Multiple Regression Analysis Statistics Project Example | Topics and Well Written Essays - 750 words

Multiple Regression Analysis - Statistics Project Example Governments’ focus on improving labor force and imports are recommended for economic growth. Economic growth is an important factor to governments, whose responsibilities include availing resources for public utilities and ensuring good living standards that are dependent on economic well being. Governments also have the responsibility of ensuring good macroeconomic environment for economic competitiveness in the international scope. Gross domestic product is one of the indicators of economic growth and its value can be used to understand factors to economic growth and to inform macroeconomic policies in a country. This report analyses factors to economic growth with the aim of identifying significant factors. Human capital is one of the factors that have been associated with economic growth and according to Somashekar (N.d.), is directly proportional to growth. International trade and foreign direct investment inflow have also been associated with effects on a country’s economic growth. Foreign direct investments have diversified indirect and positive effects on economic growth. Imports and exports have also been associated with economic development and the factors have beet correlated with foreign direct investment flows (OECD, 2002). This paper investigate relationships between gross domestic product and employment rate, as an indicator of human capital, foreign direct investments, import, and export. The following hypothesis is tested. A survey design is used in the study with reliance on secondary data. The Central Intelligence Agency library is used as the source of data. Stratified random sampling is used to select countries, the research participants, and respective data identified. Four countries are selected from Europe, Africa, America, and Asia. Descriptive statistics and regression analysis are used to analyze the data. Each of the variables has high standard deviations and this suggest possible variations across other