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Five Principles of Politics

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1 Five Principles of Politics
1 Five Principles of Politics

2 Making Sense of Government and Politics
Two fundamental questions about government and politics: What do we observe? An empirical question Why? Requires building a theory around principles Two objectives in this introductory chapter: Explain what we mean by government and politics Introduce our five principles of politics

3 What is Government? The institutions and procedures through which a land and its people are ruled Governments may be simple, like a tribal council that makes all decisions, or they may be complex, like our own system of separate branches and levels of government

4 Discussion: Government in a Farming Society
Imagine that everyone in this room is a farmer in our own self-contained society We’re all equal in every respect One of us proposes to build an irrigation system How do we make decisions? Discussion: Imagine that everyone in the room is a farmer in our own self-contained society. We’re all equal in every respect. We all have farms that produce enough for our families to consume. Nobody is rich or poor. We’re all the same linguistically, racially, ethnically, and we all worship the same God. But one of us has come up with the idea of building an irrigation system so that our farms can be more productive in the future to generate surpluses that we may use to hedge against future drought or to sell to a neighboring society. The problem is that this construction project will require sacrifice in the short term. We’ll all have to give up some of our time and labor and some of our land to build the irrigation system and this means we will be a little hungry and overworked in the short term. How will we make a decision on this proposal? Will it require a majority, a consensus, or some number in between? How will we organize and enforce our agreements? What will we do about those who do not support the proposal if the majority of us decide to move forward with the project? Will they share in the benefits? How we decide to decide is establishing “the institutions and procedures through which a land and its people are ruled.” Getting students to work through the different kinds of arrangements that might be established and the implications of the institutions they establish allows them the chance to begin to imagine the different forms government may take.

5 Forms of Government: Inclusiveness
Autocracy – A single individual rules Oligarchy – A small group of landowners, military officers, or wealthy merchants rules Democracy – A system of rule that permits citizens to play a significant part in the governmental process

6 Forms of Government: Recognition of Limits
Constitutional – Formal and effective limits are placed on the powers of government Authoritarian – No formal limits are placed on government but government may be effectively limited by other social institutions Totalitarian – No formal or effective limits on government’s power of any kind Discussion: Students should be able to quickly identify where the United States falls within these forms of government but it is useful to get them to try to categorize other contemporary or historical examples of governments. Some useful examples for discussion might include North Korea, Nazi Germany, Feudal Europe, Ancient Athens, and contemporary Iran.

7 What is Politics? The conflicts and struggles over the leadership, structure, and policies of government Politics takes many forms – voting, running for office, joining groups and parties, lobbying, and even speaking to friends and neighbors The 5 principles of politics can be used to explain political action

8 Clicker Question Imagine a hypothetical society in which a king has almost total power but is constrained in his coercive power by the church. This government would best be described as a(n): authoritarian democracy. constitutional autocracy. totalitarian oligarchy. authoritarian autocracy. Answer: D

9 Introducing the 5 Principles of Politics
All political behavior has a purpose Institutions structure politics All politics is collective action Political outcomes are the products of individual preferences, institutional procedures, and collective action History matters

10 Rationality Principle
All political behavior has a purpose Political behavior is instrumental Not random Done with forethought Calculation Political actors pursue policy preferences, reelection, power, and to maximize their agency budgets

11 Institution Principle
Institutions structure politics Institutions are the rules and procedures that provide incentives for political behavior Remember that institutions themselves are not necessarily permanently fixed. Rules may change; they just don’t change easily

12 Institutions Provide Authority in Four Ways
Jurisdiction – The domain over which decisions may be made Agenda and Veto Power – Gatekeeping power and the power to say “no” Decisiveness – Rules for decision making Delegation – Transmission of authority

13 Collective Action Principle
All politics is collective action Collective action is difficult and the difficulty mounts as the number of people and interests involved grows Sometimes there are collective action dilemmas – situations in which individually rational incentives do not align with shared, collective interests

