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Chebyshev's theorem and empirical rule can be used to approximate proportion of observations within a given interval. When should one use empirical rule instead of Chebyshev's theorem?

Chebyshev's theorem and empirical rule can be used to approximate proportion of observations within a given interval. When should one use empirical rule instead of Chebyshev's theorem?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Chebyshev's theorem and empirical rule can be used to approximate proportion of observations within a given interval. When should one use empirical rule instead of Chebyshev's theorem? a. Empirical rule should always be used over Chebyshev's theorem O b. When the data has a bell-shaped distribution O c. When the number of observations is more than 30 O d. When the data has a symmetric distribution
Transcribed Image Text:Chebyshev's theorem and empirical rule can be used to approximate proportion of observations within a given interval. When should one use empirical rule instead of Chebyshev's theorem? a. Empirical rule should always be used over Chebyshev's theorem O b. When the data has a bell-shaped distribution O c. When the number of observations is more than 30 O d. When the data has a symmetric distribution
Which of the following statements is true regarding cross-sectional data and time-series data? O a. For cross-sectional data, data are collected in different geographical area O b. For time-series data, data are collected at different points in time O c. For time-series data, the variable of interest in the data is time O d. For cross-sectional data, the variable in the data is a discrete variable
Transcribed Image Text:Which of the following statements is true regarding cross-sectional data and time-series data? O a. For cross-sectional data, data are collected in different geographical area O b. For time-series data, data are collected at different points in time O c. For time-series data, the variable of interest in the data is time O d. For cross-sectional data, the variable in the data is a discrete variable
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