A retailer has 300 physical stores, which make 95% of the revenue; the rest of the revenue comes from an online store. The total number of visits for all the physical stores in a month is 66,000, and the conversion rate in store is 30%. The online store, in a month, receives 10,000 visits; the bounce rate is 52%, the sessions that continue navigating in the store and have a cart are 45%, and the abandonment cart rate is 45%. For the online store, the average order value is $50.00. (approximate numbers to the nearest integer if necessary). a) calculate the physical revenue per month?

b) calculate average revenue per physical store per month.

c) calculate the average order value in the physical stores.

d) calculate the online revenue per month

e) calculate the conversion rate online.
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Consider the following estimates from the early 2010s of shares of income to each group. country poorest 40% next 30% richest 30% bolivia 10 25 65 chile 10 20 70 uruguay 20 30 50 1.) using the 4-point curved line drawing tool, plot the lorenz curve for bolivia. properly label your curve. 2.) using the 4-point curved line drawing tool, plot the lorenz curve for uruguay. properly label your curve.

What are the solutions of the equation x4 – 5x2 – 14 = 0? use factoring to solve. someone !

When booking personal travel by air, one is always interested in actually arriving at one’s final destination even if that arrival is a bit late. the key variables we can typically try to control are the number of flight connections we have to make in route, and the amount of layover time we allow in those airports whenever we must make a connection. the key variables we have less control over are whether any particular flight will arrive at its destination late and, if late, how many minutes late it will be. for this assignment, the following necessarily-simplified assumptions describe our system of interest: the number of connections in route is a random variable with a poisson distribution, with an expected value of 1. the number of minutes of layover time allowed for each connection is based on a random variable with a poisson distribution (expected value 2) such that the allowed layover time is 15*(x+1). the probability that any particular flight segment will arrive late is a binomial distribution, with the probability of being late of 50%. if a flight arrives late, the number of minutes it is late is based on a random variable with an exponential distribution (lamda = .45) such that the minutes late (always rounded up to 10-minute values) is 10*(x+1). what is the probability of arriving at one’s final destination without having missed a connection? use excel.