The following table shows the cost C of traffic accidents, in cents per vehicle-mile, as a function of vehicular speed s, in miles per hour, for commercial vehicles driving at night on urban streets. Speed s 20 1.3 25 30 35 0.4 0.1 0.3 40 0.9 2.2 5.8 45 50 Cost C The rate of vehicular involvement in traffic accidents (per vehicle-mile) can be modeled as a quadratic function of vehicular speed s, and the cost per vehicular involvement is roughly a linear function of s, so we expect that C (the product of these two functions) can be modeled as a cubic function of s. (a) Use regression to find a cubic model for the data. (Keep two decimal places for the regression parameters written in scientific notation.) Oc = 0.005643s - 0.2365s + 0.789s - 2.54 C= 0.000422s - 0.0294s + 0.562s -1.65 C=0.001245s - 0.1234s Oc- 0.000348s - 0.0946s + 0.341s - 1.91 Oc= 0.000526s - 0.0351s + 0.976s - 0.34 OC= + 0.652s - 0.48 answer means in practical terms. (Use the model found in part (a). Round your answer to two decimal places.) mph at night on urban streets, the cost of a traffic accident will be [ (b) Calculate C(48) and explain what your C(48) = [ ). so for a vehicle driving |cents per vehicle mile. (c) At what speed is the cost of traffic accidents (for commercial vehicles driving at night on urban streets) at a minimum? (Use the model found in part (a). Consider speeds between 20 a 50 miles per hour. Round your answer to the nearest whole number.) mph

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A: The given expression is 3/8 + 5/24.Simplify the given expression as follows.

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Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.