Question

1. What is the difference between data and evidence? 2. Can you have data without evidence? 3. Can you have evidence without data?

Answer 1

Data is a synonym of evidence. As nouns the difference between data and evidence is that data is (time) date while evidence is obviousness, clearness. Data use for educational improvement is studied under many guises (e.g., data use, data-driven decisionmaking, evidence use), all with the same intention: providing districts, schools, and educators with better information that can ensure that students learn. If offered in a useful form, such data can help teachers, principals and other educational personnel learn more about their students, improve their teaching craft, and ultimately impact a variety of educational outcomes.

Evidence Use

Direct evidence is actual work showing knowledge and skills. Indirect evidence is student or faculty perceptions of student performance. Examples might include surveys, exit interviews, focus groups, or student self-assessment. These types of evidence are meant to be combined to more fully understand a learning outcome.

Evidence is a body of facts and information showing whether a hypothesis is true or untrue. Data forms the basis for evidence, so there's a lot of overlap between the two concepts. However, data is raw information with no judgment attached. Evidence is when data is used to try to prove or disprove a particular point.

So maybe your study of the colors of cars passing through an intersection might be used as evidence to show that the most popular color of car in your neighborhood is dark gray. Or, your data for what ages people get diagnosed with prostate cancer could be used as evidence for the proposition that prostate cancer affects mostly older men. Evidence should always be verifiable--it should be possible to get the same results and make the same conclusions by taking another look at the real world.

Data Use

Data driven decision-making is a subset of evidence-based decision making. Use of data involves a carefully organized set of evidence – ideally a combination of direct and indirect evidence that provides a rich display of information regarding the question at hand: “Are the students as a whole achieving the particular learning target at the desired level(s) of performance?”

Data should meet these criteria:

1. Systematically collected

2. Has been organized to aid its analysis, is not still in raw form

3. Based on a valid and reliable assessment

As much as a location in space cannot be determined without three reference points, drawing a conclusion about student learning based on a single line of evidence does not lead to a fully accurate conclusion. Organizing multiple lines of evidence, direct and indirect, into a data set, enhances the reliability of conclusions and is scholarly practice.

Empirical data is facts, numbers, and statistics measured in the real world and collected together for analysis. You could collect data on how many cars of different colors pass through an intersection, at what ages people get diagnosed with prostate cancer, or a million other things.

Data is usually most useful when it is made up of numbers. This is called quantitative data, but you can also have data that is made up of personal accounts and descriptions and other non-numerical information. This is called qualitative data. However, individual accounts and stories do not qualify as data--qualitative information only becomes data when it's put together on a large scale.

It is often said that, 'The plural of anecdote is not data.' This means that your personal experiences have no bearing on what the truth about a subject is--it would take the personal experiences of huge numbers of people before you could make conclusions from them.

Data is only evidence in the presence of an opinion or argument, otherwise, it is just data and has no meaning on its own. The problem is and why this matters, is that the moment you form an opinion you start to select which data you are going to use to support your argument.

So data is just data but on its own, it doesn’t have any validity or reliability (the two tests for good data. Validity = it measures or describes what it claims to, and reliability = it measures or describes it consistently). There is no such thing as 100% validity or reliability. There is always variation in any measurement or description and these variations can stack up. Due to the variations in components two apparently identical aircraft made next to each other at the same time can vary as much as 10-20% in weight from each other due to the compound effect of the cumulative variation.

Data is just data and has no intrinsic meaning on its own. Evidence has to be evidence for or of something; an argument, an opinion, a viewpoint or a hypothesis. The evidence you use depends on your argument. As we get more evidence or different types of evidence our argument might change.