?/C/Users/tahma/Downloads/Chapter%2089620questions.pdf 9. What is an analysis pl
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?/C/Users/tahma/Downloads/Chapter%2089620questions.pdf 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 statist tical technique called "meta-analysis" help clarify research results? 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? 15. What is a correlation matrix? How can such a matris help researchers develop questions or theories about behavior? 16 Why should researchers graph or plot their data? 17. Why is statisties an important tool for pychology, rescarch methods, and becoming a practical researcher?Explanation / Answer
Note: This response is in UK English, please paste the response to MS Word and you should be able to spot discrepancies easily. You may elaborate the answer based on personal views or your classwork if necessary.
(Answer) (9) An analysis plan is essential because it informs the reader about what research is conducted to help prove each of the hypotheses. This might include steps like data cleaning, data plan, transformations, assumptions and analytical strategies.
(10) MAGIC:
Magnitude – How big is the issue?
Articulation – The specifics of the issue.
Generality – How is it generally applicable?
Interestingness – Does it have the potential to turn an empirical analysis to influence the thoughts people have about the subject?
Credibility – Are the claims credible?
The purpose of MAGIC in research is to make interesting claims about the given hypothesis through credible data.
(11) Chartjunk is all of the visual information like graphs or charts that are extraneous details. It is a problem for data display because it might distract one from focusing on the information that is essential to the study.
(12) Secondary analyses of results or any existing data is a cost-effective way of extracting as much as possible from existing data, in order to explore new facets or perspectives of the subject in a new research.
(13) “Meta-analysis” is the data about the analytical data. A good example of this would be like the key of the map that tells us that “blue” denotes water; “green” denotes land and other information that helps us read the map.
Meta-analysis is, therefore, data that helps one read the actual data.
(14) Spearman’s Correlation – Describes the strength and direction of the variables in the correlation.
It is a non-parametric version of correlation.
Pearson’s Correlation – Describes the measure of strength between the linear relationships between variables.
It is a positive correlation that is referred to as correlation coefficient.
(15) A correlation matrix measures the linear dependence between variables; hence, the Pearson method is the default method for a matrix.
The purpose of the correlation Matrix is to form a data frame of the required variable in order to succinctly display the relationship between them within a single frame. The correlation matrix highlights the correlation coefficient between the variables listed in the matrix.
(16) Data is used for the purpose of interpretation. In other words, the data a researcher collects is then analysed and deciphered in order to come to a calculated conclusion. In order to do this, the data must be organised and accurately presented. This is why a researcher would generally make graphs or plots of their data, as it concisely presents information in the most accurate manner possible.
(17) In the field of research, the data to be found is extensive and the calculations and analysis are vast and strenuous. Statistics are a way to interpret the data and turn it into usable information for the purpose of proving or disproving a hypothesis. Statistics involves the stages of collecting, analysis and making an inference for the data.
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