- "Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data."
A structured approach to analyzing numerical data using statistical techniques such as measures of central tendency, correlation, and regression analysis.
Basic statistical concepts: Basic statistical concepts in anthropology and quantitative data analysis refer to fundamental principles and techniques used to organize, summarize, analyze, and interpret numerical data to gain insights into human behavior and social phenomena.
Data collection techniques: Data collection techniques in Anthropology and Quantitative Data Analysis involve the systematic gathering and recording of information through methods such as surveys, interviews, participant observation, and archival research.
Data cleaning and preparation: Data cleaning and preparation in Anthropology and Quantitative Data Analysis involves ensuring accuracy, consistency, and completeness of the collected data by identifying and rectifying errors, inconsistencies, and missing values prior to analysis.
Descriptive statistics: Descriptive statistics in anthropology and quantitative data analysis involves summarizing and presenting numerical information about a population or sample, such as measures of central tendency, variability, and distribution.
Inferential statistics: Inferential statistics in Anthropology and Quantitative Data Analysis involve drawing conclusions and making predictions about a population based on a sample.
Non-parametric tests: Non-parametric tests are statistical methods used for analyzing quantitative data in anthropology without making assumptions about the underlying distribution of the data.
Correlation and regression analysis: Correlation and regression analysis explores the statistical relationship between variables, examining the strength and direction of associations, and predicting one variable based on another.
Multiple regression analysis: Multiple regression analysis is a statistical method used in anthropology to determine the relationship between multiple independent variables and a single dependent variable, allowing for the prediction and explanation of complex social phenomena.
Sampling techniques: Sampling techniques in anthropology and quantitative data analysis refer to methods used to select a representative subset of individuals or groups from a larger population for research purposes.
Probability theory: Probability theory is a mathematical framework that allows anthropologists to quantify uncertainty and predict the likelihood of events occurring in their quantitative data analysis.
Statistical software: Statistical software refers to computer programs designed to analyze and interpret quantitative data in anthropology, facilitating statistical analysis and hypothesis testing.
Data visualization techniques: Data visualization techniques in Anthropology and Quantitative Data Analysis involve displaying and interpreting data through various visual forms, such as charts, graphs, and maps, to communicate patterns, relationships, and trends.
Experimental design: Experimental design in anthropology and quantitative data analysis refers to the systematic planning, implementation, and control of experiments to investigate causal relationships and understand social and cultural phenomena.
Survey research: Survey research in Anthropology and Quantitative Data Analysis involves collecting systematic and standardized information from a sample population through structured questionnaires to data analysis and draw insights for understanding social phenomena.
Statistical assumptions and interpretation: Statistical assumptions and interpretation in anthropology and quantitative data analysis involve making assumptions about the population and interpreting results based on statistical tests.
Reliability and validity of data: Reliability and validity of data in Anthropology and Quantitative Data Analysis refers to the consistency and accuracy of the measurements and conclusions drawn from the data collected.
Ethical considerations in quantitative research: Ethical considerations in quantitative research involve addressing potential ethical issues related to data collection, privacy, informed consent, and ensuring the well-being of participants.
Descriptive statistics: The numerical data is analyzed to give a summary of the characteristics of a population or a sample. This is often used to find the mean, standard deviation, and range of a data set.
Inferential statistics: The sample data is used to draw conclusions about the characteristics of the population from which it was drawn. This is often used to test research hypotheses.
Correlation analysis: This method examines the relationship between two or more variables, looking for patterns of association.
Multiple regression: This is a statistical method for analyzing the relationship between two or more independent variables and a dependent variable.
Factor analysis: This method is used to find underlying factors that are influencing a set of variables. It is often used in survey research.
Cluster analysis: This analyzes the data to identify groups of individuals or businesses that have similar characteristics.
Discriminant analysis: This method is used to distinguish between groups of individuals or businesses based on a set of variables.
Network analysis: This method examines the relationships between individuals or businesses in a network, looking for patterns of connection.
Time-series analysis: This method examines changes in data over time, looking for trends and patterns. It is often used to forecast future trends.
Structural Equation Modeling: This is a statistical method that analyzes complex relationships among multiple variables, often used in situations where causative relationships between variables cannot be detected through conventional techniques.
- "Quantitative research is formed from a deductive approach where emphasis is placed on the testing of theory."
- "Quantitative research is shaped by empiricist and positivist philosophies."
- "Associated with the natural, applied, formal, and social sciences, this research strategy promotes the objective empirical investigation of observable phenomena to test and understand relationships."
- "There are several situations where quantitative research may not be the most appropriate or effective method to use."
- "When exploring in-depth or complex topics." - "When studying subjective experiences and personal opinions." - "When conducting exploratory research." - "When studying sensitive or controversial topics."
- "The objective of quantitative research is to develop and employ mathematical models, theories, and hypotheses pertaining to phenomena."
- "The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships."
- "Quantitative data is any data that is in numerical form such as statistics, percentages, etc."
- "Qualitative research, on the other hand, inquires deeply into specific experiences, with the intention of describing and exploring meaning through text, narrative, or visual-based data, by developing themes exclusive to that set of participants."
- "Quantitative research is widely used in psychology, economics, demography, sociology, marketing, community health, health & human development, gender studies, and political science."
- "Quantitative research is less frequently used in anthropology and history."
- "Research in mathematical sciences, such as physics, is also 'quantitative' by definition."
- "Quantitative methods can be used to verify which of such hypotheses are true."
- "A comprehensive analysis of 1274 articles published in the top two American sociology journals between 1935 and 2005 found that roughly two-thirds of these articles used quantitative method."