Explain clearly and in your own words the reason for conducting a hypothesis test instead of simply comparing sample statistics
Case study 1: Amazon Fresh
The new Amazon Till-Less shop (Amazon Fresh) has just opened in London. It offers a shopping experience without the use of a till for payment. A study with an objective to examine the level of take-up for shopping Till-Less was conducted and has set the following research questions:
RQ1: Is the proportion of people who consider shopping at Amazon Fresh greater than 50%?
RQ2: Is the proportion of people who consider shopping at Amazon Fresh different between those who are comfortable with mobile technology and those who are not?
A simple random survey, conducted among shoppers at a traditional food supermarket, used an instrument in which the following two questions are of interest for this study.
Question 1: Are you comfortable with mobile technology?
0. No 1. Yes
Question 2: Would you consider shopping at AMAZON Fresh?
No 1. Yes
The dataset for this survey is collated in the SPSS and Jamovi files “Amazon”.
For this case study, we are required to produce the following tasks
Produce a frequency table for the dependent variable “Take up” and report your findings.
[Max: 50 words]
Conduct an appropriate hypothesis test fully to inform on the RQ1 above. [Max: 50 words]
Conduct an appropriate hypothesis test fully to inform on the RQ2 above. [Max: 50 words]
General question: Explain clearly and in your own words the reason for conducting a hypothesis test instead of simply comparing sample statistics of RQ2 above. [Max: 100 words]
The output for the two tests above is included in the appendix at the end of this brief. You may decide to produce your own output by using the data available to you. You should insert the appropriate output to evidence your reports.
The reports should follow the classic research style adopted during the online classes. For full marks, you should clearly state the null and alternative hypotheses for each test.
Conducting a hypothesis test is necessary in this case because it provides a statistical framework for evaluating the significance of the research questions and determining whether the observed differences between groups are due to chance or a genuine effect. Simply comparing sample statistics, such as the proportions of people who consider shopping at Amazon Fresh, does not provide a reliable indication of whether the differences are statistically significant or not. By using a hypothesis test, the researchers can set up null and alternative hypotheses, calculate the appropriate test statistic and p-value, and make a statistically sound conclusion about the significance of the observed differences. This helps to ensure that the results are reliable and can be used to draw meaningful conclusions about the research questions.
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