14 A Collective Dilemma Discussion:
This figure is from a story in the book about two neighbors who share a fence that will cost $1,000 to mend. If the fence is mended they each would get $700 of positive value. As the text explains, it is actually individually rational for Smith and Jones NOT to mend the fence even though their combined benefit would be $1,400 ($700 each) and the combined cost would only be $1,000. The figure shows Jones’s possible outcomes in the lower left side of each box and Smith’s outcomes in the upper right of each box. Notice that each person has a binary choice to contribute to mending the fence or not. Smith’s outcomes are $200 or -$300 if he chooses to mend the fence; his outcomes are $700 and $0 if he chooses not to mend the fence. In other words, no matter what Jones chooses to do, Smith is better off not mending the fence. This is true of Jones as well. What is most striking about this story is that the collective outcome (adding both their individual outcomes) is worst if they both don’t mend the fence. In all other outcomes, the collective outcome is +$400 though this benefit is most equitably distributed in a scenario where they both mend the fence. So, individually rational behavior leads to the worst collective outcome. This dilemma is known as the prisoner’s dilemma and will be re-visited in the chapter on interest groups. For students, it is useful to get them into groups to act as either Smith or Jones and to be paired up with another group acting as their neighbor. Have them discuss what to do (mend or don’t mend) and then share their answer at the same time. The point of the exercise is for students to understand the ways in which collective action may not happen even when there is a shared collective interest.

15 Collective Action is Difficult
Collective action becomes even more difficult as the number of parties involved increases or as the ability to bargain face-to-face is hampered. Examples: Free Riding Tragedy of the Commons Institutions are the solutions to these problems Discussion: Traffic patterns are another interesting way to introduce students to collective action problems. Ask students to imagine they are in a traffic jam caused by an accident a couple of miles ahead. Imagine the cars in the accident have been moved off to the shoulder of the road but traffic is still moving very slowly. Why? “Rubber-necking” is a good example of a collective action problem students have experienced. The person at the front of the traffic jam has an individual incentive to go slow and look at the accident while all others pay most of the cost. It is also a good example to use to show students how institutions are the solution to this collective action problem.

16 Policy Principle Political outcomes are the products of individual preferences and institutional procedures The policy principle is the logical combination of the first three principles

17 History Principle How we got here matters
Path dependency – certain possibilities are made more or less likely because of the historical path taken

18 Clicker Question A member of Congress seeks to bring additional dollars home to his districts for construction of roads and bridges. This is an example of the: Institution Principle. Rationality Principle. History Principle. Collective Action Principle. Answer: B

19 19

20 The five principles introduced in this chapter provide a foundation for understanding and explaining the facts of political life; they capture the basic framework that underlies our analysis of politics. However, to make and test arguments about politics, we need more than just an analytical framework; we also need empirical evidence. We need to understand how political scientists uncover facts about politics and what tools they use to analyze and interpret these facts. What data are relevant to an argument about politics? How do we learn things from these data? How do we test arguments about the data? Consider one of the most basic questions about voting: Why do people vote the way they do? In elections, Americans face two main alternatives in the form of the Democratic Party and the Republican Party. These parties have distinctive policy priorities, notably in the important area of economic policy. Since at least the 1930s, the Democratic Party has favored economic policies that redistribute income to poorer segments of society; Republicans, on the other hand, favor lower taxes and little or no redistribution. If those are the choices, we might argue that it makes sense to vote according to one’s economic self- interest: choose the candidate from the party that maximizes your income. On reflection, however, we can see that other factors may also affect election outcomes and voting, including the candidates’ personal qualities, important noneconomic issues, and even habits. Which best explains vote choice? What Are Data? There is, in our example, a behavior that we generally want to explain, vote choice. We represent this general construct as a variable. A variable defines all possible outcomes that might have occurred and assigns them a unique label or value. Vote choice, for instance, may take four possible values or outcomes: vote for the Democratic Party candidate, vote for the Republican Party candidate, vote for another party or candidate, or don’t vote. The second step is to measure the behavior of interest. This stage requires the collection of data. Observation of a small set of events can be quite enlightening. We might, for instance, conduct in-depth interviews with a dozen or so people about how they decided to vote. However, we often require more evidence to support a given claim; a small number of people might not be sufficiently representative. Censuses and random sample surveys are staples of social science data collection. With a census we observe all individuals in a population at a given moment. Every 10 years, the United States conducts a comprehensive enumeration of all people living in the country, including information on families, education levels, income, race and ethnicity, commuting, housing, and employment. An election is a census of sorts, as it is a comprehensive count of all votes cast in a given election. So we can measure vote choice by taking count of all electoral votes (Table A). A survey, on the other hand, consists of a study of a relatively small subset of individuals. We call this subset a sample . One of the most important social science research projects of the second half of the twentieth century is the American National Election Study, or ANES. The ANES is a national survey that has been conducted during every presidential election and most midterm congressional elections since 1948 to gauge how people voted and to understand why. In recent years, the ANES has used a sample of between 1,000 and 2,000 Americans to make inferences about the entire voting population of over 100 million. So voter behavior can also be measured through surveys. Today, most of the information used by public policy makers, businesses, and academic researchers, including estimates of unemployment and inflation, television and radio ratings, and most demographic characteristics of the population, are measured using surveys. Summarizing Data. Communicating the information in a census or survey requires tools for summarizing data. First, we compute the frequency with which each value of a variable occurs. Frequency may be either the actual number of times that a specific behavior or value of a variable occurs or the percent of the observations in which it occurs. Second, we construct a graph or statistic that summarizes the frequencies of all values of the variable. The distribution of a variable expresses how often each of the values of the variable occurs. A bar chart displays all possible values of a variable on one axis, usually the horizontal axis; the heights of the bars equal the frequency or percent of cases observed for each value (Figure A). In a pie chart, the frequency for each value is depicted as a share of the whole (Figure B). A line graph is often used to show frequency over time (Figure C). A statistical table typically displays the values of the variable along the left-hand side of the table and the frequencies, which may be the number or the percentage of occurrences, to the right (Table A). 20

