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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 () at = 0.01.

Step by step solution

01

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:

H鈧: P1 鈥 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: P1 鈥 P2 鈮 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-伪 = 0.99

伪 = 1-0.99

= 0.01

= 0.005

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

za2=z0.005=2.58

=2.58

So, the value of za2is 2.58.

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 p1-
andp2-

05

Calculate the value of P1

Consider 伪 = 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=0.0522

08

Calculate the test statistic

Calculate the test statistic (z).

Z=P-1-P-2p-q-1n+1nz=0.0714-0.04200.0522(1-0.06522)1252+1456=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 of Za2.

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 hypothesis (H0) at 伪 = 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 伪 = 0.01.

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Descriptive Statistics: Support

Variables

N

Mean

StDev

Variance

Minimum

Maximum

Range

Support

992

67.755

26.871

722.036

0.000

155.000

155.000

Question: Promotion of supermarket vegetables. A supermarket chain is interested in exploring the relationship between the sales of its store-brand canned vegetables (y), the amount spent on promotion of the vegetables in local newspapers(x1) , and the amount of shelf space allocated to the brand (x2 ) . One of the chain鈥檚 supermarkets was randomly selected, and over a 20-week period, x1 and x2 were varied, as reported in the table.

Week

Sales, y

Advertising expenses,

Shelf space,

Interaction term,

1

2010

201

75

15075

2

1850

205

50

10250

3

2400

355

75

26625

4

1575

208

30

6240

5

3550

590

75

44250

6

2015

397

50

19850

7

3908

820

75

61500

8

1870

400

30

12000

9

4877

997

75

74775

10

2190

515

30

15450

11

5005

996

75

74700

12

2500

625

50

31250

13

3005

860

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43000

14

3480

1012

50

50600

15

5500

1135

75

85125

16

1995

635

30

19050

17

2390

837

30

25110

18

4390

1200

50

60000

19

2785

990

30

29700

20

2989

1205

30

36150

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  5. Explain how you could be misled by using a first-order model instead of an interaction model to explain how advertising expenditures and shelf space influence sales.
  6. Based on the type of data collected, comment on the assumption of independent errors.
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