Final answer:
The question relates to conducting a hypothesis test to determine if the proportion of users on a social media platform has decreased, using a sample of user data and a 5% level of significance. The significance level is the threshold that defines the probability of rejecting the null hypothesis when it is true.
Step-by-step explanation:
The question concerns a social media platform's inquiry about a possible decrease in user proportion worldwide. The report stated that 57% of social media users were on their platform. However, a sample survey of 47 people indicated that only 22 of them still had an account. We are asked to determine whether this sample data presents evidence that the proportion has decreased, using a 5% level of significance.
To do this, a hypothesis test for the proportion is used. The null hypothesis (H0) would state that the proportion of users has not decreased (p ≥ 0.57), while the alternative hypothesis (H1) claims that the proportion has decreased (p < 0.57).
The level of significance mentioned in the question, 5%, is the probability of rejecting the null hypothesis when it is true - it is the threshold for determining whether the observed sample provides strong enough evidence against the null hypothesis.
Performing the hypothesis test would involve calculating the test statistic using the sample proportion and comparing it to a critical value from the standard normal distribution. If the test statistic falls in the critical region (usually for a one-tailed test like this, in the left tail of the distribution), then we reject the null hypothesis in favor of the alternative.