Salmonella in yield. Salmonella infection is the most common bacterial foodborne illness in the United States. How current is Salmonella in yield grown in the major agricultural region of Monterey, California? Experimenters from the U.S. Department of Agriculture (USDA) conducted tests for Salmonella in yield grown in the region and published their results in Applied and Environmental Microbiology (April 2011). In a sample of 252 societies attained from water used to wash the region, 18 tested positive for Salmonella. In an independent sample of 476 societies attained from the region's wildlife (e.g., catcalls), 20 tested positive for Salmonella. Is this sufficient substantiation for the USDA to state that the frequency of Salmonella in the region's water differs from the frequency of Salmonella in the region's wildlife? Use a = .01 to make your decision

Short Answer

Expert verified

There is no evidence to reject the null hypothesis (H0) at α= 0.01

Step by step solution

01

Step-by-Step Solution Step 1: Check the Null hypothesis and Alternative hypothesis

Let p1 be the proportion of Salmonella in the region's water and p2 be the proportion of Salmonella in the region's wildlife. The hypotheses are given below:

Null hypothesis:

H₁: P1 – P2 = 0

There is no evidence that the prevalence of Salmonella in the region's water differs from the prevalence of Salmonella in the region's wildlife.

Alternative hypothesis:

He: P1 – P2 ≠ 0

There is evidence that the prevalence of Salmonella in the region's water differs from the prevalence of Salmonella in the wildlife.

02

Calculate the critical value

calculate the critical value.

Let the confidence position be0.99.

1-α = 0.99

α = 1-0.99

= 0.01

α2=0.005

From Excursus Table II, the value of za2is given below.

za2=Z0.005=2.58

So,thevalueofza2is2.58.

03

Rejection region

Rejection region:

If Z >za2(= 2.58), then reject the null hypothesis.

its Z > za2(= -2.58), then reject the null hypothesis.

04

Calculate the value of P1and P2

Calculate the value of P¯1and P¯2

05

Calculate the value of P1

Consider α = 0.10, n1= 476,x1 = 18, and x2 = 20.

The value of P¯1is obtained as shown below.

P¯1=x1n1=18252=0.0714

06

Calculate the value of P2

The value of P¯2is obtained as shown below.

P¯2=x2n2=20252=0.0420

07

calculate the value of p

The value of P¯is obtained below.

P¯=x1+x2n1+n2=18+20252+476=38728=0.0522

08

Calculate the test statistic

Calculate the test statistic (z).

The formula for z is given below.

Z=p¯1p¯2p¯q¯(1n+1n)

There P1= 0.0714, P2=0.0420, P = 0.0522, n1=252 and n2 =476.

Z=0.07140.04200.0522(10.0522)(1252+1476)=0.02940.0174=1.69

09

Conclusion

The critical value is 2.58, and the value of z is 1.69.

Here, the value of z is lesser than the value ofza2.

That is, z (= 1.69) <za2(=2.58).

So, by the rejection rule, don't reject the null hypothesis (H0)

Interpretation

Thus, it can be concluded that there is no evidence to reject the null hypothesisH0 at α = 0.01.

Hence, there is no evidence that the prevalence of Salmonella in the region's water differs from the prevalence of Salmonella in the region's wildlife.

From the above steps, there is no evidence to reject the null hypothesis at α = 0.01.

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Most popular questions from this chapter

Assume that x is a binomial random variable with n = 1000 andp = 0.50. Use a normal approximation to find each of the following probabilities:

a. P(x>500)

b.P(490x<500)

c.P(x>550)

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a.Ha:σ225;α=0.5;n=16

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A random sample of n = 6 observations from a normal distribution resulted in the data shown in the table. Compute a 95% confidence interval for σ2

Question: Deferred tax allowance study. A study was conducted to identify accounting choice variables that influence a manager’s decision to change the level of the deferred tax asset allowance at the firm (The Engineering Economist, January/February 2004). Data were collected for a sample of 329 firms that reported deferred tax assets in 2000. The dependent variable of interest (DTVA) is measured as the change in the deferred tax asset valuation allowance divided by the deferred tax asset. The independent variables used as predictors of DTVA are listed as follows:

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BONUS: x2 = 1 if firm maintains a management bonus plan,

0 if not

MVALUE: x3 = market value of common stock

BBATH: x4 = 1 if operating earnings negative and lower than last year,

0 if not

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A first-order model was fit to the data with the following results (p-values in parentheses):

Ra2 = .280

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  1. Interpret the estimate of the β coefficient for x4.
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Question: The speed with which consumers decide to purchase a product was investigated in the Journal of Consumer Research (August 2011). The researchers theorized that consumers with last names that begin with letters later in the alphabet will tend to acquire items faster than those whose last names begin with letters earlier in the alphabet—called the last name effect. MBA students were offered free tickets to an event for which there was a limitedsupply of tickets. The first letter of the last name of those who responded to an email offer in time to receive the tickets was noted as well as the response time (measured in minutes). The researchers compared the response times for two groups of MBA students: (1) those with last names beginning with one of the first nine letters of the alphabet and (2) those with last names beginning with one of the last nine letters of the alphabet. Summary statistics for the two groups are provided in the table.

First 9

Letters: A–I

Last 9

Letters: R–Z

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Mean response time (minutes)

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Standard deviation (minutes)

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Source: Based on K. A. Carlson and J. M. Conrad, “The Last Name Effect: How Last Name Influences Acquisition Timing,” Journal of Consumer Research, Vol. 38, No. 2, August 2011.

a. Construct a 95% confidence interval for the difference between the true mean response times for MBA students in the two groups.

b. Based on the interval, part a, which group has the shorter mean response time? Does this result support the researchers’ last name effect theory? Explain.

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