In hypothesis testing within sociology, how does an alternative hypothesis influence the interpretation of qualitative data when considering the sample size?

In hypothesis testing, the alternative hypothesis represents what researchers expect to find if their main idea is true. When analyzing qualitative data, this hypothesis shapes how we interpret the information we gather. For example, if a researcher believes that social media affects communication skills, the alternative hypothesis would suggest that there is a noticeable difference in communication abilities among heavy social media users compared to those who don’t use it much. The sample size matters because a larger sample can provide more reliable data, helping to confirm or reject the alternative hypothesis. This means that with a well-chosen sample size, researchers can better understand the impact of social media on communication and make stronger conclusions about their findings.