• Describe how the idea of causal inference can apply to your interactions in everyday life. Also, make an argument for how the idea of causal inference could be applied the way we approach ministry.
• Begin by explaining what the p value reveals about the probability that a study is replicable. Next. describe the major alternatives to the use of α < .5 (NHST). What is p-hacking? Describe common researcher practices can be described as p-hacking and how research results might be implicated as a result of p-hacking. Moreover, how are future research studies which are attempting to replicate these studies implicated as a result of p-hacking?
Full Answer Section
Causal Inference in Ministry
The concept of causal inference is highly applicable to how we approach ministry. Rather than simply observing outcomes (e.g., increased church attendance or higher tithes), we can use causal inference to understand what interventions are actually effective. For example, if a ministry launches a new mentorship program and sees an increase in youth engagement, the leaders should use causal inference to determine if the program
caused the increase, or if other factors were at play (e.g., a new youth pastor, a popular guest speaker, or a broader trend in the community).
To apply this systematically, ministry leaders could:
- Formulate a hypothesis: "Our new program will increase community service participation."
- Establish a baseline: Measure current community service participation before the program starts.
- Implement the program: Roll out the new initiative.
- Collect data: Measure participation after the program has been implemented.
- Analyze and infer causality: Compare the new data to the baseline, and use critical thinking to rule out other possible causes. For example, did participation increase because of the program, or was there a major disaster in the area that prompted people to volunteer? By asking these questions, leaders can more accurately assess the impact of their ministry efforts and make better decisions about where to invest their time and resources.
Sample Answer
Causal Inference in Everyday Life
Causal inference is the process of determining the cause-and-effect relationship between two events or variables. In everyday life, we apply causal inference constantly, often without realizing it. For instance, if you get a flat tire after driving over a pothole, you infer that the pothole
caused the flat tire. You're not just observing a correlation (the pothole and the flat tire happened around the same time); you're making a judgment that one event directly led to the other. Similarly, if a plant withers after you forget to water it, you infer that the lack of water caused its demise. This is an informal causal inference based on your understanding of how plants work.
In our daily interactions, we also use causal inference to understand people's behavior. If a friend is quiet and withdrawn, you might infer that a recent difficult event in their life is the cause.
You are looking beyond mere observation to understand the underlying reason for their change in behavior. This process helps us navigate social situations and make informed decisions, such as offering support to our friend.