An economist wants to estimate the relationship between earnings (in thousands of dollars) and years ofeducation.She estimates the model Earnings = BO + B1 *Education + ε.The following is a portion of her results.Coefficient Standard Error15.774.21InterceptEducationWhich of the following is true?3.81.4p-value0.0030.032O If education is increased by one year, we predict that earnings will increase by $4,210.O If earnings are increased by $1000, we predict that education will increase by .21O If education is increased by one year, we predict that earnings will increase by $3200.O If earnings are increased by $1000, we predict that education will increase by .032 years.

From the information, given thatLet X denotes the years of education( in years) the independent…

Answered: An economist wants to estimate the…

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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Rail ridership during the summer months in the North-East is believed to beclosely related to the number of tourists visiting the region. The following tableshows the data on the number of tourists and North-East ridership for the past16 years. (Answer in Excel showing formulas for answers)Year Tourists( in millions) Rail Ridership (in millions) 2000 9 2.32001 4 1.9 2002 7 1.7 2003 5 1.8 2004 12 2.8 2005 13 2.9 2006 14 2.42007 20 4.8 2008 7 1.3 2009 5 1.12010…
1) Height of Golf Ball Determine the rate of change in the table and identify whether this data is linear, exponential or quadratic. Time (s) Height (ft) 4 1 68 2 100 100 4 68
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An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression…

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