In the research, there was the need to base decisions on the behavior of the sample. whatsoever discrepancy in the sample data would lead to inaccurate inference. Which made the selection of appropriate drug user groups and sample size crucial for the success of the research? Steve mentioned that the senior citizens resisted biometric system during the pilot lamp implementation. They form 27 percent of the VB & FF customers and hence it was unavoidable to gauge this reaction. Adults and middle aged citizens form 18 and 45% of the VB and FF customer respectively. Together they constitute 63% of the total customers and their prospect is crucial for the implementation of this system. Anne had mentioned that teen adults are tech labour and hence do not resist new technological products. This is not necessary to select the user group of young adults below 25 years. The optimum sample size for the user groups is 90.
This also was the correct supposition. Edith had said that the company should only fit if 65 percent of the personal banking customers favored the biometric system. By relating the hypothesis we were able to determine if sample proportion was equal to or greater than 65%.
Rejecting the null hypothesis when it is true is cognise as a Type I error.
Failing to hold out the null when it is false is known as Type II error. The level of signifi tailce, alpha denotes the probability of a Type I error occurring. Since the level of significance is specified before finish the test. The risk of a Type I error occurring can be controlled by the person doing the research. The probability of Type I error can be reduced by change magnitude the probability of making Type II error and ungodliness versa. My decision was made to reject the...
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