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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def pager_fatality_rates():
 """USGS Pager fatality estimation model. Fatality rate(MMI) = cum. standard normal dist(1/BETA * ln(MMI/THETA)). Reference: Jaiswal, K. S., Wald, D. J., and Hearne, M. (2009a). Estimating casualties for large worldwide earthquakes using an empirical approach. U.S. Geological Survey Open-File Report 2009-1136. v1.0: Theta: 14.05, Beta: 0.17, Zeta 2.15 Jaiswal, K, and Wald, D (2010) An Empirical Model for Global Earthquake Fatality Estimation Earthquake Spectra, Volume 26, No. 4, pages 1017–1037 v2.0: Theta: 13.249, Beta: 0.151, Zeta: 1.641) (http://pubs.usgs.gov/of/2009/1136/pdf/ PAGER%20Implementation%20of%20Empirical%20model.xls) :returns: Fatality rate calculated as: lognorm.cdf(mmi, shape=Beta, scale=Theta) :rtype: dic """

    # Model coefficients
    theta = 13.249
    beta = 0.151
    mmi_range = list(range(2, 11))
    fatality_rate = {mmi: 0 if mmi < 4 else log_normal_cdf(
        mmi, median=theta, sigma=beta) for mmi in mmi_range}
    return fatality_rate