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Summary Research methods in social relations, chapter 1, 2, 4-9, 11 & 13 $3.75   Add to cart

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Summary Research methods in social relations, chapter 1, 2, 4-9, 11 & 13

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Summary of 24 pages for the course Methods & Statistics I at UCU

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  • June 30, 2014
  • June 30, 2014
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Research methods in social
relations, chapter 1, 2, 4-9, 11 & 13

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Research methods in social relations chapter 1, 2, 4, 5, 6, 7, 8, 9, 11 & 13

- Social science and physical sciences the same in logic of inquiry but different in degree to which
objects under observation play active role in the inquiry.
- Social science similar to casual observation in the quest to understand how people behave and relate
to each other, but different in systematic methods of inquiry.
-
The place of Values in Social Science Research
- Public reaction should be considered in publishing a research report, otherwise censorship and
suppression of free scientific inquiry (example: sex abuse (page 5)).
- Values affect the questions we ask and the way we react to what we find. But they should not be used
as a justification for preventing a given question from being asked.
- Stereotyping is viewed as acceptable and even helpful when the stereotypes are categories referring
to physical objects; when people are stereotyped, however, it is viewed as unacceptable. The
observations/”facts” of racial stereotyping are quite straightforward; it is the interpretation that
introduces social and political beliefs and values.

The results of social science appear to be more contestable (debatable) than the results of research in the
physical sciences (“in most people’s eyes). If someone is opposed, it is relatively easy to find apparent fault
with the research and conclude that the results were erroneous. Why?
1. The seemingly ordinary quality of most methods of observation (ask, listen & observe)
2. Often address issues about which there are serious, deeply felt, politically identifiable differences of
opinion  more difficult to persuade


Causal observation
The expectations, hunches, or hypotheses of casual observation are ultimately utilitarian (= the proper course
of action is the one that maximizes utility, usually defined as maximizing happiness and reducing suffering).
Because our ordinary hunches, hypotheses, and explanations ultimately are constructed to help us achieve our
own goals, and because we must inevitably realize that our hunches are not always correct, part of casual
observation involves trying to figure out when they are right and wrong. These tasks also characterize scientific
studies of social behavior. They want to construct theories of human social behavior and critically examine
those theories to improve their accuracy.

Naïve hypotheses = clichés about human social behavior that argue that one phenomenon/behavior (the
subject) is associated/causes with another phenomenon/behavior (the object)
Construct = abstract concept that we like to measure (e.g. love intelligence etc.).
Operational definition = set of procedures we use to measure/manipulate it (e.g. IQ test), specifies precisely
how to measure a variable so that anyone could repeat the steps and obtain the same measurements  limits
depth, but is objective
Definitional operationism = the assumption that the operational definition is the construct (fails to
acknowledge failibility of specific measures  multiple operational definitions are advocated
Hypotheses (in social science) = a falsifiable statement of the association between two or more constructs that
have to do with human social behavior.
Causal associations = some constructs are identified as causes and others as effects.
Theory = a set of interrelated hypotheses that is used to explain a phenomenon and make predictions about
associations among constructs relevant to the phenomenon. A syllogistic conclusion of a theory as a whole
ought to be held with no more confidence than the least confident premise.
Variable = any attribute that changes values across people or things being studied. Variables are used to
represent the constructs addressed by a theory

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A correlation coefficient is a statistical index of the strength of association between two variables. It is an
answer to the question: “To what extent do two variables measure the same thing?”

Abstract concepts are called constructs; concrete, fallible, measurable representations are called variables; and
operational definitions specify how to measure a variable so that we can assign someone a score.


Sources of Support for Naïve Hypotheses
At least five sources routinely used to develop hypotheses and theories rooted in casual observation:
1. Logical analysis
We often derive hypotheses and decide whether they are accurate by examining whether they are
logically consistent with other hypotheses that we hold. A final hypothesis is deduced/logically
inferred from the combination of two earlier ones. However, our “intuition” and logical process are
often incorrect.
2. Authority
We are likely to turn to various authorities/experts to determine what hypotheses make sense in our
casual observation of social behavior.
3. Consensus
We might appeal to the wisdom of our peers seeking consensus regarding our hypotheses. This is
subject to the same kinds of biases and distortions as is consultation with authorities.
4. Observation
We routinely compare our naïve hypotheses to the behavior of ourselves and others through
observation. This has four major problems.
1. The constructs mentioned in a hypothesis can mean different things to different people.
2. Causal direction can be very hard to establish.
3. We might make our observations on a very select group of people, that are not representative.
4. We probably are biased in deciding which observations are relevant.
5. Past experience
We most frequently reflect on/remembering past experiences. We think back to instances/events that
confirm the hypothesis, and we attempt to make modifications to take into account disconfirming
instances. Memory is inherently reconstructive. We store and organize events selectively.


Differences scientists/causal observers
1. Scientists are alert for biased conclusions & operate as if their hypotheses might be in error. The
scientist systematically studies how to avoid biases.
2. Scientists rely mainly on observation to evaluate a hypothesis critically. Empirical research is
observation that is systematic in attempting to avoid biases. They ultimately put confidence in a
hypothesis if it has been able to withstand empirical attempts to falsify it. Scientists who rely on
empirical research are necessarily concerned with how to measure theoretical constructs.
3. Social scientists assume that all constructs of interest can indeed be measured or observed. This is the
assumption of operationism. However, they do assume that all constructs are measured with error.
We say that the results are “consistent with” or “support” a hypothesis but not that the hypothesis has been
accepted. A hypothesis gains gradual acceptance if it is repeatedly supported, survives numerous attempts to
falsify it and seems to account for observations conducted by different scientists in different settings. Science
requires replication.

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