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Understanding Discrete and Continuous Random Variables in Hydrology (a) List at least five examples of hydrologic discrete variables and five hydrologic continuous variables. Discuss and/or explain and how and/or why these variables in each category qualify the stated variables? (b) For the English River with watershed area 6230 km2and located in Thunder Bay district of Northwestern Ontario, find the median and mode-class of the discrete flow dataset as summarized below in the table. (c) Compute statistical parameters (mean, variance, coefficients of skewness, kurtosis, variation, and the lag one correlation coefficient) for the discrete flow data set as summarized below in the table. (d) Based on the assumption that the 42-year of flow data of the English River follow a normal probability distribution (that is a theoretical distribution of flow being a continuous variable), compute the peak flow estimates the corresponding probability of occurrence of 0.2, 0.1, and 0.01.

Understanding Discrete and Continuous Random Variables in Hydrology (a) List at least five examples of hydrologic discrete variables and five hydrologic continuous variables. Discuss and/or explain and how and/or why these variables in each category qualify the stated variables? (b) For the English River with watershed area 6230 km2and located in Thunder Bay district of Northwestern Ontario, find the median and mode-class of the discrete flow dataset as summarized below in the table. (c) Compute statistical parameters (mean, variance, coefficients of skewness, kurtosis, variation, and the lag one correlation coefficient) for the discrete flow data set as summarized below in the table. (d) Based on the assumption that the 42-year of flow data of the English River follow a normal probability distribution (that is a theoretical distribution of flow being a continuous variable), compute the peak flow estimates the corresponding probability of occurrence of 0.2, 0.1, and 0.01.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Understanding Discrete and Continuous Random Variables in Hydrology

(a) List at least five examples of hydrologic discrete variables and five hydrologic continuous variables. Discuss and/or explain and how and/or why these variables in each category qualify the stated variables?

(b) For the English River with watershed area 6230 km2and located in Thunder Bay district of Northwestern Ontario, find the median and mode-class of the discrete flow dataset as summarized below in the table.

(c) Compute statistical parameters (mean, variance, coefficients of skewness, kurtosis, variation, and the lag one correlation coefficient) for the discrete flow data set as summarized below in the table.

(d) Based on the assumption that the 42-year of flow data of the English River follow a normal probability distribution (that is a theoretical distribution of flow being a continuous variable), compute the peak flow estimates the corresponding probability of occurrence of 0.2, 0.1, and 0.01.

statistical parameters (mean, variance, coefficients of skewness, kurtosis, prrelation coefficient) for the discrete flow data set as summarized below the assumption that the 42-year of flow data of the English River follow on (that is a theoretical distribution of flow being a continuous variable), • nates the corresponding probability of occurrence of 0.2, 0.1, and 0.01. Year Flow (m³/s) Year Flow (m³/s) 1976 138 144 1977 69.4 1978 866 163 132 6661 1979 164 152 1980 70.7 2002 224 1981 75 2003 201 1982 112 2004 90.4 1983 96.2 2005 223 9007 2007 1984 118 171 1985 245 154 986 1987 800. 197 175 600 2010 245 222 8861 185 2011 84.4 152 2012 172 102 2013 1992 222 2014 201 1993 140 2015 235 1994 2016 125 1995 106 2017 90.8 210 2018 121 9661
Transcribed Image Text:statistical parameters (mean, variance, coefficients of skewness, kurtosis, prrelation coefficient) for the discrete flow data set as summarized below the assumption that the 42-year of flow data of the English River follow on (that is a theoretical distribution of flow being a continuous variable), • nates the corresponding probability of occurrence of 0.2, 0.1, and 0.01. Year Flow (m³/s) Year Flow (m³/s) 1976 138 144 1977 69.4 1978 866 163 132 6661 1979 164 152 1980 70.7 2002 224 1981 75 2003 201 1982 112 2004 90.4 1983 96.2 2005 223 9007 2007 1984 118 171 1985 245 154 986 1987 800. 197 175 600 2010 245 222 8861 185 2011 84.4 152 2012 172 102 2013 1992 222 2014 201 1993 140 2015 235 1994 2016 125 1995 106 2017 90.8 210 2018 121 9661
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