A technology specialist studied the relationship between time spent on social media and age. One observation found that a 50-year-old person spends 2 hour per week on social media. Asecond observation showed that a 25-year-old person spends 12 hours per week on social media. Assuming time spent per week on social media 7 (in hr) is a linear function of age a (inyr), find a linear model of this event.THxUse the model to find the age (in yr) of a person who spends 10 hours per week on social media.30уг

Answers..a. Linear model A=(-2.5)t+55b. Age 30 years old person use social media 10 hours per week.…

Answered: A technology specialist studied the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A quality control team studies the relationshipbetween years of experience (x) for individualdesign employees and ability to complete acomplex project within a certain time frame (y),where Y = 1 if the project is successfullycompleted, and Y = 0 if not. We know: b0 = −1.68and b1 = 0.12.a) Write the estimated logit function.b) Estimate the odds that a design employeewith 10 years of experience completes thecomplex project.c) Find and interpret the estimated odds ratiofor this model.
Write an absolute value function f(t) to describe an individual variance from normal body temperature where t is the individual current temperature
A study done in 1994, of Maryland's portion of Chesapeake Bay found the following information about stocks of market-sized oysters. The stock population was 218 million, the stock will not exceed 5089 million oysters, and the intrinsic exponential growth rate is 0.274 per year.
Nitrogen dioxide, NO2, is an air pollutant resulting from burning fossil fuels in cars and power plants. The following table shows the decrease in the national average of the concentration in parts per billion (ppb) of NO2 for selected years. Year 2014 2015 2016 2017 2018 NO2 (ppb) 40.8107 39.7886 38.7972 37.8209 36.8752 Use exponential regression to find an exponential decay function for the concentration, C, of NO2 t years after 2014. Round constants to the nearest ten-thousandth. C = Use the model to predict the concentration of NO2 (in ppb) in 2050. Round to the nearest whole number. ? ppb

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