Uncertainty Quiz

Measurement uncertainty: What is the difference between precision and accuracy in measurement?

• Precision is about the consistency of the measurement, while accuracy is about the color of the measurement.

• Precision refers to the size of the measurement, while accuracy refers to the shape of the measurement.

• Precision refers to the closeness of two or more measurements to each other, while accuracy refers to the closeness of a measurement to the true value.

• Precision is related to the instrument used, while accuracy is related to the time of the measurement.

Measurement uncertainty: Explain the concept of systematic and random errors in measurement.

• Systematic errors are consistent and repeatable, while random errors are unpredictable and can occur in any direction.

• Systematic errors occur in any direction, while random errors are consistent and predictable.

• Systematic errors are unpredictable, while random errors are consistent and repeatable.

• Systematic errors are always in the same direction, while random errors are always in the opposite direction.

Probability distributions: What is the difference between a discrete and a continuous probability distribution?

• Discrete probability distributions are used for continuous data, while continuous probability distributions are used for discrete data.

• Discrete probability distributions have an infinite number of possible outcomes, while continuous probability distributions have a finite number of possible outcomes.

• Discrete probability distributions are always symmetrical, while continuous probability distributions are always asymmetrical.

• Discrete probability distributions have a finite number of possible outcomes, while continuous probability distributions have an infinite number of possible outcomes.

Probability distributions: Describe the concept of mean, median, and mode in a probability distribution.

• Mean is the middle value, median is the sum of all values, and mode is the highest value

• Mean is the value that appears most frequently in the distribution, median is the average, and mode is the middle value

• Mean is the highest value in the distribution, median is the lowest value, and mode is the sum of all values

• Mean is the average of all the values in the distribution, median is the middle value when the data is arranged in ascending order, and mode is the value that appears most frequently in the distribution.

Error analysis: How does error propagation affect the final result of a calculation?

• Error propagation has no effect on the final result of a calculation.

• Error propagation amplifies the uncertainty in the input values, leading to a larger uncertainty in the final result.

• Error propagation only affects the input values, not the final result.

• Error propagation reduces the uncertainty in the input values, leading to a smaller uncertainty in the final result.

Error analysis: Explain the concept of absolute and relative error in error analysis.

• Absolute error is always positive, while relative error can be positive or negative.

• Absolute error is the difference between the measured value and the true value, while relative error is the ratio of the absolute error to the true value.

• Absolute and relative error are measures of the accuracy of a measurement.

• Absolute error is the error that occurs when the measurement is taken in absolute terms, while relative error is the error that occurs when the measurement is taken in relative terms.

Significant figures: When should you round a number to the correct number of significant figures?

• When you want to increase the precision of the number

• When you want to make the number easier to remember

• When reporting a measurement or calculation result

• When you want to make the number look nicer

Significant figures: How do you determine the number of significant figures in a calculated result?

• By using the most number of significant figures in the given values used in the calculation

• By using the least number of significant figures in the given values used in the calculation.

• By rounding the calculated result to the nearest whole number

• By counting the number of decimal places in the calculated result

Standard deviation: What does the standard deviation measure in a set of data?

• The maximum value in a set of data

• The average value of a set of data

• The minimum value in a set of data

• Variation or dispersion of a set of values from the mean

Standard deviation: How does the standard deviation change when the data points are spread out more or less?

• The standard deviation is not affected by how the data points are spread out

• The standard deviation increases when the data points are spread out more, and decreases when the data points are spread out less.

• The standard deviation remains the same regardless of how the data points are spread out

• The standard deviation decreases when the data points are spread out more, and increases when the data points are spread out less