Research Methods Flashcards
What is Qualitative Research?
an approach for understanding the meaning individuals and groups ascribe to a human or social problem. Builds from particular data to general theories.
What is Quantitative Research?
An approach for testing objective theories by examining relationships among variables. Typically numbered data which can be analyzed using statistical procedures.
What is the case study method of qualitative research?
Case study method focuses on the study of a single case. Not typically used to compare one individual or group to another.
What is the comparative analysis methods of qualitative research?
The comparative analysis method analyzes data from different settings or groups at the same point in time or the same settings or groups over a period of time for differences.
What is the discourse analysis method of qualitative research?
The discourse analysis method is a study of the the way version of the world, society, events, and psyche are produced in the use of language and discourse. It is often concerned with the construction go dubjrv
What is e-research?
Harnessing of digital technology to undertake and promote social research.
What is ethnography?
A multi-method qualitative approach that studies people in their naturally occurring settings
What is grounded theory?
In grounded theory, data analysis and collection are conducted together. It develops the theory from the data collected, rather than applying theory to the data.
What is the narrative analysis method of qualitative research?
Narrative analysis is a form of discourse analysis that seeks to study the textual devices at work in the constructions of process or sequence within a text.
Nominal Data
Nominal data are classified into mutually exclusive groups or categories and lack intrinsic order. A zoning classification, social security number, and sex are examples of nominal data. The label of the categories does not matter and should not imply any order. So, even if one category might be labeled as 1 and the other as 2, those labels can be switched.
Ordinal Data
Ordinal data are ordered categories implying a ranking of the observations. Even though ordinal data may be given numerical values, such as 1, 2, 3, 4, the values themselves are meaningless, only the rank counts. So, even though one might be tempted to infer that 4 is twice 2, this is not correct. Examples of ordinal data are letter grades, suitability for development, and response scales on a survey (e.g., 1 through 5).
Interval Data
Interval data is data that has an ordered relationship where the difference between the scales has a meaningful interpretation. The typical example of interval data is temperature, where the difference between 40 and 30 degrees is the same as between 30 and 20 degrees, but 20 degrees is not twice as cold as 40 degrees.
Ratio Data
Ratio data is the gold standard of measurement, where both absolute and relative differences have a meaning. The classic example of ratio data is a distance measure, where the difference between 40 and 30 miles is the same as the difference between 30 and 20 miles, and in addition, 40 miles is twice as far as 20 miles.
Continuous Variables
Continuous variables can take an infinite number of values, both positive and negative, and with as fine a degree of precision as desired. Most measurements in the physical sciences yield continuous variables.
Discrete Variables
Discrete variables can only take on a finite number of distinct values. An example is the count of the number of events, such as the number of accidents per month. Such counts cannot be negative, and only take on integer values, such as 1, 28, or 211.
Dichotomous Variables
can only take on two values, typically coded as 0 and 1.
What is a population?
A population is the totality of some entity. For example, the total number of planners preparing for the 2018 AICP exam would be a population.
What is a sample?
A sample is a subset of the population. For example, 25 candidates selected at random out of the total number of planners preparing for the 2018 AICP exam.
What are descriptive statistics?
Descriptive Statistics describe the characteristics of the distribution of values in a population or in a sample. For example, a descriptive statistic such as the mean could be applied to the age distribution in the population of AICP exam takers, providing a summary measure of central tendency (e.g., “on average, AICP test takers in 2018 are 30 years old”). The context will make clear whether the statistic pertains to the population (all values known), or to a sample (only partial observations). The latter is the typical case encountered in practice.
What is inferential statistics?
Inferential Statistics use probability theory to determine characteristics of a population based on observations made on a sample from that population. We infer things about the population based on what is observed in the sample. For example, we could take a sample of 25 test takers and use their average age to say something about the mean age of all the test takers.
What is distribution?
Distribution is the overall shape of all observed data.
What is a histogram?
A histogram groups observations in bins represented as a bar chart.
What is a normal distribution?
The gold standard in many statistical analyses is the normal or Gaussian distribution, also referred to as the bell curve. This distribution is symmetric and has the additional property that the spread around the mean can be related to the proportion of observations. More specifically, 95% of the observations that follow a normal distribution are within two standard deviations from the mean (see below, for further discussion). The normal distribution is often used as the reference distribution for statistical inference (see below).
What is a symmetrical distribution?
Symmetric distribution is one where an equal number of observations are below and above the mean (e.g., this is the case for the normal distribution).
What is central tendency?
Central tendency is a typical or representative value for the distribution of observed values. There are several ways to measure central tendency, including mean, median, and mode. The central tendency can be applied to the population as a whole, or to a sample from the population. In a descriptive sense, it can be applied to any collection of data. Typically, the terminology will make clear what the context is, i.e., a population mean or a sample average (mean).
What is a hypothesis test?
A central concept in statistical inference is that of a hypothesis test, i.e., a statement about a particular characteristic of a population (or several populations). We distinguish between the null hypothesis (H0), i.e., the point of departure or reference, and the alternative hypothesis (H1), or the research hypothesis one wants to find support for by rejecting the null hypothesis.