21 The five principles introduced in this chapter provide a foundation for understanding and explaining the facts of political life; they capture the basic framework that underlies our analysis of politics. However, to make and test arguments about politics, we need more than just an analytical framework; we also need empirical evidence. We need to understand how political scientists uncover facts about politics and what tools they use to analyze and interpret these facts. What data are relevant to an argument about politics? How do we learn things from these data? How do we test arguments about the data? Consider one of the most basic questions about voting: Why do people vote the way they do? In elections, Americans face two main alternatives in the form of the Democratic Party and the Republican Party. These parties have distinctive policy priorities, notably in the important area of economic policy. Since at least the 1930s, the Democratic Party has favored economic policies that redistribute income to poorer segments of society; Republicans, on the other hand, favor lower taxes and little or no redistribution. If those are the choices, we might argue that it makes sense to vote according to one’s economic self- interest: choose the candidate from the party that maximizes your income. On reflection, however, we can see that other factors may also affect election outcomes and voting, including the candidates’ personal qualities, important noneconomic issues, and even habits. Which best explains vote choice? What Are Data? There is, in our example, a behavior that we generally want to explain, vote choice. We represent this general construct as a variable. A variable defines all possible outcomes that might have occurred and assigns them a unique label or value. Vote choice, for instance, may take four possible values or outcomes: vote for the Democratic Party candidate, vote for the Republican Party candidate, vote for another party or candidate, or don’t vote. The second step is to measure the behavior of interest. This stage requires the collection of data. Observation of a small set of events can be quite enlightening. We might, for instance, conduct in-depth interviews with a dozen or so people about how they decided to vote. However, we often require more evidence to support a given claim; a small number of people might not be sufficiently representative. Censuses and random sample surveys are staples of social science data collection. With a census we observe all individuals in a population at a given moment. Every 10 years, the United States conducts a comprehensive enumeration of all people living in the country, including information on families, education levels, income, race and ethnicity, commuting, housing, and employment. An election is a census of sorts, as it is a comprehensive count of all votes cast in a given election. So we can measure vote choice by taking count of all electoral votes (Table A). A survey, on the other hand, consists of a study of a relatively small subset of individuals. We call this subset a sample . One of the most important social science research projects of the second half of the twentieth century is the American National Election Study, or ANES. The ANES is a national survey that has been conducted during every presidential election and most midterm congressional elections since 1948 to gauge how people voted and to understand why. In recent years, the ANES has used a sample of between 1,000 and 2,000 Americans to make inferences about the entire voting population of over 100 million. So voter behavior can also be measured through surveys. Today, most of the information used by public policy makers, businesses, and academic researchers, including estimates of unemployment and inflation, television and radio ratings, and most demographic characteristics of the population, are measured using surveys. Summarizing Data. Communicating the information in a census or survey requires tools for summarizing data. First, we compute the frequency with which each value of a variable occurs. Frequency may be either the actual number of times that a specific behavior or value of a variable occurs or the percent of the observations in which it occurs. Second, we construct a graph or statistic that summarizes the frequencies of all values of the variable. The distribution of a variable expresses how often each of the values of the variable occurs. A bar chart displays all possible values of a variable on one axis, usually the horizontal axis; the heights of the bars equal the frequency or percent of cases observed for each value (Figure A). In a pie chart, the frequency for each value is depicted as a share of the whole (Figure B). A line graph is often used to show frequency over time (Figure C). A statistical table typically displays the values of the variable along the left-hand side of the table and the frequencies, which may be the number or the percentage of occurrences, to the right (Table A). 21

