Main objective: To demonstrate ability to maintain a linked set of statistical investigations into what is really going on in the data, and to find/discover/invent fresh questions to be asked of it.
The attached dataset (in .sav and .xlsx formats) contains data on a selection of variables of potential relevance to aspects of human freedom for 162 countries. The Human Freedom Index presents a broad measure of human freedom, understood as the absence of coercive constraint. It uses 79 distinct indicators of personal and economic freedom in the following areas:
Rule of Law; Security and Safety; Movement; Religion; Association, Assembly, and Civil Society; Expression and Information; Identity and Relationships; Size of Government;
Legal System and Property Rights; Access to Sound Money; Freedom to Trade Internationally; Regulation of Credit, Labour, and Business. The methodology and used variables are explained at the end of the above report (page 380 onwards).
It is an open dataset, © Original authors: Ian Vásquez and Tanja Porčnik, The Human Freedom Index 2018: A Global Measurement of Personal, Civil, and Economic Freedom (Washington: Cato Institute, Fraser Institute, and the Friedrich Naumann Foundation for Freedom, 2018).
You are invited to produce a report targeting academic and managerial audience, setting out the analyses of the attached dataset in no more than 1350 words*.
You do not focus on the while dataset, but you create a subset of the entire dataset which is the Group one of the G20 countries; USA, Canada, Australia, and Saudi Arabi.
Please note: You must only use suitable analyses of the following:
Descriptive statistics. Measures of location (mean, median, mode, trimmed mean, geometric mean). Dispersion (standard deviation, range, interquartile range). Skewness, kurtosis and excess kurtosis. Their properties, advantages, disadvantages and typical uses.
Levels of measurement. Stevens’ classification of ratio, interval, ordinal and categorical. Permissible operations, permissible tests.
Simple graphical devices: Histograms, stem & leaf diagrams, scatterplots, boxplots, QQ plots. Detecting and defining outliers, their adverse influence on analysis.
Probability. Laws of probability, odds, log odds, conditional probability, subjective probability, Bayes.
Normal distribution. Normalization. Data transformations to remove skew. Central limit theorem; designing sample size.
Hypothesis testing. Type I & II errors; 1 & 2-tailed tests; statistical significance; Z-tests, t-tests
Non-parametric tests for repeated & independent measures. Chi-squared tests. Phi. Goodness of fit.
Other distributions & their uses: Discrete and continuous; Uniform, Binomial, Poisson
Matching problems to hypotheses and tests.
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