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Jan 5, 2021 · This article presents and analyzes the design of quantitative research. It also discusses the proper use and the components of quantitative research methodology. It is used to quantify...
Writing Chapter 4 Chapter 4 is comprised of the following content: The results or findings on the data collected and analysed. Results of descriptive analyses Results of inferential analyses (Quantitative). Findings of text analyses (Qualitative).
After briefly reviewing quantitative research assumptions, this chapter is organized in three parts or sections. These parts can also be used as a checklist when working through the steps of your study.
Aug 24, 2023 · quantitative research are: Describing a problem statement by presenting the need for an explanation of a variable's relationship. Offering literature, a significant function by answering...
- What is research?
- Quantitative research
- Research process
- Research process (actually)
- Data Collection
- Models
- Hypotheses
- Statistical model
- STATA resources
- Excel to Stata
- STATA gold rules
- Exploring your data
Controlled collection and analysis of information in order to understand a phenomenon Originates with a question, a problem, a puzzling fact Requires both theory and data. Previous theory helps us form an understanding of the data we see (no blank slate). Data lets us tests our hypotheses.
Quantitative methods allow us to learn about the world by quantifying some variation(s) in it. Example: how do suicide rates vary across demographic categories (Durkheim)? In order to learn about the world, we use inference: General definition: “Using facts you know to learn about facts you don't know” (Gary King) Example: Using a sample to learn a...
(confirmatory or deductive model) Reviewing literature and identifying a question Sometimes question helps you identify relevant literature, sometimes literature helps you identify unsolved puzzle What makes the question interesting? Real world implications and theoretical contribution Form hypotheses Think about data you need to test them Think ab...
Back and forth between theory and data Each is going to highlight relevant features of the other That’s how a contribution takes shape But: you can’t use the same data to generate and test hypotheses. It would be tautological Importance of cross-validation Exploratory and confirmatory analysis
Think hard about the population you want to study Think hard about selection Interviewing method: face to face, phone Sampling: random? Purposive? Time of day Place Who agrees to respond?
A model is a strategic simplification Never true or false Only useful or not (does it capture the features you are interested in?) Examples: Obesity rate=f(absolute wealth, inequality) Food security=f(total hh income, distribution of control over income) Fertility=f(individual factors, structural constraints*cultural norms) Models Let’s think about...
Inequality and health H0: life expectancy only affected by level of GDP Ha: autonomous effect of economic inequality on life expectancy To test this, I need data on countries which have similar levels of GDP but different levels of inequality (eg, Sweden versus US)
Depends on the process you want to study: Continuous outcome (rate, income...): linear or log-linear regression Binary outcome (marriage, incarceration): logistic regression Count data (civil wars): Poisson regression (advanced) Timing of events: Survival analysis (advanced)
UCLA website (v. popular): http://www.ats.ucla.edu/stat/stata/ Princeton web page (the one I learnt from, good to start): http://data.princeton.edu/stata/ List of various books: http://www.stata.com/links/resources-for-learning-stata/ My personal bible: Cameron & Trivedi Microeconometrics using Stata, Stata Press. RTC team in CGIS building (awesome...
If your data are currently in Excel, you need to convert and import them: http://www.stata.com/support/faqs/data -management/converting-excel-files/ Also: “help insheet” in Stata
Always use a do-file Always comment on everything you do within the do-file You don’t want to be lost months from now Also in some cases you might want to show me or your adviser your do-file (Almost) never save the data at the end of a session That will replace your original data set Better to “save as”
Always useful: help command What do my variables mean? Command describe [name/list of var] Command codebook [name/list of var] Basic statistics Summarize [list of variables], detail Tabulate [one or two variables], options
May 17, 2021 · 1. Quantitative Data Analysis. Quantitative data analysis is a systematic process of both collecting and evaluating measurable. and verifiable data. It contains a statistical...
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the findings are divided into four groups: 1) methods to balance all contributions, 2) methods to overcome existing creative constraints, 3) methods to achieve full integration, and 4) Smart Clothing’s context. The results shown in this chapter have already been.