An Introduction to Scientific Research Methods in Geography Chapter 2: Fundamental Research Concepts

Fundamental Scientific Concepts Idea Concepts Empirical Concepts

Idea Concepts Theory Central idea concept An idea or conjecture about a casual relationship in reality Answers question of “Why” by identifying causes Authors define it narrowly in order to recognize explanation as the goal for scientific research

Idea Concepts Hypothesis A conjecture about a pattern of observations of the world Refers to a testable idea “If theory A is true, then one hypothesizes that data pattern B will hold”

Idea Concepts Causality Causality is complex and is accepted by most scientists as an important concept The apparent fact that event A (cause) is a reason that event B (effect) occurred Basically, the occurrence of event B depends in some way on the occurrence of event A David Hume’s 3 principles They co-occur (covariation) The cause comes first (temporal precedence) Controlling the cause controls the effect

Idea Concepts Causality continued There are necessary and sufficient causes A necessary cause is required for the effect to occur, but it doesn’t have to occur every time A sufficient cause can cause the effect, but something else could cause it as well Ex: drought & wildfires

Idea Concepts Causality continued Mechanistic and functional causality Mechanistic causality is the idea that causes move forward “densely” in space and time (ex., light switch) Functional causality is the idea that places the cause after the effect by seeing the cause as functional or purposeful; cause is seen as a goal (ex., evolution)

Idea Concepts Model A simplified representation of a portion of reality expressed in conceptual, physical, graphical or computational form Ex: Huff model shows gravity model in economic geography showing store choice of consumers based on attractiveness

Idea Concepts Construct What we attempt to measure; a scientific concept; elementary component within a theory Ex: a table has length (construct) and we try to measure it, but it will always be an imperfect reflection of the construct Latent and Manifest variables Latent variables are what we try to measure; they are the constructs (ex., intelligence tests) Manifest variables are the measurements, the imperfect reflections

Empirical Concepts Case The thing or entity being studied such as a unit of analysis, entity, element, etc. We don’t study cases directly, we study attributes or properties of cases (ex., mountains & cities)

Empirical Concepts Variables The properties studied within a case that change over time and depending on the case; they take on multiple values across cases Constants stay the same measurement; the process of how we observe and determine values Dichotomous variable is the simplest variable possible, having two values

Empirical Concepts Measurement Assigning numbers to cases to reflect their values on a variable Data refers to the measured numbers

Empirical Concepts Measurement Level (Hierarchy): Nominal: assigning numbers to distinguish one case’s value on a variable from that of another case; classification Ordinal: assigning numbers to distinguish the relative order or rank of the value of one case on a variable from that of another case; ranking; doesn’t express how much more or less of a difference between rankings Interval: expresses the ranks of cases on a variable and also the quantitative lengths of intervals between the cases; it doesn’t express a value of nothing or a true zero Ratio: expresses lengths of intervals between cases on a variable and also the lengths of intervals relative to a true zero; comparisons can be made *Ratio and interval measurements taken together are known as metric

Empirical Concepts Discrete vs. Continuous Variables Discrete variables have a limited set of distinct possible values Continuous variables can take on an infinite number of values between any two values

Empirical Concepts Discrete vs. Continuous Variables cont. Zeno’s Paradoxes, pg. 25 Box 2.1 The distinction between discrete and continuous may seem straightforward, it is an intellectual enigma when pondered In relation to levels of measurement there is overlap: Nominal and ordinal variables = discrete Interval and ratio variables = discrete or continuous Discrete variables = any 4 levels Continuous variables = interval or ratio

Empirical Concepts Accuracy vs. Precision of Measurement Accuracy is the correctness of measurement at a given levels of precision; how close the measured value is to the true value of what is being measured Precision is the sharpness or resolution of a measurement; how small the units are with which a value is measured

Empirical Concepts Accuracy vs. Precision of Measurement

What is Scale? Scale is idea concept and empirical concept Scale is about size: relative or absolute Scale is relevant to space, time and theme Themes are the non-spatial and non-temporal characteristics of human and natural phenomena that geographers measure and map as variables

What is Scale? Phenomenon Scale The size of human or physical earth structures or processes actually exist (ex., lake & pond) Analysis Scale The size of the unit at which a problem is analyzed Cartographic Scale The depicted size of a feature on a map relative to actual size in real life

What is Scale? Hierarchy of scales means that smaller phenomena are nested within larger phenomena (ex., economies)

Generating Research Ideas Non-systematic Creativity / Intuition / Experience

Generating Research Ideas Systematic Intensive case study Paradoxical incident Analogical extension Practitioner’s rule of thumb Account for conflicting results Reduce complexity to simpler components Account for exceptions to general findings

Developing Research Ideas Find a research area Generate research ideas Your own ideas first Avoid groupthink / staleness Link with other knowledge Your own Experts / Literature Formulate your idea as specific hypotheses Design research to address your hypotheses