Any kind of data can be collected.
Data that is collected may have been collected previously for some reason, or it might have been collected recently. Data is usually collected to show statistics or information about something specific.
The collected data is organized in a fashion so you can determine if the hypothesis is supported.
Line graphs are often more clear to analyze, and are used for continuous data. bar graphs are used for just a certain amount of results, ones that don't continue.
The definition of statistics is the science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data.
Quantitative
A Likert scale is considered a quantitative measurement tool because it assigns numerical values to responses and allows for numerical analysis of data.
The next step in the scientific method is to analyze the data you collected.
it depends what you researching? what are your hypotheses and how are you going to treat your variables (ordinal, continous)? what scale are u using? 3, 5, 7 or more?in one case the analysis is a bit limited on the other hand there are many choices like Pearsons linear Gronbachs alpha and so on
Analyzing data helps scientists explain their observations and their explanations are based on the evidence they collected.
That depends upon whom you ask, as there is some degree of controversy around Likert scales. Many people, myself included, would consider it interval data, and it is usually interpreted that way. However, there is another school of thought that says that Likert data is ordinal at best. Both sides of the debate have valid points, and this question hasn't been settled.
The information collected during an experiment is called data. This data is used to analyze the results of the experiment and draw conclusions based on the findings.
The term that describes the data collected during an experiment is "experimental data". This data is gathered through observations, measurements, and other methods during the experimental process to analyze and draw conclusions.
If you are considering a single ordinal variable, determining the mode or median would be meaningful, but the mean or SD would not. Many researchers do consider likert-scale data to possess only ordinal qualities. However, leading research studies, for example in the marketing area, obtain measures such as means and standard deviations from likert-scale data. Indeed leading textbooks also follow this approach. One concern has been that the 'distances' between points on a likert scale are not equal, for example the 'distance' or 'difference' between a strongly disagree and disagree is not the same as the difference between disagree and neutral. A recent study discusses these issues, as well as demonstrating that data obtained from 5-point, 7-point and 10-point likert scales are approximately comparable in terms of mean score (once re-scaled) and various measures of variation and data shape. The study reference is Dawes, John "Do Data Characteristics Change According to the Number of Scale Points Used ? An Experiment using 5-point, 7-point and 10-point Scales" International Journal of Market Research, Vol 50 2008.
Thermometer, Spring Scale, and a Balance Scale ;-) Math Homework... Suckie! :P
The data collected during an experiment is called experimental data. It consists of observations, measurements, or information gathered during the experimental process to analyze and draw conclusions.
A data analysis tool, such as Microsoft Excel or Google Sheets, can help you organize and analyze data effectively. Additionally, using search engines like Google or databases like PubMed can assist in finding information collected by others.