Chat with us, powered by LiveChat Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedb - EssayAbode

Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedb

 Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will perform an article critique on t tests. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another.

To prepare for this Discussion:

  • Review the Learning Resources and the media programs related to t tests.
  • Search for and select a quantitative article specific to your discipline and related to t tests. (Please use a quantitative article related to crime or the criminal justice system if you can) Help with this task may be found in the Course guide and assignment help linked in this week’s Learning Resources. Also, you can use as a guide the Research Design Alignment Table located in this week’s Learning Resources

By Day 3

Write a 3- to 5-paragraph critique of the article. In your critique, include responses to the following:

  • Which is the research design used by the authors?
  • Why did the authors use this t test?
  • Do you think it’s the most appropriate choice? Why or why not?
  • Did the authors display the data?
  • Do the results stand alone? Why or why not?
  • Did the authors report effect size? If yes, is this meaningful?  

Resources:

 

Discrete Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 62-67). Thousand Oaks, CA: SAGE Publications, Inc.

Fox, J. (1991). Quantitative Applications in the Social Sciences: Regression diagnostics Thousand Oaks, CA: SAGE Publications Ltd doi: 10.4135/9781412985604

Non-Normally Distributed Errors. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 41-49). Thousand Oaks, CA: SAGE Publications, Inc.

Nonconstant Error Variance. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 49-54). Thousand Oaks, CA: SAGE Publications, Inc.

Nonlinearity. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 54-62). Thousand Oaks, CA: SAGE Publications, Inc.

Outlying and Influential Data. (1991). In J. Fox (Ed.), Regression Diagnostics. (pp. 22-41). Thousand Oaks, CA: SAGE Publications, Inc.

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