The work has not been graded but I like the output that was submitted to me. Is it possible for the same prof to do the next assignment I will be submitting? If possible, I will greatly appreciate it.
Write 6 pages with APA style on Theoretical Statistics Analysis. Chi-square tests are also performed to determine the relationship between adoption and actual use. Chi-square tests are used in situations where the data can be put in contingency tables or in cases where there is a need for a test of goodness of fit. In this case, the chi-square statistics are computed and compared with the various probabilities for significance.
According to Blanca, Julio & Jose (2009), to compare any differences that may exist between potential future users of e-commerce and by experienced e-commerce customers, random sampling of the participants is used. However, this goes against requirements of sampling that a sample needed to be unbiased. Although random sampling will ensure an unbiased sample, the whole population is not homogenous and is made up of people of different traits which should occasion stratified sampling. Stratified sampling should have been used as the whole population will be sub-divided into non-overlapping strata and then select a random sample from each stratum and combine to have an equally representative sample.
Of the 805 participants in this survey, 580 were potential e-customers while the remaining 225 were experienced e-customers. There is the need to use binomial tests to test for statistical significance in the sample difference. Normally, a binomial test will test whether potential e-customers and experienced e-customers are distributed at a proportion of 0.5.
Further, t-tests can be used to test the differences between the attitudes of potential e-customers and experience e-customers and to confirm the formulated hypothesis. But first, there is a need for normality tests to confirm whether the data is normally distributed so as to decide whether to use parametric or non-parametric independent samples t-test. T-tests would produce differences in samples.
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