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MATLAB!!!!!!!!!!!! Table Part 1 For each of the forty largest countries in the world (according to 1990 population figures), data are given for the country's

MATLAB!!!!!!!!!!!!

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Table Part 1 For each of the forty largest countries in the world (according to 1990 population figures), data are given for the country's life expectancy at birth, number of people per television set, and number of people per physician. The data is stored a table tvPLE in the mat file Television Physician and Life Expectancy Write a script that has two subfunctions: 1) findMinimumRecord that find the minimum life expectancy in the dataset, and the extract the accompanying record, and 2) ExtractRecordBasedonCountry to find the record given the name of a country, and extract the record. The main script should call the two functions as indictated in the Learner Template. The countries in the table are Argentina Bangladesh' "Brazil' Canada China Colombia" Egypt Ethiopia' France "Germany India Indonesia Iran Italy Japan 'Kenya 'Korea, North Korea, South' Mexico Morocco Myanmar (Burma) 'Pakistan' Peru Philippines' Poland 'Romania 'Russia South Africa Spain "Sudan Taiwan Tanzania Thailand Turkey 'Ukraine United Kingdom United States Venezuela Vietnam Zaire For example Table Part 1 For each of the forty largest countries in the world (according to 1990 population figures), data are given for the country's life expectancy at birth, number of people per television set, and number of people per physician. The data is stored a table tvPLE in the mat file Television Physician and Life Expectancy Write a script that has two subfunctions: 1) findMinimumRecord that find the minimum life expectancy in the dataset, and the extract the accompanying record, and 2) ExtractRecordBasedonCountry to find the record given the name of a country, and extract the record. The main script should call the two functions as indictated in the Learner Template. The countries in the table are Argentina Bangladesh' "Brazil' Canada China Colombia" Egypt Ethiopia' France "Germany India Indonesia Iran Italy Japan 'Kenya 'Korea, North Korea, South' Mexico Morocco Myanmar (Burma) 'Pakistan' Peru Philippines' Poland 'Romania 'Russia South Africa Spain "Sudan Taiwan Tanzania Thailand Turkey 'Ukraine United Kingdom United States Venezuela Vietnam Zaire For example

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