Why should statistical analysis be viewed as a tool for researchers? What are de

Question

Why should statistical analysis be viewed as a tool for researchers? What are descriptive and inferential statistics? How do they differ from one another? How are they used in psychological research? What are the four types of scales of measurement used in psychological research? Describe each one in the context of an example. 1. 2. 3. 4. Why are measures of central tendency especially the arithmetic mean so important to o psychological research and theory? 5. What is statistical significance? What is the proper use of this concept? Why is the concept often misunderstood? 6. What are the two types of statistical errors that can occur in hypothesis testing? Describe each one and provide an example. 7. How do parametric and non-parametric statistics differ from one another? 8. Why should researchers plan their data analyses in advance of data collection? 9. What is an analysis plan? Why is it an important research tool? 10. Explain the acronym MAGIC and its importance to evaluating research results. 11. What is "chartjunk," and why is it a problem for data display? 12. What are secondary analyses of results? 13. How does the statistical technique called "meta-analysis" help clarify research results? 14. As a statistical test, how does the Spearman correlation differ from the Pearson correlation? That is, on what sorts of data should each be applied? What is a correlation matrix? How can such a matrix help researchers develop questions or theories about behavior? 15. 16. Why should researchers graph or plot their data? 17. Why is statistics an important tool for psychology, research methods, and becoming a practical

Explanation / Answer

Statistical analysis should be viewed as a tool for researchers as statistical analysis gives meaning to the data represented by numbers. Thus statistics is basically the systematic collection and analysis of numerical data, for investigating or discovering relationships among phenomena so as to explain, predict and control their occurrence.

Descriptive statistics deals with quantitative data and the methods for describing them.

Inferential (analytical) statistics draw inferences about populations by analyzing data gathered from samples.

Statistically, significance finds the is likelihood if is a relationship between two or more variables is caused by something other than random chance.

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