Each of two pesticide brands is applied to 100 containers of fire ants. Brand1 killed all ants in 65 of 100 containers within two hours, and Brand 2 killed all ants in 58 of 100 containers within two hours. b. Apply Fisher’s exact test in part (a) and compare.part (a) Is there statistically significant evidence to suggest Brand 1 works better? Use the hypothesis test based on the normal distribution. Be sure to check all assumptions, obtain the p-value, and state your conclusion.

Question
Asked Nov 22, 2019
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Each of two pesticide brands is applied to 100 containers of fire ants.
Brand1 killed all ants in 65 of 100 containers within two hours, and
Brand 2 killed all ants in 58 of 100 containers within two hours.

b. Apply Fisher’s exact test in part (a) and compare.

part (a)

 Is there statistically significant evidence to suggest Brand 1 works better? 
Use the hypothesis test based on the normal distribution.
 Be sure to check all assumptions, obtain the p-value, and state your conclusion. 

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Expert Answer

Step 1

The test for two proportions to compare the two brands using MINITAB software is given below:

Software procedure:

Step-by-step procedure to test two proportions using MINITAB software:

  • Choose Stat > Basic Statistics > 2 Proportions.
  • In Summarized data, for sample 1 enter the brand 1 values; number of events as 61 and number of trials as 100.
  • for sample 2 enter the brand 2 values; number of events as 58 and number of trials as 100.
  • Check Options, enter Confidence level as 0.
  • Choose greater than in alternative.
  • Choose test method as estimate proportions separately.
  • Click OK in all dialogue boxes.
Step 2

Output using MINITAB softw...

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Test and Cl for Two Proportions Method pi: proportion where Sample 1 Event p: proportion where Sample 2 Event Difference: p, - p Estimation for Difference 95% Lower Bound for Difference Difference -0.042897 0.07 CI based on normal approximation Test Null hypothesis Ho pi -p 0 Alternative hypothesis H: p p: 0 Method Z-Value P-Value Normal approximation 0.154 1.02 Fisher's exact 0.192

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Hypothesis Testing

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