22 The five principles introduced in this chapter provide a foundation for understanding and explaining the facts of political life; they capture the basic framework that underlies our analysis of politics. However, to make and test arguments about politics, we need more than just an analytical framework; we also need empirical evidence. We need to understand how political scientists uncover facts about politics and what tools they use to analyze and interpret these facts. What data are relevant to an argument about politics? How do we learn things from these data? How do we test arguments about the data? Consider one of the most basic questions about voting: Why do people vote the way they do? In elections, Americans face two main alternatives in the form of the Democratic Party and the Republican Party. These parties have distinctive policy priorities, notably in the important area of economic policy. Since at least the 1930s, the Democratic Party has favored economic policies that redistribute income to poorer segments of society; Republicans, on the other hand, favor lower taxes and little or no redistribution. If those are the choices, we might argue that it makes sense to vote according to one’s economic self- interest: choose the candidate from the party that maximizes your income. On reflection, however, we can see that other factors may also affect election outcomes and voting, including the candidates’ personal qualities, important noneconomic issues, and even habits. Which best explains vote choice? What Are Data? There is, in our example, a behavior that we generally want to explain, vote choice. We represent this general construct as a variable. A variable defines all possible outcomes that might have occurred and assigns them a unique label or value. Vote choice, for instance, may take four possible values or outcomes: vote for the Democratic Party candidate, vote for the Republican Party candidate, vote for another party or candidate, or don’t vote. The second step is to measure the behavior of interest. This stage requires the collection of data. Observation of a small set of events can be quite enlightening. We might, for instance, conduct in-depth interviews with a dozen or so people about how they decided to vote. However, we often require more evidence to support a given claim; a small number of people might not be sufficiently representative. Censuses and random sample surveys are staples of social science data collection. With a census we observe all individuals in a population at a given moment. Every 10 years, the United States conducts a comprehensive enumeration of all people living in the country, including information on families, education levels, income, race and ethnicity, commuting, housing, and employment. An election is a census of sorts, as it is a comprehensive count of all votes cast in a given election. So we can measure vote choice by taking count of all electoral votes (Table A). A survey, on the other hand, consists of a study of a relatively small subset of individuals. We call this subset a sample . One of the most important social science research projects of the second half of the twentieth century is the American National Election Study, or ANES. The ANES is a national survey that has been conducted during every presidential election and most midterm congressional elections since 1948 to gauge how people voted and to understand why. In recent years, the ANES has used a sample of between 1,000 and 2,000 Americans to make inferences about the entire voting population of over 100 million. So voter behavior can also be measured through surveys. Today, most of the information used by public policy makers, businesses, and academic researchers, including estimates of unemployment and inflation, television and radio ratings, and most demographic characteristics of the population, are measured using surveys. Summarizing Data. Communicating the information in a census or survey requires tools for summarizing data. First, we compute the frequency with which each value of a variable occurs. Frequency may be either the actual number of times that a specific behavior or value of a variable occurs or the percent of the observations in which it occurs. Second, we construct a graph or statistic that summarizes the frequencies of all values of the variable. The distribution of a variable expresses how often each of the values of the variable occurs. A bar chart displays all possible values of a variable on one axis, usually the horizontal axis; the heights of the bars equal the frequency or percent of cases observed for each value (Figure A). In a pie chart, the frequency for each value is depicted as a share of the whole (Figure B). A line graph is often used to show frequency over time (Figure C). A statistical table typically displays the values of the variable along the left-hand side of the table and the frequencies, which may be the number or the percentage of occurrences, to the right (Table A). 22

