Data description

Why Manage Your Data?

Data description

Data description refers to how the results from research studies are organized, summarized, and characterized statistically.

Expert Answers Certified Educator Introduction Almost all research investigations involve studying a sample of individuals randomly selected from a population with the goal of applying what is learned from the sample to all the individuals who constitute the population.

A critical part of this enterprise entails organizing, Data description, and characterizing the data collected from the sample in meaningful ways.

To accomplish this aim, researchers use statistical procedures and graphing techniques. Among these techniques are frequency distributions, measures of central Introduction Almost all research investigations involve studying a sample of individuals randomly selected from a population with the goal of applying what is learned from the sample to all the individuals who constitute the population.

Among these techniques are frequency distributions, measures of central tendency, and measures of variability. In addition, the numbers that constitute research data have different meanings.

Data description

This is reflected in the scales of measurement to which numbers adhere. Scales of Measurement Not all numbers are created equal. Different numbers have different meanings and thus have different characteristics.

To differentiate these characteristics, one must understand the scale of measurement to which numbers adhere. There are four scales of measurement. In ascending order, they are nominal, ordinal, interval, and ratio. Each scale has all the characteristics of the preceding scale plus one additional unique characteristic.

Numbers that adhere to the nominal scale simply represent different categories or groups, such as the numbers 1 or 2 to indicate the gender of a research subject. The ordinal scale has the characteristic of different categories but also reflects relative magnitude or degree of measurement, such as ranking photographs from 1 to 5 based on their aesthetic qualities.

Both features of separate categories and relative magnitude are reflected in the next scale, the interval scale, with the added characteristic that the distances between successive numbers on the scale are of equal interval. Temperatures on either the Celsius or Fahrenheit scale would be examples of an interval scale of measurement.

Finally, numbers that adhere to the ratio scale of measurement reflect the three characteristics of the interval scale along with an absolute zero point, with a value of 0 representing the absence of the measurement. The variables, for example, of time, height, or body weight all would adhere to the ratio scale of measurement.

In a research context, knowing the scale of measurement to which numbers adhere will have an impact on the type of statistical procedure used to analyze the data. Organizing Data At the completion of any research study, the data collected need to be organized and summarized in ways that allow the researcher to identify trends or other interesting consistencies in the results.

One of the techniques for organizing and summarizing data, especially large sets of data, is the frequency distribution. Frequency distributions allow the researcher to tabulate the frequencies associated with specific response categories and also allow for the data to be summarized and characterized in a more manageable fashion.

The organized frequency data are then presented in table form, with the response categories organized in ascending or descending order. Organizing the results in such a manner will facilitate making interpretations from and conclusions about the data.

Generally speaking, there are two types of frequency distribution: These two types of frequency distribution are constructed identically, with one exception.

The simple frequency distribution entails categorizing frequencies for each and every possible response category or score symbolized as Xwhile grouped frequency distributions combine specific categories or specific scores into groups called class intervals.

Grouping frequencies into class intervals has the advantage of making data sets with wide-ranging categories or scores easier to manage and thus easier to summarize. However, doing so does come with a price. By grouping categories or scores together, the researcher loses some specificity with regard to the number of frequencies associated with particular categories or scores.Quick Answer Data description refers to how the results from research studies are organized, summarized, and characterized statistically.

It is critical to begin to document your data at the very beginning of your research project, even before data collection begins; doing so will make data documentation easier and reduce the likelihood that you will forget aspects of your data later in the research project.

Metadata: One element of data documentation is the description of the data, known as metadata. Metadata is often defined literally, as data about data, which refers to the information used to describe an item's attributes in a standardised format e.g.

the author's name and title of a book in a library catalogue. Data Desk is an exciting update for all Data Desk 8 users that brings brand new features. XLSX import brings your everyday data into perspective with Data Desk analytics. Relations are automatically imported and .

Data description

It is critical to begin to document your data at the very beginning of your research project, even before data collection begins; doing so will make data documentation easier and reduce the likelihood that you will forget aspects of your data later in the research project.

Ch3: Data Description Santorico – Page 71 Rules and Notation: Let x represent the variable for which we have sample data. Let n represent the number of observations in the sample.

(the sample size). Let N represent the number of observations in the population. x represents the sum of all the data values of x. x2 is the sum of the data values after squaring them.

Introduction - Research data management - LibGuides at Curtin University