The table below shows the U.S population from 1970 to 2020.Use the data to respond to the following questions.Year179018001810182018301840185018601870188018901900191019201930194019501960197019801990200020102020t = Timesince 17900102030405060708090100110120130140150160170180190200210220230Population(Millions)3.9295.3087.2409.63812.86617.06923.19231.44339.81850.15662.94875.99591.972105.711122.775131.669150.697179.323203.302226.542248.710282.399308.746331.449a.Create a scatter plot representing therelationship between the U.S populationand census year.b. Describe any relationships between thetime since 1970 and the population.c. Create a formula for the U.S population interms of the time (t) since 1790.d. Use the model to predict the U.S populationin 2050.

Given the US census data from 1790 to 2020. YeartPopulation (in…

Answered: The table below shows the U.S…

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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Following shows the numbers of Amazon Prime members in the millions, each quarter from 2016 to 2021. Quarter 2016 2017 2018 2019 2020 2021 1 26 36 48 62 81 98 2 27 37 50 65 83 103 3 29 40 53 69 86 109 4 33 44 57 74 93 117 Construct a line chart using the data. Describe the relationship between the time and number of subscribers.
You collect data of average annual returns for Amazon Stock and Microsoft Stock and make the following table: (This data can be copied into Excel.) Year Amazon Return Microsoft Return 2013 0.5896 0.1221 2014 -0.2218 0.2416 2015 1.1778 0.1944 2016 0.1095 0.1200 2017 0.5596 0.3766 2018 0.2843 0.1874 2019 0.3216 0.5526 You use this data to answer the research question: are true population Amazon Returns greater than true population Microsoft Returns?
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Please answer question 9 fully, data included: Size($) Rent(sq.feet) 850 1950 1450 2600 1085 2200 1232 2500 718 1950 1485 2700 1136 2650 726 1935 700 1875 956 2150 1100 2400 1285 2650 1985 3300 1369 2800 1175 2400 1225 2450 1245 2100 1259 2700 1150 2200 896 2150 1361 2600 1040 2650 755 2200 1000 1800 1200 2750 A real estate agent wishes to examine the relationship between the selling price of a home (measured in thousands of dollars) and its size (measured in square feet). In particular she wants to assess if the size of the home can accurately predict the house’s selling price.
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