--%>

Calculate the p- value

Medical tests were conducted to learn about drug-resistant tuberculosis. Of 284 cases tested in New Jersey, 18 were found to be drug- resistant. Of 536 cases tested in Texas, 10 were found to be drugresistant. Do these data indicate that New Jersey has a statistically significant higher outbreak of drugresistant tuberculosis cases? Use a .03 level of significance. What is the p- value, and what is your conclusion? Is the conclusion any different under critical-value approach?

E

Expert

Verified

Data

Let P1' denote observed proportion of drug resistant TB in New Jersey population and P2' is observed proportion of drug resistant TB in Texas, then

P1'= 18/284   = 0.0633803

P2' = 10/536  = 0.0186567

Hypothesis Formation

Null Hypothesis H0:    P1 - P2 = 0

Alternative Hypothesis H1:    P1 - P2 > 0

Z Statistic

Z = (P1' - P2')/SQRT(P(1-P)/(1/n1+1/n2))

Where P = (18+10)/(284+536)

                 = 0.0341463

Critical Region

Reject null hypothesis in favor of alternative if Z is greater than Z critical value of 1.88

Computation

Z = (0.0633803 - 0.0186567)/SQRT(0.0341463*(1-0. 0.0341463)(1/284+1/536))

   = 0.0447236/SQRT(0.0329803*0.0053868)

   = 0.0447236/SQRT(0.0001777)

   = 0.0447236/0.01333

   = 3.36

Decision

Null hypothesis is rejected in favor of alternative as Z value is greater than Z critical value. So we can say that New Jersey has statistically greater outbreak of drug resistant TB.

   Related Questions in Basic Statistics

  • Q : Simplified demonstration of Littles Law

    Simplified demonstration of Little’s Law:

    Q : Derived quantities in Queuing system

    Derived quantities in Queuing system: • λ = A / T, Arrival rate • X = C / T, Throughput or completion rate • ρ =U= B / T, Utilization &bu

  • Q : Regression Analysis 1. A planning

    1. A planning official in the Texas Department of Community Affairs, which works in the office next to you, has a problem. He has been handed a data set from his boss that includes the costs involved in developing local land use plans for communities wi

  • Q : What is Inter-arrival times

    Inter-arrival times:A) Requests arrive randomly, often separated by small time intervals with few long separations among themB) The time until the next arrival is independent of when the last arrival occurredC) Coro

  • Q : Creating Grouped Frequency Distribution

    Creating Grouped Frequency Distribution: A) At first we have to determine the biggest and smallest values. B) Then we have to Calculate the Range = Maximum - Minimum C) Choose the number of classes wished for. This is generally between 5 to 20. D) Find out the class width by dividing the range b

  • Q : Problems on ANOVA We are going to

    We are going to simulate an experiment where we are trying to see whether any of the four automated systems (labeled A, B, C, and D) that we use to produce our root beer result in a different specific gravity than any of the other systems. For this example, we would l

  • Q : Explain Service times Service times: A)

    Service times:A) In most cases, servicing a request takes a “short” time, but in a few occasions requests take much longer.B) The probability of completing a service request by time t, is independent of how much tim

  • Q : Use the NW corner rule to find an

      (a) Use the NW corner rule to find an initial BFS, then solve using the transportation simplex method. Indicate your optimal objective function value. (b) Suppose we increase s1 from 15 to 16, and d3 from 10 to 11. S

  • Q : Data Description 1. If the mean number

    1. If the mean number of hours of television watched by teenagers per week is 12 with a standard deviation of 2 hours, what proportion of teenagers watch 16 to 18 hours of TV a week? (Assume a normal distribution.) A. 2.1% B. 4.5% C. 0.3% D. 4.2% 2. The probability of an offender having a s

  • Q : Define Service Demand Law

    Service Demand Law:• Dk = SKVK, Average time spent by a typical request obtaining service from resource k• DK = (ρk/X