, analyzed, and summarized for presentation and interpretation
13. Variable: A characteristic or a quantity of interest that can take on ditterent values
14. Observation: Set of values corresponding to a set of variables
15. Variation: The ditterence in a variable measured over observations
16. Random variable/uncertain variable: A quantity whose values are not known with certainty.
17. Population: All elements of interest
18. Sample: Subset of the population
19. Random sampling: A sampling method to gather a representative sample of the population data
20. Quantitative data: Data on which numeric and arithmetic operations, such as addition, subtraction,
multiplication, and division, can be performed
21. Categorical data: Data on which arithmetic operations cannot be performed
22. Cross-sectional data: Data collected from several entities at the same, or approximately the same, point
in time
23. Time series data: Data collected over several time periods
1/5
, Business Analytics, Jeffrey D. Camm - Chapter 1-4 exam complete
questions and verified answers
24. Experimental study: Then one or more other variables are identified and controlled or manipulated so
that data can be obtained about how they influence the variable of interest
25. Non-experimental study or observational study: Make no attempt to control the variables
of interest
26. Frequency distribution: A summary of data that shows the number (frequency) of observations in each
of several nonoverlapping classes
27. Relative frequency distribution: It is a tabular summary of data showing the relative frequency for
each bin
28. Percent frequency distribution: Summarizes the percent frequency of the data for each bin
29. Percent frequency distribution: used to provide estimates of the relative likelihoods of ditterent
values of a random variable
30. Frequency Distributions for Quantitative Data: Determine the number of nonoverlapping
bins. Determine the width of each bin. Determine the bin limits.
31. Histogram: common graphical presentation of quantitative data
32. Skewness: an important characteristic of the shape of a distribution
33. Cumulative frequency distribution: A variation of the frequency distribution that provides another
tabular summary of quantitative data
34. Median: Value in the middle when the data are arranged in ascending order
35. Mode: Value that occurs most frequently in a data set
36. Multimodal data: Data contain at least two modes
37. Bimodal data: Data contain exactly two modes
38. Geometric Mean: nth root of the product of n values
39. Range: Found by subtracting the smallest value from the largest value in a data set
40. Drawback: Range is based on only two of the observations and thus is highly influenced by extreme values
41. Variance: Measure of variability that utilizes all the data
42. Standard Deviation: Positive square root of the variance
43. Coefficient of Variation: Measures the standard deviation relative to the mean
44. Percentiles: Value of a variable at which a specified (approximate) percentage of observations are below that
value
45. Quartiles: when the data is divided into four equal parts
46. Z-score: Measures the relative location of a value in the data set
47. Empirical Rule: For data having a bell-shaped distribution
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