estimate the following multiple regression model log⁑(𝒕𝒐𝒕𝒂𝒍_𝒅𝒆&#

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answerhappygod
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estimate the following multiple regression model log⁑(𝒕𝒐𝒕𝒂𝒍_𝒅𝒆&#

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estimate the following multiple regression model
log⁑(𝒕𝒐𝒕𝒂𝒍_𝒅𝒆𝒂𝒕𝒉𝒔_𝒑𝒆𝒓_π’Žπ’Šπ’π’π’Šπ’π’)
= 𝛽0 + 𝛽1log⁑(𝒕𝒐𝒕𝒂𝒍_𝒄𝒂𝒔𝒆𝒔_𝒑𝒆𝒓_π’Žπ’Šπ’π’π’Šπ’π’) + 𝛽2π’ˆπ’…π’‘_𝒑𝒆𝒓_π’„π’‚π’‘π’Šπ’•π’‚ + 𝑒
Report your regression results in a sample regression function.
Interpret
the estimated coefficient of gdp_per_capita and explain whether the
sign
of the coefficient matches your predictions.
Using the regression results from (iii), predict the number
of
total_deaths_per_million for Australia with gdp being 44.64871 and
total deaths per million being 122946.616 and compare your
prediction
with the actual number of total_deaths_per_million (198.967)
observed for
Australia.
Using the estimated model in (iii), test whether the coefficient
of
gdp_per_capita is statistically significant at 1% level of
significance.
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SUMMARY OUTPUT Regression Statistics Multiple R 0.90067334 R Square 0.81121247 Adjusted R Sq 0.80574037 Standard Erro 0.67848116 Observations 72 ANOVA df Regression Residual Total SS MS F Significance F 2 136.485335 68.2426673 148.245119 1.0497E-25 69 31.7632317 0.46033669 71 168.248566 t Stat Coefficients standard Error Intercept -3.5473359 0.59453913 gdp_per_capi-0.0288239 0.00501823 log(total_case 0.96688852 0.05730568 -5.9665305 -5.7438275 16.872472 P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 9.3401 E-08 -4.733409 -2.3612627 -4.733409 -2.3612627 2.2849E-07 -0.038835 -0.0188128 -0.038835 -0.0188128 3.4659E-26 0.85256681 1.08121023 0.85256681 1.08121023
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