The alternative and null hypotheses are constantly opposed to one another. The null hypothesis is that the average satisfaction rating is the same or lower if our alternative hypothesis is that it has increased.
A sample mean (M) is compared with a fictitious population mean (0), which offers an intriguing baseline for comparison, using the one-sample t-test. The null hypothesis is that the population's mean () is the same as the fictitious population mean: = 0 The other possibility is that the population's mean differs from the fictitious population mean: 0 Finding the likelihood of attaining the sample mean (or another extreme) if the null hypothesis were true can help us choose between these two hypotheses. But calculating a test statistic known as t is necessary before calculating this p value. (A test statistic is a statistic calculated solely to assist in determining the p value.)
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