23 The five principles introduced in this chapter provide a foundation for understanding and explaining the facts of political life; they capture the basic framework that underlies our analysis of politics. However, to make and test arguments about politics, we need more than just an analytical framework; we also need empirical evidence. We need to understand how political scientists uncover facts about politics and what tools they use to analyze and interpret these facts. What data are relevant to an argument about politics? How do we learn things from these data? How do we test arguments about the data? Consider one of the most basic questions about voting: Why do people vote the way they do? In elections, Americans face two main alternatives in the form of the Democratic Party and the Republican Party. These parties have distinctive policy priorities, notably in the important area of economic policy. Since at least the 1930s, the Democratic Party has favored economic policies that redistribute income to poorer segments of society; Republicans, on the other hand, favor lower taxes and little or no redistribution. If those are the choices, we might argue that it makes sense to vote according to one’s economic self- interest: choose the candidate from the party that maximizes your income. On reflection, however, we can see that other factors may also affect election outcomes and voting, including the candidates’ personal qualities, important noneconomic issues, and even habits. Which best explains vote choice? What Are Data? There is, in our example, a behavior that we generally want to explain, vote choice. We represent this general construct as a variable. A variable defines all possible outcomes that might have occurred and assigns them a unique label or value. Vote choice, for instance, may take four possible values or outcomes: vote for the Democratic Party candidate, vote for the Republican Party candidate, vote for another party or candidate, or don’t vote. The second step is to measure the behavior of interest. This stage requires the collection of data. Observation of a small set of events can be quite enlightening. We might, for instance, conduct in-depth interviews with a dozen or so people about how they decided to vote. However, we often require more evidence to support a given claim; a small number of people might not be sufficiently representative. Censuses and random sample surveys are staples of social science data collection. With a census we observe all individuals in a population at a given moment. Every 10 years, the United States conducts a comprehensive enumeration of all people living in the country, including information on families, education levels, income, race and ethnicity, commuting, housing, and employment. An election is a census of sorts, as it is a comprehensive count of all votes cast in a given election. So we can measure vote choice by taking count of all electoral votes (Table A). A survey, on the other hand, consists of a study of a relatively small subset of individuals. We call this subset a sample . One of the most important social science research projects of the second half of the twentieth century is the American National Election Study, or ANES. The ANES is a national survey that has been conducted during every presidential election and most midterm congressional elections since 1948 to gauge how people voted and to understand why. In recent years, the ANES has used a sample of between 1,000 and 2,000 Americans to make inferences about the entire voting population of over 100 million. So voter behavior can also be measured through surveys. Today, most of the information used by public policy makers, businesses, and academic researchers, including estimates of unemployment and inflation, television and radio ratings, and most demographic characteristics of the population, are measured using surveys. Summarizing Data. Communicating the information in a census or survey requires tools for summarizing data. First, we compute the frequency with which each value of a variable occurs. Frequency may be either the actual number of times that a specific behavior or value of a variable occurs or the percent of the observations in which it occurs. Second, we construct a graph or statistic that summarizes the frequencies of all values of the variable. The distribution of a variable expresses how often each of the values of the variable occurs. A bar chart displays all possible values of a variable on one axis, usually the horizontal axis; the heights of the bars equal the frequency or percent of cases observed for each value (Figure A). In a pie chart, the frequency for each value is depicted as a share of the whole (Figure B). A line graph is often used to show frequency over time (Figure C). A statistical table typically displays the values of the variable along the left-hand side of the table and the frequencies, which may be the number or the percentage of occurrences, to the right (Table A). 23

24 The distribution of income in the United States offers a somewhat different example. This variable takes a range of values from the smallest household income to the largest household income, which we can organize in categories. In Figure D, the first category is “less than $10,000,” the second category is “$10,000 to $14,999,” and so forth up to top category, “$200,000 or more.” All possible income levels are covered in this classification. Variables such as income can also be characterized with statistics, such as the median or mean. In this example, the median is the value of household income such that half of all households have income below the value and half have income above it. Fifty percent of all cases have income above the median value, and fifty percent have income below it; thus the median is also called the fiftieth percentile. The median household income in the United States in 2007 was $50,233, meaning that half of all households have income below that value and half have income above that amount. The mean is the average value for the variable. In the case of household income, the mean equals the sum of all households’ incomes divided by the number of households. Personal income totaled approximately $11.6 trillion in 2007, and there were 117 million households. So the average household income was $99,800. Why do the median and mean differ? In calculating the median, every household is equal. We merely count the percent above and below a certain income level. The mean value weights households according to their count the percent above and below a certain income level. The mean value weights households according to their incomes; consequently, a household with $200,000 income contributes 10 times as much to the calculation of the mean as a household with $20,000. If there were only small differences in income among households, the mean would be very close to the median. The difference between the median income and the mean income thus provides a way to measure inequality. The concept of the median is particularly important in thinking about voting. In an election involving two parties or candidates, it takes at least 50 percent of the votes to win. In a legislature, any bill must receive at least half of the votes of those present in order to pass. Suppose a piece of legislation directly affects people’s incomes by taxing those with income above a certain level, say $75,000, and redistributing that income to people who make less than that amount. Suppose also that people only care about their personal income when thinking about this bill. Based on the data in Figure D, if people voted only on the basis of their income—their economic self-interest—then the 31.1 percent with incomes over $75,000 would oppose the tax and 68.9 percent would support it. In such a setting, one could easily see that democracy would inevitably tax the rich and redistribute wealth. 24

