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Multiple leaner regression model on data set of hair eye colour

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Perhaps the most important part of a statistician’s job once the analysis is complete is to communicate the results to others. This is usually done with some type of report that is delivered to the client, manager, or administrator. Other situations that call for reports include term papers, final projects, thesis work, etc. This chapter is designed to pass along some tips about writing reports once the work is completed with R. F.1 What to Write It is possible to summarize this entire appendix with only one sentence: the statistician’s goal is to communicate with others. ...

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Perhaps the most important part of a statistician’s job once the analysis is complete is to communicate the results to others. This is usually done with some type of report that is delivered to the client, manager, or administrator. Other situations that call for reports include term papers, final projects, thesis work, etc. This chapter is designed to pass along some tips about writing reports once the work is completed with R. F.1 What to Write It is possible to summarize this entire appendix with only one sentence: the statistician’s goal is to communicate with others. Basic Outline for a Statistical Report 1. Executive Summary (a one page description of the study and conclusion) 2. Introduction (a) What is the question, and why is it important? (b) Is the study observational or experimental? (c) What are the hypotheses of interest to the researcher? (d) What are the types of analyses employed? (one sample t-test, paired-sample t-test, ANOVA, chi-square test, regression, . . . ) 3. Data Collection (a) Describe how the data were collected in detail. (b) Identify all variable types: quantitative, qualitative, ordered or nominal (with levels), discrete, continuous. (c) Discuss any limitations of the data collection procedure. Look carefully for any sources of bias. 4. Summary Information (a) Give numeric summaries of all variables of interest. i. Discrete: (relative) frequencies, contingency tables, odds ratios, etc. ii. Continuous: measures of center, spread, shape. (b) Give visual summaries of all variables of interest. i. Side-by-side boxplots, scatterplots, histograms, etc. (c) Discuss any unusual features of the data (outliers, clusters, granularity, etc.) (d) Report any missing data and identify any potential problems or bias. 5. Analysis (a) State any hypotheses employed, and check the assumptions. (b) Report test statistics, p-values, and confidence intervals. (c) Interpret the results in the context of the study. (d) Attach (labeled) tables and/or graphs and make reference to them in the report as needed. 6. Conclusion (a) Summarize the results of the study. What did you learn? (b) Discuss any limitations of the study or inferences. (c) Discuss avenues of future research suggested by the study. 1.Appendix a.R code b.Edited Log file

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