Statistical Methods Of Psychology Journals : Guidelines And Explanations

Statistics provides us with very useful tools and techniques that aide us in dealing with real world scenarios. I have been able to learn several useful concepts by studying statistics that can aide me in making rational and informed decisions that are supported by the analysis results. Statistics as a discipline is the application and development of various processes put in place to gather, interpret, and analyse the information. The quantification of biological, social, and scientific phenomenons, design and analysis of experiments and surveys, and application of

Bersstein, D.A., Roy, E.J., Srull, T.K. and Wickens, C.D. (1991). Psychology. 2nd Edition. Boston: Houston Mifflin Company.

For the Final Paper, you will identify three to five research studies from peer-reviewed sources that were published within the last ten years, which investigate a particular social science problem or topic. The Final Paper will focus on critiquing the varying statistical approaches used in each of these studies.

Dunbar, G. (2005). Evaluating Research Methods in Psychology. New Jersey: John Wiley & Sons Inc.

The LV team is eager to learn what statistical significance is and why it’s an important construct in the study and use of inferential statistics.

Part II introduces you to a debate in the field of education between those who support Null Hypothesis Significance Testing (NHST) and those who argue that NHST is poorly suited to most of the questions educators are interested in. Jackson (2012) and Trochim and Donnelly (2006) pretty much follow this model. Northcentral follows it. But, as the authors of the readings for Part II argue, using statistical analyses based on this model may yield very misleading results. You may or may not propose a study that uses alternative models of data analysis and presentation of findings (e.g., confidence intervals and effect sizes) or supplements NHST with another model. In any case, by learning about alternatives to NHST, you will better understand it and the culture of the field of education.

American Psychological Association. Publication manual of the American Psychological Association (2015). Washington, DC: American Psychological Association

Statistics, facts, data, and comparisons are absorbing and challenging to present in a way that is anything other than, well, boring. For purposes of an informational presentation, the statistics are unavoidable. However, in this

Pollastek et al (2012) fail to give those reading the article the salient information that led the experimenters to make their conclusions. The information missing includes the sample population, and how many participants were assigned to the various groups being tested. The failure to provide this information brings into question whether the conclusions drawn are from smaller sample sizes or varied group sizes. Leaving out these details in conjunction with a lack of any analyzable data causes the audience to accept the conclusions of the study without any data to back it

Source: G. C. Britz, D. W. Emerling, L. B. Hare, R. W. Hoerl, & J. E. Shade. "How to Teach Others to Apply Statistical Thinking." Quality Progress (June 1997): 67--80.

In his 2013 book, Naked Statistics, Charles Wheelan explains a field that is commonly seen, commonly applied, and commonly misinterpreted: statistics. Though statistical data is ubiquitous in daily life, valid statistical conclusions are not. Wheelan reveals that when data analysis is flawed or incomplete, faulty conclusions abound. Wheelan’s work uncovers statistics’ unscrupulous potential, but also makes a key distinction between deliberate misuse and careless misreading. However, his analysis is less successful in distinguishing common sense from poor judgement, a gap that enables the very statistical issues he describes to perpetuate themselves.

Cohen’s paper The Earth is Round (p>0.05) is a critique of null-hypothesis significance testing (NHST). In his article, Cohen presents his arguments about what is wrong with NHST and suggests ways in which researchers can improve their research, as well as the way they report their research. Cohen’s main point is that researchers who use NHST often misinterpret the meaning of p-values and what can be concluded from them (Cohen, 1994). Cohen also shows that the NHST is close to worthless. NHST is a way to show how unlikely a result would be if the null hypothesis were true. A Type I error is where the researcher incorrectly rejects a true null hypothesis and a Type II error is where the researcher incorrectly accepts the false null

After a compelling read of “How to lie with statistics” by Darrell Huff, I am pleased to say that I learned a great amount of quality information. Not only was I shocked about the witty tone but also, I felt as if this book changed the way I would view statistics for the rest of my life. Even though this book was written in the 1950’s, I would say that the writing is time-less and that it still gives you great knowledge of how the world statistical works. Huff explains all of the tricky ways that statistics can cause a person to believe in something that possibility isn’t true. I’ve learned to be careful and not overlook the things that could be a statisticulation, as the author cleverly calls it, or a manipulated statistic. Most people would

In Charles Wheelan’s Naked Statistics: Stripping the Dread from the Data, Wheelan introduces many concepts fundamental to everyday life that escape the attention of even the most attentive human beings. Within these texts, Wheelan expresses that statistics, and therefore data, is an integral part of our lives, though it is often grossly misunderstood. With detailed descriptions of introductory statistical analysis, the author provides insights to the many misinterpretations and misrepresentations present in the statistical world today, often citing instances relatable to all people. Ads, commercials, campaigns, and any other mode of propaganda will contain data to support the cause of promotion, and for this reason—although not this reason alone—statistics has become intricate in our lives. The two most interesting points Wheelan makes refer to the intentional warping of data or computations to manipulate intended audiences; specifically, it is interesting to consider the moral obligation behind decision making versus the societal pressure added by the increasing use of statistics to rank or qualify oneself not to the world, but also to measure one’s self. Secondly, it fascinating to consider that statistical evidence that is seemingly unrelated to human life can explain phenomena intrinsic to human behavior and physiology previously misunderstood or unconsidered.

The Joy of Stats Nishant Sinha Kennesaw Mountain High School  The Joy of Stats One trend I observed in The Joy of Stats is that smokers are more likely to develop lung cancer than people who do not smoke. The scientist credited with this discovery is Richard Doll; he conducted a study on the relationship between the amount of tobacco one uses and lung cancer involving 40,000 doctors. After plotting his data, Doll’s graphs showed a strong and positive correlation between the amount someone smokes and their risk of developing lung cancer (Hillman, director, 2010). For a clear example of when statistics have been useful, we can refer back to Richard Doll’s research.