Chapter 1 Flashcards

(90 cards)

1
Q

why learn statistics?

A

First, you are
constantly exposed to statistics every day of your life. Marketing surveys, voting polls, and
social research findings appear daily in the news media. By learning statistics, you will
become a sharper consumer of statistical material. Second, as a major in the social sciences,
you may be expected to read and interpret statistical information related to your occupation
or work.

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2
Q

what is stats

A

But
the word statistics also refers to a set of procedures used by social scientists to organize,
summarize, and communicate numerical information.

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3
Q

what kind of info can b the subject of stat analysis

A

info represented by numnbers ONLY

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4
Q

how to think of research process?

A

. We can think of the research process as a set of activities in which
social scientists engage so that they can answer questions, examine ideas, or test theories.

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5
Q

research process studies

A

. Asking the research question

  1. Formulating the hypotheses
  2. Collecting data
  3. Analyzing data
  4. Evaluating the hypotheses
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6
Q

. For example, the questions “Is racial equality good for society?” and “Is an
urban lifestyle better than a rural lifestyle?” cannot be answered empirically - why

A

because the
terms good and better are concerned with values, beliefs, or subjective preference and,
therefore, cannot be independently verified

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7
Q

how to come up w a research q?

A

pick a q that interests u. u can find inspo all around u

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8
Q

what relationship lies at the heart of social sci inquiry

A

The relationship between attributes or characteristics of individuals and groups
lies at the heart of social scientific inquiry.

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9
Q

diff btwn theories in life n in sci?

A

y. Whereas our theories about events
in our lives are commonsense explanations based on educated guesses and personal
experience, to the social scientist, a theory is a more precise explanation that is frequently
tested by conducting research.

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10
Q

what is a theory and its goal?

A

A theory is a set of assumptions and propositions used by social scientists to explain,
predict, and understand the phenomena they study.
4 The theory attempts to establish a
link between what we observe (the data) and our conceptual understanding of why certain
phenomena are related to each other in a particular way.

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11
Q

after coming up w a theory n qs, what is the next step

A

Our next step is to test some of the ideas suggested by the gender segregation theory

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12
Q

what do theories suggest

A

. Instead, theories suggest specific concrete
predictions or hypotheses about the way that observable attributes of people or groups are
interrelated in real life

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13
Q

why are hyporthesis tentative and what are they

A

Hypotheses are tentative because they can be verified only after they
have been tested empirically. A statement predicting the relationship between two or more observable attributes.

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14
Q

are all hypotheses derived from theories and if not, where can they come from

A

Not all hypotheses are derived directly from theories. We can generate hypotheses in many
ways—from theories, directly from observations, or from intuition. Probably, the greatest
source of hypotheses is the professional or scholarly literature

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15
Q

what is a unit of analysis

A

Social scientists must also select a unit of analysis; that is, they must select the object of
their research. We often focus on individual characteristics or behavior, but we could also
examine groups of people such as families, formal organizations like elementary schools or
corporations, or social artifacts such as children’s books or advertisements

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16
Q

If we examine how often women are featured in prescription drug advertisements, what is the unit of analysis

A

the ads

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17
Q

how are hypotheses usually stated

A

d in terms of a relationship between an independent and a

dependent variable.

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18
Q

what is the variable the researcher wants to explain

A

dependent

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19
Q

what is an inependent vble

A

The variable that is expected to “cause” or account for the

dependent variable is called the independent variable.

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20
Q

how can you say two variables are causally related

A

To establish that two variables are causally related, your analysis must meet three
conditions: (1) The cause has to precede the effect in time, (2) there has to be an empirical
relationship between the cause and the effect, and (3) this relationship cannot be explained
by other factors.

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21
Q

for the crime example on page 35 how can we prove its a causal relationship

A

we need to show that : (1) The
reduction of crime actually occurred after the enactment of this measure, (2) the enactment
of the “three strikes and you’re out” measure was empirically associated with a decrease in
crime, and (3) the relationship between the reduction in crime and the “three strikes and
you’re out” policy is not due to the influence of another variable (e.g., the improvement of
overall economic conditions).

