HRCM1-GC 1210 – Quantitative
Methods and Metrics for Decision
Making 50 QUESTIONS UPDATED EXAM
SETTING WITH RATIONALE ANSWERS
AND SAMMARY FORMULAE NOTES
ATTACHED 2025/2026
1. What is the primary purpose of quantitative methods in decision-making?
Answer: To analyze data and inform decisions
Rationale: Quantitative methods provide structured, numerical analysis to support more
accurate and objective decision-making.
2. Define descriptive statistics.
Answer: Descriptive statistics summarize and describe the main features of a dataset
Rationale: They allow managers to understand data trends and patterns without making
predictions.
3. What is inferential statistics?
Answer: Inferential statistics enable generalizations about a population based on
sample data
Rationale: It allows decision-makers to predict outcomes and test hypotheses from
limited data.
, 4. Which measure of central tendency is most affected by outliers?
Answer: Mean
Rationale: Extreme values can skew the mean, making it less representative of the
dataset.
5. What does a high standard deviation indicate?
Answer: Data points are widely spread around the mean
Rationale: A high standard deviation shows greater variability in the dataset.
6. What does a p-value less than 0.05 indicate in hypothesis testing?
Answer: Strong evidence against the null hypothesis
Rationale: This suggests the observed effect is statistically significant and unlikely due to
chance.
7. What is a key assumption of linear regression?
Answer: Homoscedasticity (constant variance of errors)
Rationale: Regression analysis assumes equal variance of residuals to produce unbiased
estimates.
8. What is the purpose of a decision tree?
Answer: To visualize decisions, possible outcomes, and associated probabilities
Rationale: It helps structure complex decisions and evaluate risk-reward trade-offs.
9. What is time series analysis used for?
Answer: Predicting future values based on historical data
Rationale: Identifying patterns and trends in past data allows informed forecasting.
10. What does R² (coefficient of determination) measure?
Answer: The proportion of variance in the dependent variable explained by the
independent variable(s)
Rationale: It indicates how well the regression model fits the data.
Methods and Metrics for Decision
Making 50 QUESTIONS UPDATED EXAM
SETTING WITH RATIONALE ANSWERS
AND SAMMARY FORMULAE NOTES
ATTACHED 2025/2026
1. What is the primary purpose of quantitative methods in decision-making?
Answer: To analyze data and inform decisions
Rationale: Quantitative methods provide structured, numerical analysis to support more
accurate and objective decision-making.
2. Define descriptive statistics.
Answer: Descriptive statistics summarize and describe the main features of a dataset
Rationale: They allow managers to understand data trends and patterns without making
predictions.
3. What is inferential statistics?
Answer: Inferential statistics enable generalizations about a population based on
sample data
Rationale: It allows decision-makers to predict outcomes and test hypotheses from
limited data.
, 4. Which measure of central tendency is most affected by outliers?
Answer: Mean
Rationale: Extreme values can skew the mean, making it less representative of the
dataset.
5. What does a high standard deviation indicate?
Answer: Data points are widely spread around the mean
Rationale: A high standard deviation shows greater variability in the dataset.
6. What does a p-value less than 0.05 indicate in hypothesis testing?
Answer: Strong evidence against the null hypothesis
Rationale: This suggests the observed effect is statistically significant and unlikely due to
chance.
7. What is a key assumption of linear regression?
Answer: Homoscedasticity (constant variance of errors)
Rationale: Regression analysis assumes equal variance of residuals to produce unbiased
estimates.
8. What is the purpose of a decision tree?
Answer: To visualize decisions, possible outcomes, and associated probabilities
Rationale: It helps structure complex decisions and evaluate risk-reward trade-offs.
9. What is time series analysis used for?
Answer: Predicting future values based on historical data
Rationale: Identifying patterns and trends in past data allows informed forecasting.
10. What does R² (coefficient of determination) measure?
Answer: The proportion of variance in the dependent variable explained by the
independent variable(s)
Rationale: It indicates how well the regression model fits the data.
