Description
Write up the analysis in a 1500 words report using the following report structure, all the tables and charts required are in the attached doc. The dataset is based on a selection of World Bank development indicators in 2020. (continuous level measures) Countries rather than individuals make up the cases in the dataset. Analyse the relationship between the dependent variable (Total Fertility Fertility rate) and two explanatory variables (Education attainment, at least completed upper secondary, population 25+, female (%) and GNI per capita). Tables and figures included in the report should be numbered and given clear titles, and should always be referred to in the text.
Introduction
-Introduce the research question/research objective (and any hypotheses) that will be investigating with the secondary analysis, with some reference to relevant literature (One hypotheses for each explanatory variable)
-Introduce and briefly give key details about the dataset will be using (the 2020 World Bank Development indicators).
-Explain the reasoning for the choice of explanatory variables and how they might be expected to influence the chosen dependent variable. In discussing choice of explanatory variables give clear reasoning for the choice, with some reference to literature.
– Briefly report the histograms and summary statistics for each of the variables
The Analysis
– Present the scatterplots, correlation analysis and regression (including the relevant SPSS outputs) with a clear reporting and interpretation of what they show. Don’t forget p value to see if statistically significant
Conclusion
-Conclude with a brief summary of your main findings and include short reflections on one perceived limitation of the analysis
Unformatted Attachment Preview
Dependent variables: Total Fertility Fertility rate, total (births per woman)
Explanatory variables: Ed_uppersec_female Educational attainment, at least
completed upper secondary, population 25+, female (%)
-The percentage of population ages 25 and over that attained or completed upper
secondary education.
Explanatory variables: GNI_percapita GNI per capita (constant 2015 US$)
– GNI per capita (formerly GNP per capita) is the gross national income, converted to
U.S. dollars using the World Bank Atlas method, divided by the midyear population.
GNI is the sum of value added by all resident producers plus any product taxes (less
subsidies) not included in the valuation of output plus net receipts of primary
income (compensation of employees and property income) from abroad. GNI,
calculated in national currency, is usually converted to U.S. dollars at official
exchange rates for comparisons across economies, although an alternative rate is
used when the official exchange rate is judged to diverge by an exceptionally large
margin from the rate actually applied in international transactions. To smooth
fluctuations in prices and exchange rates, a special Atlas method of conversion is
used by the World Bank. This applies a conversion factor that averages the exchange
rate for a given year and the two preceding years, adjusted for differences in rates of
inflation between the country, and through 2000, the G-5 countries (France,
Germany, Japan, the United Kingdom, and the United States). From 2001, these
countries include the Euro area, Japan, the United Kingdom, and the United States.
Scatterplots show the relationship between dependent variable and each of the
explanatory variables
Correlation analysis show the relationship between dependent variable and each
of the two explanatory variables
Pearson correlation
Spearmans correlation
The simple linear regression that model the relationship between dependent
variable and one of the explanatory variables which showed the strongest linear
correlation with the dependent variable
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