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22
Q

how can u find the indep n dep vbles

A

. The dependent variable is always the property that you are trying to explain; it is
always the object of the research.
2. The independent variable usually occurs earlier in time than the dependent variable.
3. The independent variable is often seen as influencing, directly or indirectly, the
dependent variable.

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23
Q

what should the purpose of the research help determine

A

The purpose of the research should help determine which is the independent variable and
which is the dependent variable.

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24
Q

what is the case w vbles in the real world

A

In the real world, variables are neither dependent nor

independent; they can be switched around depending on the research problem.

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25
what are some vbles that r never considered dep n why
Some variables, such as race, age, and ethnicity, because they are primordial characteristics that cannot be explained by social scientists, are never considered dependent variables in a social science analysis
26
what must researchers decide
As researchers, we must decide how to measure the variables of interest to us, how to select the cases for our research, and what kind of data collection techniques we will be using
27
. For instance, suppose we decide to study how one’s social class is related to attitudes about women in the labor force. Since attitudes about working women are not directly observable, we need to collect data by...
asking a group of people questions about their attitudes and opinions. A suitable method of data collection for this project would be a survey that uses some kind of questionnaire or interview guide to elicit verbal reports from respondents. The questionnaire could include numerous questions designed to measure attitudes toward working women, social class, and other variables relevant to the study.
28
The type of statistical operation we employ depends on ...
how our variables | are measured
29
The correspondence between the | properties we measure and the numbers representing these properties determines ...
the type | of statistical operations we can use
30
The degree of correspondence also leads to different ways of measuring—that is, to distinct levels of measurement. In this section, we will discuss three levels of measuremen
nominal, ordinal and intervaql ratio
31
At the nominal level of measurement
Because the different categories (e.g., males vs. females) vary in the quality inherent in each but not in quantity, nominal variables are often called qualitative. Other examples of nominal-level variables are political party, religion, and race.
32
nominal level of measurement
Numbers or other symbols are assigned to a set of categories for the purpose of naming, labeling, or classifying the observations. Nominal categories cannot be rank-ordered.
33
Nominal variables should include categories that are both exhaustive and mutually exclusive. Exhaustiveness means...
that there should be enough categories composing the variables to classify every observation. For example, the common classification of the variable marital status into the categories “married,” “single,” and “widowed” violates the requirement of exhaustiveness. As defined, it does not allow us to classify same-sex couples or heterosexual couples who are not legally married
34
we can make all vbles exhaustive how? when is this not recommended
by adding the category "other" However, this practice is not recommended if it leads to the exclusion of categories that have theoretical significance or a 38 substantial number of observations.
35
mutual exclusiveness
means that there is only one category suitable for each observation. For instance, the categories Protestant and Methodist are not mutually exclusive because Methodists are also considered Protestant and, therefore, could be classified into both categories.
36
ordinal measurement
t Numbers are assigned to rank-ordered categories ranging from low to high.
37
Whenever we assign numbers to rank-ordered categories ranging from low to high, we have...
an ordinal level of measurement. ex of a vble- social class
38
Like nominal variables, ordinal variables should include categories that are...
mutually exhaustive and exclusive
39
when has an interval ratio measurement been achieved
If the categories (or values) of a variable can be rank-ordered and if the measurements for all the cases are expressed in the same units, and equally spaced
40
examples of interval ratio vbles and why?
. Examples of variables measured at the interval-ratio level are age, income, and SAT scores. With all these variables, we can compare values not only in terms of which is larger or smaller but also in terms of how much larger or smaller one is compared with another
41
natural and arbitrary zero point
. In some discussions of levels of measurement, you will see a distinction made between interval-ratio variables that have a natural zero point (where zero means the absence of the property) and those variables that have zero as an arbitrary point. For example, weight and length have a natural zero point, whereas temperature has an arbitrary zero point. Variables with a natural zero point are also called ratio variables.
