Problem 1: Aviation and InnovationA researcher attempts to study the effect of aviation connectivity on innovation usingregression analysis. They gathered the following data in 2015, including inventors, the totalnumber of inventors located in city i for patents registered in 2015, connectivity, a measure ofglobal connectivity through aviation networks of city i's airports, Personal Income, the totalpersonal income recorded for 2015 in City i, and Population, the level of population in 2015 incity i.. reg inventors connectivity Personal Income PopulationSourcedfMSNumber of obs526F(3, 522)236.47Model1.6167e+093538888533Prob > F0.0000Residual1.1896e+09522 2278847.84R-squared0.5761Adj R-squaredadj_R2%3DTotal2.8062e+095255345188.9Root MSE1509.6%3Dinventors Coefficient Std. err.tP>|t|[95% conf. interval]tCI-LBCI-UBconnectivity0356768.0093273le.e00Personal_Income00005636.92e-068.140.000.0000427.0000699beta_370.32327Population.0003614-5.080.000-.0025461-.0011261_cons74.578380.940.346-76.18737216.8339a) Is this dataset cross-sectional, panel, or a time series? Whyb) Compute the 5 missing values in the regression table. Show your work.c) Carefully interpret the regression coefficients and their statistical significance. Is this in linewith your expectations?Page 3 of 14

A researcher attempts to study the effect of aviation connectivity on innovation using regression…

Answered: A researcher attempts to study 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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Use the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to develop the multiple linear regression model. Assume a 5% level of significance. Which independent variable is the strongest predictor of the average P/E ratio of a company? A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…
ABC, Inc., sells tea products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. She determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales.Question: List two advantages and two limitations of regression analysis.
a. Develop the least squares estimated regression equation that relates labor hours to house square footage and type of flooring. b. Use the regression equation developed in part (a) to predict labor hours when the house size is 3350 square feet and the type of flooring is wood.
La Quinta Inns has a competitive edge over its rivals because it: uses regression analysis to determine which variables most influence profitability. has better television advertisements. picks larger locations than its rivals. builds only along interstate highways. consistently receives four-star ratings for its inns.
Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
One of the biggest changes in higher education in recent years has been the growth of online universities. The Online Education Database is an independent organization whose mission is to build a comprehensive list of the top accredited online colleges. The following table shows the retention rate (%) and the graduation rate (%) for 29 online colleges.a). Use Excel Data Analysis Tool – Regression to get the relationship between the two variables;b). Create a scatter diagram for the two variables and display regression equation and R square on chart, then explain the relationship between the variables;c). Did the estimated regression equation provide a good fit?d). Suppose you were the president of South University. After reviewing the results, would you be able to use the regression result for forecasting. College RR(%) GR(%) Western International University 7 25 South University 51 25 University of Phoenix 4 28 American InterContinental University 29 32 Franklin…
Several states have argued that the 65-mph speed limit has no justification and have refused to enforce it. The federal Department of Transportation (DOT) believes that the 65-mph limit saves lives. To illustrate its contention, the department regressed the number of traffic fatalities (Y) last year in a state on the state’s population (X1), the number of days of snow cover (X2), and the average speed of all cars (X3). The results are shown below. Table 10: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .821 a .780 .613 3.258 a. Predictors: (Constant), population, days of snow, average speed Table 11: Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.4 2.957 .473 .584 Population .00029 .00003 .0034 9.667 .000 Days of Snow 2.4 .62 .759 3.871 .000 Average Speed 10.3 1.1…

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