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Applied Social Science Methodology

Name: Applied Social Science Methodology
Author: John Gerring, Dino Christenson

An Introductory Guide

John Gerring, Dino Christenson

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Applied Social Science Methodology

An Introductory Guide

John Gerring, Dino Christenson

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About This Book

This textbook provides a clear, concise, and comprehensive introduction to methodological issues encountered by the various social science disciplines. It emphasizes applications, with detailed examples, so that readers can put these methods to work in their research. Within a unified framework, John Gerring and Dino Christenson integrate a variety of methods - descriptive and causal, observational and experimental, qualitative and quantitative. The text covers a wide range of topics including research design, data-gathering techniques, statistics, theoretical frameworks, and social science writing. It is designed both for those attempting to make sense of social science, as well as those aiming to conduct original research. The text is accompanied by online practice questions, exercises, examples, and additional resources, including related readings and websites. An essential resource for undergraduate and postgraduate programs in communications, criminal justice, economics, business, finance, management, education, environmental policy, international development, law, political science, public health, public policy, social work, sociology, and urban planning.

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Information

Publisher

Cambridge University Press

Year

2017

ISBN

9781108116817

Topic

Social Sciences

Subtopic

Social Science Research & Methodology

Index

Social Sciences

if

there

was

truly

no

difference

between

means

due

to

actual

differences

in

the

population,

then

the

differences

that

do

show

up

in

the

samples

should

look

like

random

ﬂ

uctuations

about

the

mean

with

most

scores

close

to

the

mean

and

few

scores

in

the

tail.

Indeed

the

difference

in

means

should

overestimate

and

under-

estimate

the

mean

in

roughly

equal

numbers.

In

addition,

the

mean

of

the

difference

in

means

should

be

close

to

zero

as

the

true

central

tendency

of

cases

is

to

have

no

difference

between

the

sample

means.

Figure

21.1

plots

the

histogram

of

differences

overlayed

with

a

polygon.

The

polygon

shows

that

after

only

70

draws

from

each

sample

we

can

already

see

a

shape

that

somewhat

resembles

the

normal

curve,

which

we

should

expect

given

the

central

limit

theorem.

More-

over,

the

mean

is

zero,

which

suggests

the

samples

are

very

similar

to

each

other.

Table

21.3

Distribution

of

differences

between

means

Differences

Frequency

–

1

10

–

2

8

–

3

5

–

4

3

–

5

1

Differences

Frequency

–4

–2

0

2

4

0

5

10

15

Figure

21.1

Histogram

with

polygon

of

differences

between

means

n

318

Bivariate

Statistics