42
what do ratio vbles undergo in stats
In statistical practice, however, ratio variables are subjected to operations that treat them as interval and ignore their ratio properties
43
dichotomous vble and ex
a vble w only two values. Several key social factors, such as gender, employment status, and marital status, are dichotomies—that is, you are male or female, employed or unemployed, married or not married. Such variables may seem to be measured at the nominal level: You fit in either one category or the other. No category is naturally higher or lower than the other, so they can’t be ordered.
44
see graphy on pg 42 or 43
ok lol
45
However, because there are only two possible values for a dichotomy, we can measure it at...
the ordinal or the interval-ratio level.
46
an example of a dichotomy
For example, we can think of “femaleness” as the ordering principle for gender, so that “female” is higher and “male” is lower. Using “maleness” as the ordering principle, “female” is lower and “male” is higher. In either case, with only two classes, there is no way to get them out of order; therefore, gender could be considered at the ordinal level.
47
Dichotomous variables can also be considered to be interval-ratio level. Why is this?
In measuring interval-ratio data, the size of the interval between the categories is meaningful: The distance between 4 and 7, for example, is the same as the distance between 11 and 14. But with a dichotomy, there is only one interval. Therefore, there is really no other distance to which we can compare it. Mathematically, this gives the dichotomy more power than other nominal-level variables . bc of this, researchers may choose to dichotomozie their vbles. (pg 44)
48
discrete vbles
have a minimum-sized unit of measurement, | which cannot be subdivided
49
ex of a discrete vble
The number of children per family is an example of a discrete variable because the minimum unit is one child. A family may have two or three children, but not 2.5 children. The variable wages in our research example is a discrete variable because currency has a minimum unit (1 cent), which cannot be subdivided
50
Unlike discrete variables, continuous variables do not have ...
e a minimum-sized unit of measurement; their range of values can be subdivided into increasingly smaller fractional value
51
ex of a continuous vble
length- can have an infinite number of them even though they may not all b accurate
52
This attribute of variables—whether they are continuous or discrete—affects...
—affects subsequent research operations, particularly measurement procedures, data analysis, and methods of inference and generalization. However, keep in mind that, in practice, some discrete variables can be treated as if they were continuous, and vice versa
53
reread a cautionary note: measurement error on pg 46
ok
54
Specific techniques and practices for determining and improving measurement reliability and validity are the subject of...
research methods courses
55
Following the data collection stage...
researchers analyze their data and evaluate the | hypotheses of the study (pg 47)
56
Statistical procedures can be divided into two major categories:
descriptive and inferential
57
population- d and ex
. A population is the total set of individuals, objects, groups, or events in which the researcher is interested. For example, if we were interested in looking at voting behavior in the last presidential election, we would probably define our population as all citizens who voted in the election
58
why cant u study populations
Although we are usually interested in a population, quite often, because of limited time and resources, it is impossible to study the entire population.
59
sample and sampling- d n ex
. A subset of cases selected from a population is called a sample. The process of identifying and selecting this subset is referred to as sampling.
60
what will researchers do after collecting data from a sample
Researchers usually collect their data from a | sample and then generalize their observations to the population.
61
ultimate goal of sampling n why is it taken seriously
The ultimate goal of sampling is to have a subset that closely resembles the characteristics of the population. Because the sample is intended to represent the population that we are interested in, social scientists take sampling seriously
62
diff btwn desrciptinve and inferential stats and defs
Descriptive statistics includes procedures that help us organize and describe data collected from either a sample or a population. Occasionally data are collected on an entire population, as in a census. Inferential statistics, on the other hand, make predictions or inferences about a population based on observations and analyses of a sample
63
GSS
general social survey
64
why doesnt the avg of sample= avg of pop?
. But because the data are based on a sample rather than on the entire population, the average of the sample does not equal the average of the population as a whole. (also reread pg 49 it was confusing)
65
At the completion of these descriptive and inferential procedures, we can move to the next stage of the research process:
: the assessment and evaluation of our hypotheses and theories in light of the analyzed data.
