Is it possible for a result to have practical significance but not statistical signficance? Explain. Why is it important to consider both statistical and practical significance? Discuss the practical significance of the results. A randomized trial that ran for 12 weeks. The two randomized groups include the control group and the intervention group. The control group was given the usual treatment of how to contact the national smoking cessation help line for youth smoking cessation. While the intervention group was given an automated text message that consists of health risks, tips on behavioral changes, and activities. The researchers measured the outcomes by following up after three months and sending a text message that included a hyperlink to a web questionnaire. The researcher did another follow-up with the students four weeks after completing smoking cessation. Collected data was input in R version 3.4.2 and measured using a P-value of 0.05 significance level. The outcome of the study involved 201 in the controlled and 212 students in the intervention group. After the 3 month follow-up, 39 controlled students reported having less than 5 cigarettes in the past 8 weeks, while 49 intervention students reported the same. The P-values for this follow-up were 0.46, which shows statistically no significant difference between the two groups. In the four-week follow-up of completing smoking cessation, 31 controlled students reported not smoking a single cigarette at the time of the 3 months follow-up, while 53 intervention students reported the same. The P-value for this second follow-up was 0.018, which showed a statistically significant difference between the two groups. Concluding that text-messaging based smoking cessation programs can help adolescents quit smoking.
Questions:
- Is it possible for a result to have practical significance but not statistical signficance? Explain.
- Why is it important to consider both statistical and practical significance?
- Discuss the practical significance of the results.
A randomized trial that ran for 12 weeks. The two randomized groups include the control group and the intervention group. The control group was given the usual treatment of how to contact the national smoking cessation help line for youth smoking cessation. While the intervention group was given an automated text message that consists of health risks, tips on behavioral changes, and activities.
The researchers measured the outcomes by following up after three months and sending a text message that included a hyperlink to a web questionnaire. The researcher did another follow-up with the students four weeks after completing smoking cessation. Collected data was input in R version 3.4.2 and measured using a P-value of 0.05 significance level.
The outcome of the study involved 201 in the controlled and 212 students in the intervention group. After the 3 month follow-up, 39 controlled students reported having less than 5 cigarettes in the past 8 weeks, while 49 intervention students reported the same. The P-values for this follow-up were 0.46, which shows statistically no significant difference between the two groups. In the four-week follow-up of completing smoking cessation, 31 controlled students reported not smoking a single cigarette at the time of the 3 months follow-up, while 53 intervention students reported the same. The P-value for this second follow-up was 0.018, which showed a statistically significant difference between the two groups. Concluding that text-messaging based smoking cessation programs can help adolescents quit smoking.
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