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Pages:
9 pages/≈2475 words
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Level:
APA
Subject:
Mathematics & Economics
Type:
Statistics Project
Language:
English (U.S.)
Document:
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Date:
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# STA437. Predicting the Happiness Score of a Country Using the Explanatory Variables. (Statistics Project Sample)

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please write the whole file in r markdown and knit out as a pdf
https://github(dot)com/michealhackathon/STA437-Final-Project
my friend gave me his work for reference
you can check it on GitHub
but mine cannot be similar to his
otherwise will be considered plagiarism
and for the summary
Abstract: 1. Research Topic, 2. Data description, 3. statistical method used, (transformation, regression, PCA, etc), 4. Conclusion and Result
My last four digit of student number is 8874
Abstract: 1. Research Topic, 2. Data description, 3. statistical method used, (transformation, regression, PCA, etc), 4. Conclusion and Result

source..
Content:

Predicting the Happiness Score of a Country Using the Explanatory Variables
Student's Name
Institutional Affiliation
Predicting the Happiness Score of a Country Using the Explanatory Variables
Abstract
The research paper uses the explanatory variables to predict the happiness score of a country. Moreover, it was the purpose of the research to assess the understanding of happiness from different subjects. Using the data analyzed in the study, the research will show that by using the explanatory variables from the data under consideration, it is possible to obtain accurate predictions of the happiness scores from the different nations. The methodology applied in this paper includes correlational, trying to investigate how the other nine variables correlate with the happiness scores of the different countries. The source of the data was the World Happiness Report 2017. The sample statistics used will be obtained randomly and will be of size n=100 from the original data set, which will be normally distributed following the gauss distribution. The main variables used in the data are as follows: Ladder (happiness score), LogGDP (the logarithm of country's' GDP 2017), Social (national average of the binary responses), HLE (healthy life expectancy), Freedom (national average of what you do), Generosity (donation regression residual of national averages), Corruption (national average on corruption), Positive (average of positive effects), Negative (average of negative effects), and Gini (Gini of household income).

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