Consider the following:
A researcher is conducting work on social inequality and wants to know whether there are marked differences between socioeconomic status of Caucasians and Non-Caucasians. Since the researcher cannot measure the entire population, a sample is drawn and a hypothesis can be constructed and evaluated as to whether any noticeable differences in the sample also likely appear in the population.
As a scholar-practitioner, it will be important for you to develop your knowledge and skillset in hypothesis testing. As evident in the scenario provided, hypothesis testing establishes a process to determine the probability of observing similar scores noted in the sample under the null hypothesis.
For this week, you will examine hypothesis testing and determine the statistical significance and meaningfulness in the data. You also will explore the results of data to determine implications for social change.
Learning ObjectivesStudents will:
- Evaluate statements related to null hypothesis
- Evaluate p-values
- Evaluate type I and type II errors
- Evaluate for meaningfulness
- Evaluate statistical significance
- Evaluate sample size
- Analyze implications for social change