The Pearson dispersion estimator is , well above the Poisson value one. A Quasi-Poisson regression retains the logarithmic mean model but usesThis is a quasi-likelihood specification; it does not by itself identify a count probability distribution. For a common , the quasi-score equation is the Poisson score divided by , so its roots and fitted means are unchanged. ThusCoefficient standard errors are multiplied by . The altitude standard error becomes , giving the requested approximate normal confidence intervalIt excludes zero, so retain altitude on this approximate 5% test. Its test statistic is about after allowing for overdispersion, rather than the Poisson value . Rescaling uncertainty cannot repair a systematically misspecified mean; the diagnostics in part (e) motivate reconsidering that mean as well.
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