Statistics in Decision-Making Question with 100% correct
Answers 2024
Descriptive Statistics
The branch of statistics that involves summarizing and presenting data, such as calculating measures
like the mean, median, and standard deviation.
Inferential Statistics
The branch of statistics that involves drawing conclusions and making predictions about a population
based on sample data.
Biases in Data Collection
The process of identifying and addressing biases that can impact the validity of statistical analyses,
ensuring that the data collected is representative and unbiased.
Survivorship Bias
The tendency to focus on examples that have survived or succeeded, while overlooking those that did
not, leading to skewed analysis and conclusions.
Sampling Bias
A bias that occurs when the selection of participants or samples is not random, leading to non-
representative data and potentially biased results.
Confirmation Bias
, The tendency to interpret or favor information that confirms one's preconceived beliefs or
hypotheses, potentially leading to biased analysis and conclusions.
Causation vs. Correlation
Understanding that correlation between two variables does not imply causation, and establishing
causation requires additional evidence and rigorous analysis.
Data Ethics
The consideration of ethical implications in data practices, including privacy, consent, and responsible
use of data.
Statistical Power
The ability of a statistical test or study to detect a true effect or relationship when it exists, minimizing
the chances of false negative results.
Statistical Significance
The probability that an observed effect or difference in data is not due to chance, indicating the
presence of a true relationship or effect.
Financial Decision-Making
The application of statistical models to make informed decisions in areas such as risk management,
portfolio optimization, and pricing financial instruments.
Bayesian Approach
Answers 2024
Descriptive Statistics
The branch of statistics that involves summarizing and presenting data, such as calculating measures
like the mean, median, and standard deviation.
Inferential Statistics
The branch of statistics that involves drawing conclusions and making predictions about a population
based on sample data.
Biases in Data Collection
The process of identifying and addressing biases that can impact the validity of statistical analyses,
ensuring that the data collected is representative and unbiased.
Survivorship Bias
The tendency to focus on examples that have survived or succeeded, while overlooking those that did
not, leading to skewed analysis and conclusions.
Sampling Bias
A bias that occurs when the selection of participants or samples is not random, leading to non-
representative data and potentially biased results.
Confirmation Bias
, The tendency to interpret or favor information that confirms one's preconceived beliefs or
hypotheses, potentially leading to biased analysis and conclusions.
Causation vs. Correlation
Understanding that correlation between two variables does not imply causation, and establishing
causation requires additional evidence and rigorous analysis.
Data Ethics
The consideration of ethical implications in data practices, including privacy, consent, and responsible
use of data.
Statistical Power
The ability of a statistical test or study to detect a true effect or relationship when it exists, minimizing
the chances of false negative results.
Statistical Significance
The probability that an observed effect or difference in data is not due to chance, indicating the
presence of a true relationship or effect.
Financial Decision-Making
The application of statistical models to make informed decisions in areas such as risk management,
portfolio optimization, and pricing financial instruments.
Bayesian Approach
