All posts tagged: Demographics

The Moderating Variable

Last Lesson in Data Analysis Tools… If you have not read my previous posts, I am currently enrolled in a Data Analysis Specialization with Wesleyan University through Coursera. With data from Gapminder, I am exploring a broad and basic question: does urbanization drive economic growth? For those of you interested in reading my literature review to gain a background on this project, please visit this page. This is the last lesson in the Data Analysis Tools course. After analyzing for correlations between variables, this assignment focuses on moderating variables. A moderating variable is one that influences the strength and direction of the association between the explanatory and response variables. Last time, I established that there were correlations between the amount of urbanization, as measured by percentage of total population in cities with over 1 million people, urban population growth, and GDP per capita. Additionally, I found that there was a correlation between total populations in cities and urban population growth. I suspect that one of these two variables might be a moderating variable. I first looked at total …

Correlations! Urbanization and Economic Development in Rich and Poor Countries

Continuing with Data Analysis Tools… If you have not read my previous posts, I am currently enrolled in a Data Analysis Specialization with Wesleyan University through Coursera. With data from Gapminder, I am exploring a broad and basic question: does urbanization drive economic growth? For those of you interested in reading my literature review to gain a background on this project, please visit this page. Finally! Quantitative to quantitative variable analysis! This is the lesson I have been waiting for. With my interest in urbanization and economic development, the data I pulled from Gapminder are all quantitative. As I previously mentioned, I do not like categorizing quantitative data because I believe it introduces too much subjectivity. Unless the data is qualitative to begin with, it makes little sense to categorize data. Compared to the other types of correlation tests, Pearson’s Correlation was relatively easy to perform in both Python and SAS. I looked at the relationships between urbanization rate, as measured by both urban population growth rate and percentage of population in large cities with over 1 …

Chi-Square Testing…*Warning: It’s Painful*

Continuing with Data Analysis Tools… If you have not read my previous posts, I am currently enrolled in a Data Analysis Specialization with Wesleyan University through Coursera. With data from Gapminder, I am exploring a broad and basic question: does urbanization drive economic growth? For those of you interested in reading my literature review to gain a background on this project, please visit this page. For this assignment, I had to run Chi-Square tests on my variables. As always, both my Python and SAS codes are posted. Since all my data are quantitative, I had to first categorize them. Since I found a relationship between the absolute measure of urbanization (population in cities with over 1 million people) and GDP Growth rate, I decided to categorize GDP growth rate. Additionally, I wanted to see if there is a relationship between urbanization with the absolute measure of GDP  (GDP per capita). To categorize GDP per capita, I used cut-offs of 5000, 10000, and 100000 to produce three distinctive ranks whereby a country is poor if its GDP per …

A Revelation…Through ANOVA

Now that I finished the first course in the Data Analysis and Interpretations Specialization, this is the start of the second called Data Analysis Tools.  If you have not read my previous posts, I am currently enrolled in a Data Analysis Specialization with Wesleyan University through Coursera. With data from Gapminder, I am exploring a broad and basic question: does urbanization drive economic growth? For those of you interested in reading my literature review to gain a background on this project, please visit this page. Since I have been presenting my SAS work in the previous course, I will be presenting my Python work for this course. I actually enjoy working with Python, it seems to have more flexibility and I am more used to its language, having some experience with R during graduate school. As always, I am also including the other set of code for reference, so please see my SAS code at the very bottom of the post. There will be two parts to this presentation. The first part will be a discussion of …

Data Visualization Assignment 1 – That Urbanization Thing

“When you are that curious about the world, scholarship never ends.” – October 18, 2015 As I mentioned in my last post, I started the Data Analysis and Interpretations Specialization with Coursera in order to gain more skills relevant to my pursuit of urban studies and interest in urban planning and development. Our assignment for the first week is to develop a research question based on the data sets provided by the course or another data set of our own choice. With my background and interest in cities, I looked through the code books for each data set looking for relevant data. I decided that the Gapminder data set had the information I needed to look into the effects of urbanization globally. Though the scale is on a national level, which can obscure many relationships, particularly the distinction between rural and urban areas and their respective economies, I look forward to comparing the general trends and effects of urbanization. The increasing rate of urbanization has been accompanied by a corresponding rise in number of urban …

Learning and Growing! Internship and Coursera Specialization!

Last week, I started my internship with WLM Financial – a real-estate brokerage. With my interest in urban planning and development and my background in the social sciences, it appears to be a good fit to work as their Marketing Intern. I was quickly integrated into the marketing team and I am happy to say that the owners have been very trusting and gave me a great opportunity to learn. They have taught me a great deal in the past week about mortgages and real-estate. They are always open to questions and really took me under their wings. I look forward to learning more about the real-estate industry and about business development. Though I am only an intern, my opinions were valued and contributed to the direction the company is taking. Using my skills with ArcGIS, I took the initiative located our target audiences. I integrated demographic data with geospatial data from the U.S. Census Bureau to reveal locations where our target audience might be located. I was quickly able to locate ten cities in …