CSBI HFMA COMPREHENSIVE ANSWERS AND
QUESTIONS SET A+
✔what are the levels of decision automation? - ✔✔1 - fully automated
2- partially automated ( automated with overrides)
3-assisted prediction (assisted automation)
✔✔Key Decision Attributes - related to real time decision making - ✔✔1 - targeted
2-expeditious
3-adaptable to differing circumstances
4-low in cost
5-replicable done in the same way over and over again
✔✔Application situations for BI - ✔✔1- monitoring/planning
2- operational transaction focused/ real-time decision making
✔✔Business Intelligence Work - ✔✔Statistics, experimental design, use of analytic
applications - types & tools
✔✔Statistics - ✔✔Descriptive, inferential
✔✔User of Analytic Applications - ✔✔Descriptive, Predictive, Prescriptive
✔✔Experimental Design - ✔✔Sampling
✔✔Probability - ✔✔Estimation, correlation, forecasting
✔✔probability - ✔✔a measure or estimation of how likely it is that something will happen
✔✔forecasting - ✔✔process of making statements about events where the actual
outcomes have not yet been observed
, ✔✔Sampling - ✔✔the data set used to make inferences about the entire population. it
may be a population or a subset
✔✔Distribution - ✔✔the arrangement of data values showing their frequency of
appearance when working with discrete data
✔✔Statistics - ✔✔discipline and set of methodologies for dealing with data and turning it
into usable information for making decisions
✔✔Descriptive - ✔✔Summarizations and comparisons, often made with readily
available tools
✔✔Experimental Design - ✔✔provides insight into true cause and effect by
demonstrating what outcome occurs when a particular factor is manipulated
✔✔Incorrect acceptance - ✔✔the sample can yield a conclusion that supports a theory
about the population when it is not existent in the population
✔✔Incorrect Rejection - ✔✔The sample can yield a conclusion that rejects a theory
about the population when the theory holds true in the population (poses more of a
concern)
✔✔t test - ✔✔used when you cannot know the result of the total population yet want a
level of confidence that what your sample is indicating is true or applicable to the entire
population
✔✔two-sample t test - ✔✔allows for a sample size as small as six and calls for 920
depending on the confidence level desired in the result - 25% confidence level with six
and 99% confidence level with 920.
✔✔Common mistakes made by BI analysts - ✔✔1- sophistication compensating for lack
of data
2-difficulty finding and explaining patterns in data
3-equating correlation with causation
✔✔Prioritization Metric Chart (PMC) - ✔✔tool enables a prioritization that allows
tradeoff decision making about what to work on with limited resources. Helps ensure
that important items are not obscured by items of great weight or urgency.
✔✔Opportunity Prioritization Analysis - ✔✔Steps 1 - List items and classify within ASAA
2 - Weigh each characteristic as a fraction of 1.0
3- Rate each item's performance from 1 to 5
4- Multiply ratings by the weight to obtain item score
5- Compare scores to see priority focus area
6- Analytics of all three types are developed and in use
QUESTIONS SET A+
✔what are the levels of decision automation? - ✔✔1 - fully automated
2- partially automated ( automated with overrides)
3-assisted prediction (assisted automation)
✔✔Key Decision Attributes - related to real time decision making - ✔✔1 - targeted
2-expeditious
3-adaptable to differing circumstances
4-low in cost
5-replicable done in the same way over and over again
✔✔Application situations for BI - ✔✔1- monitoring/planning
2- operational transaction focused/ real-time decision making
✔✔Business Intelligence Work - ✔✔Statistics, experimental design, use of analytic
applications - types & tools
✔✔Statistics - ✔✔Descriptive, inferential
✔✔User of Analytic Applications - ✔✔Descriptive, Predictive, Prescriptive
✔✔Experimental Design - ✔✔Sampling
✔✔Probability - ✔✔Estimation, correlation, forecasting
✔✔probability - ✔✔a measure or estimation of how likely it is that something will happen
✔✔forecasting - ✔✔process of making statements about events where the actual
outcomes have not yet been observed
, ✔✔Sampling - ✔✔the data set used to make inferences about the entire population. it
may be a population or a subset
✔✔Distribution - ✔✔the arrangement of data values showing their frequency of
appearance when working with discrete data
✔✔Statistics - ✔✔discipline and set of methodologies for dealing with data and turning it
into usable information for making decisions
✔✔Descriptive - ✔✔Summarizations and comparisons, often made with readily
available tools
✔✔Experimental Design - ✔✔provides insight into true cause and effect by
demonstrating what outcome occurs when a particular factor is manipulated
✔✔Incorrect acceptance - ✔✔the sample can yield a conclusion that supports a theory
about the population when it is not existent in the population
✔✔Incorrect Rejection - ✔✔The sample can yield a conclusion that rejects a theory
about the population when the theory holds true in the population (poses more of a
concern)
✔✔t test - ✔✔used when you cannot know the result of the total population yet want a
level of confidence that what your sample is indicating is true or applicable to the entire
population
✔✔two-sample t test - ✔✔allows for a sample size as small as six and calls for 920
depending on the confidence level desired in the result - 25% confidence level with six
and 99% confidence level with 920.
✔✔Common mistakes made by BI analysts - ✔✔1- sophistication compensating for lack
of data
2-difficulty finding and explaining patterns in data
3-equating correlation with causation
✔✔Prioritization Metric Chart (PMC) - ✔✔tool enables a prioritization that allows
tradeoff decision making about what to work on with limited resources. Helps ensure
that important items are not obscured by items of great weight or urgency.
✔✔Opportunity Prioritization Analysis - ✔✔Steps 1 - List items and classify within ASAA
2 - Weigh each characteristic as a fraction of 1.0
3- Rate each item's performance from 1 to 5
4- Multiply ratings by the weight to obtain item score
5- Compare scores to see priority focus area
6- Analytics of all three types are developed and in use
