Here is the data:
Korean war; 1950-1953: 30 billion
Vietnam war; 1965-1975: 111 billion
Persian Golf War; 1990-1991: 61 billion
Iraq; 2003-2010: 715 billion
Afghanistan; 2001-2010: 297 billion
STA2023 PROJECT OUTLINE
This is an outline to guide students in the preparation of their STA2023
Statistical Methods Course Project:
The project is a term paper oriented in week II and shows the integrative result of an individual research
by collecting, organizing, displaying and understanding data. The project provides a final report in
writing an essay about the characteristics of data in both, the descriptive and the inferential approaches
about the data collected and about the targeted population, using quantitative and qualitative fact via
the exploratory data analysis method.
Data Collection: collect meaningful raw data according to the principles explained in chapter 1 in two –
three quantitative variables and two –three qualitative variables. Size must be according to guidelines,
given and following further principles in chapter 7, about necessary sample size. Using data from the
office of the Census website, or the Department of Labor Statistics, or the Department of Health, the CIA
World Fact book websites and the corresponding organizations that poll the population of different
countries. If the project is developed in reference to the comparison of two populations with respect to
a specific variable, collect the corresponding evolution of the structure of the population in each group
(gender and ethnicity) and the average family income, for example to dispose the circumstances where
the comparison takes place.
Be able to document your data collection explaining the sample technique that you used proficiently,
identify sources of bias and get along with the literature that may have provided information for your
Data Organizing and Data Display: Produce the bar graphs and/or pie charts for the categorical
variables or attributes that may permit the characterization of the population under analysis.
Produce Chi-square tests to state inferential criteria for independence and /or goodness of fit for
qualitative variables, explain the rationale for selecting hypotheses and significance level, as well as the
conclusion and interpretation, intended to assist in describing the targeted population.
Explain the normality of data using technology in MINITAB 17. Then for the quantitative variables use
stem and leaf displays, box plots and histograms, to facilitate the explanation of the characteristics of
each variable according examples conducted in class.
Produce customs side by side stem and leaf displays; Frequency distribution tables; Side by Side
Relative Frequency Polygons; Side by Side Box plots; Bar Graphs for the variables involved in the study(
Use same intervals in all the displays for each of the quantitative variables.
Produce Normality Tests for the quantitative variables, explain the rationale for selecting hypotheses
and significance level, as well as the conclusion and interpretation of the test, the full Descriptive
Statistics( use MINITAB), Control Chart for each variable, Time Series, to assess presence of outliers and
evolution in time. Detail the incidents during data collection that are observed in the displays and
produce substantive interpretation of trends.
Data Understanding: Produce Confidence Intervals, for the Mean, the Proportion (as appropriate) and
the Variance. Develop Hypotheses tests to test one population Parameter and the difference of Means
Develop the Correlation- Regression analysis for the association predictor response of two variables in
the study or conduct ANOVA.
Written Essay: Must contain explanatory statements about the five characteristics of data involving the
triangulation of supportive arguments.
The Report is an academic term paper that is structured in Title; Author; Abstract; Introduction
(following the previous explanations in above paragraphs); methods, results, conclusions and
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