66
reread pg 50
ok lol
67
statistics provides a link btwn... and how?
Statistics provide an important link between theory and research. The results of statistical analyses help us evaluate our hypotheses and theories, discover unanticipated patterns and trends, and provide the impetus for shaping and reformulating our theories.
68
Less partial and distorted explanations of social relations tend to result when ...
researchers, | research participants, and the research process itself reflect that diversity.
69
. Though diversity has been traditionally defined by | race, class, and gender,
, other social characteristics such as sexual identity, physical ability, religion, and age have been identified as important dimensions of diversity. Statistical procedures and quantitative methodologies can be used to describe our diverse society,
70
we will learn how to organize information using descriptive statistics and graphic techniques. These statistical tools can also be employed to ...
learn about the characteristics and experiences of groups in our society that have not been as visible as other groups.
71
devices n the bureau
For example, in a series of special reports published by the U.S. Census Bureau over the past few years, these descriptive statistical techniques have been used to describe the characteristics and experiences of ethnic minorities and those who are foreign born. Using data published by the U.S. Census Bureau, we discuss various graphic devices that can be used to explore the differences and similarities among the many social groups coexisting within the American society. These devices are also used to emphasize the changing age composition of the U.S. population
72
the similarities and commonalities in social experiences can be depicted using...
measures of central tendency
73
the differences and diversity within social groups | can be described using...
statistical methods of variation
74
. Inferential | statistics, such as the t test, chi-square, and the F statistic, help us determine...
the error involved in using our samples to answer questions about the population from which they are drawn.
75
bivariate analysis
which are especially 51 suited for examining the association between different social behaviors and attitudes and variables such as race, class, ethnicity, gender, and religion
76
we use inferential stats n bivariate analysis why?
We use these methods of analysis to show not only how each of these variables operates independently in shaping behavior but also how they interlock to shape our experience as individuals in society
77
We believe being statistically literate | involves more than just completing a calculation; it also means .....
learning how to apply and | interpret statistical information and being able to say what it means
78
Statistics are /...
procedures used by social scientists to organize, summarize, and communicate information. Only information represented by numbers can be the subject of statistical analysis.
79
The research process is...1. It consists of the following stages: 2
1 a set of activities in which social scientists engage to answer questions, examine ideas, or test theories 2asking the research question, formulating the hypotheses, collecting data, analyzing data, and evaluating the hypotheses.
80
A theory is 1Theories offer 2. These predictions, called | hypotheses, are 3
1a set of assumptions and propositions used for explanation, prediction, and understanding of social phenomena. 2specific concrete predictions about the way observable attributes of people or groups would be interrelated in real life 3tentative answers to research problems.
81
A variable is1 The variable that the researcher wants to explain (the “effect”) is called the 2. The variable that is expected to “cause” or account for the dependent variable is called the 3
1a property of people or objects that takes on two or more values. 2dependent variable. 3independent variable.
82
Three conditions are required to establish causal relations:
(1) The cause has to precede the effect in time; (2) there has to be an empirical relationship between the cause and the effect; and (3) this relationship cannot be explained by other factors.
83
At the nominal level of measurement, ...
numbers or other symbols are assigned to a set of categories | to name, label, or classify the observations. A
84
At the ordinal level of measurement, ...
categories can be | rank-ordered from low to high (or vice versa)
85
At the interval-ratio level of measurement, | ....
measurements for all cases are expressed in the same unit
86
A population is ...
the total set of individuals, objects, groups, or events in which the researcher is interested.
87
A sample is...
a relatively small subset selected from a population. Sampling is the process of identifying and selecting the subset.
88
Descriptive statistics includes ...
procedures that help us organize and describe data collected from either a sample or a population
89
Inferential statistics is concerned with ...
making predictions or | inferences about a population from observations and analyses of a sample
90
Descriptive statistics are used when
the research participants are the entire population or a sample is drawn from the population.