25 Testing Arguments Using Data
Testing Arguments Using Data. The argument that democracy will tend to redistribute wealth depends on an important assumption—that people vote their economic self-interest. Is that assumption correct? Usually, such conjectures take the form of a hypothesis that there is a strong relationship between two variables, such as income and the vote. To test the argument that people vote their economic self-interest, we want to know how much voting decisions depend on individuals’ income levels. As stated earlier, in the United States today, the Republican Party generally favors lower income taxes and less income redistribution, and the Democratic Party favors higher income taxes and more income redistribution. We therefore want to know if those in high-income households vote Republican at a much higher rate than those in low-income households. The difference in voting behavior between these two groups is the effect of income on the vote. To see whether the effect of income on the vote is indeed large, we can use the data in Table B to examine the actual voting behavior of different sorts of individuals. The national exit polls in 2008 reveal that 73 percent of voters with income less than $15,000 chose the Democrat, Barack Obama. By comparison, 52 percent of those with income over $200,000 chose Barack Obama. This large difference (21 percentage points) reveals that income is associated with vote choice, but it is not absolutely determinative: no income group voted overwhelmingly Republican in this election. As we explore alternative arguments about vote choice, we can make many different comparisons— Democrats versus Republicans, men versus women, college graduates versus high school graduates, and so forth. Our goal is to find which, if any, of these potential explanations best accounts for the variation in vote choice. Throughout this book, we will consider other outcomes besides voter behavior, such as the support by members of Congress for different types of legislation and the percent of times that the executive succeeds in passing legislation—in each case, what we know about these phenomena in American politics is informed by an analytical approach to evidence. Many times we will look for a relationship or association between two variables to see if the predictions from an argument hold true, and if they do, we take that as evidence supporting the argument. A relationship or association between two variables, sometimes called a correlation , should not be taken to mean that one of the variables caused the other to occur. Causation is more difficult to establish. A correlation between two variables X (say, education) and Y (say, income) is consistent with a theory that says that education increases one’s earning power. From a simple correlation, however, one cannot tell whether variable X caused variable Y or Y caused X or some other variable W (say intelligence) caused both. Social scientists design experiments and carefully controlled comparisons (such as comparisons of twins) in order to measure causal relationships. Observing simple associations and correlations, though, is a first step in verifying our arguments, ideas, and theories about how politics works. 25

26 Be a Savvy Consumer of Quantitative Data
Be a Savvy Consumer of Quantitative Data. Beyond the figures and tables in this book, which reflect data from sources that we consider reliable and accurate, you will undoubtedly encounter other data about politics in the news and elsewhere. Before you take such data—and whatever argument they seem to support—at face value, it is worth asking a few questions about how the data were gathered and presented. What is the source of the data? Is it a respected source like a government office or a major mainstream news organization, which may be relied upon to gather and report data accurately? Or is it from a source that is likely to have a goal other than accurate presentation of the data, like an interest group or a campaign or an entertainment Web site? What is the date (or date range) for the data? What is being measured? For example, in a poll showing support for a candidate, is it the percent of all Americans? The percent of likely voters? The percent of Democrats or Republicans? Why are the data presented a certain way? Is this the best way to present these data? Does it distort the data in any way? What relationships and patterns do we observe in the data? Thinking through the questions above can also help you better understand the information in the data figures and tables found throughout this book. In each of the chapters to follow, you will also find an Analyzing the Evidence section, highlighting arguments and evidence on some of the subjects of that chapter. Many of these sections discuss how political scientists use the basic methodology discussed above to test arguments about American politics. You will then have an opportunity to analyze related data yourself in accompanying exercises on the StudySpace student Web site (wwnorton.com/studyspace). 26


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