NUR 705 Assignment 3.1: Levels of Measurement in Articles Introduction The goal of this assignment is to evaluate the independent and dependent variables in a selected article. Assignment Guidelines Review the article Physical and Psychological Effects of a 12-Session Cancer Rehabilitation Exercise ProgramLinks to an external site.. Prepare a written analysis of the article that answers the following questions: What are the independent variables and dependent variables in the selected article? What levels of measurement are the variables? How do they measure each variable? Your analysis should also include an introduction that summarizes independent and dependent variables in the article and a conclusion that provides closure to the topic. Maximum of one page. Include a reference citation at the end of your paper.

Types of Sampling Methods

Review the following video to learn more about sampling:

Types of Sampling Methods TranscriptLinks to an external site.

Evidence-Based Pyramid—Levels of Evidence

View the following to learn about the levels of evidence and sources of each.

Levels of Evidence Pyramid TranscriptLinks to an external site.

The EBP pyramid may be used as a guideline for selecting the best evidence to answer a clinical foreground question. The types of studies higher up the pyramid typically offer increased relevance to the clinical setting. However, fewer studies may be available and you may not find the highest level of evidence to answer your clinical foreground question. In that case, move down the pyramid and explore other types of studies.

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Independent and Dependent Variables

Review the video on independent and dependent variables.

Independent and Dependent Variables TranscriptLinks to an external site.

Levels of Measurement

Review the video on Levels of Measurement:

Levels of Measurement TranscriptLinks to an external site.

Levels of Measurement Transcript

Quantitative researchers measure variables to answer their research question. The level of measurement that is used to measure a variable has a significant impact on the type of test researchers can do with their data, and therefore the conclusions they can come to. The higher the level of measurement, the more statistical tests that can be run with the data. That is why it is best to use the highest level of measurement possible when collecting information.

In this video, nominal, ordinal, interval and ratio levels will be described in order from the lowest to the highest level of measurement. By the end of this video you should be able to identify the level of measurement being used in this study. You will also be familiar with types of tests that can be done with each level.

To remember these levels of measurement in order, use the acronym, NOIR, or noir. The level of measurement of a variable depends on the nature of that variable as well as how the researcher collects the data. For example, some variables, like gender, can only be measured in a nominal way. Other variables, like household income, can be measured at multiple levels, depending on how the question is asked.

The nominal level of measurement is the lowest level. Variables in this study are placed into mutually exclusive categories. Each category has a criteria that a variable either has or does not have. There is no natural order to these categories. The categories maybe assigned numbers, but the numbers have no meaning because they are simply labels.

For example, if we categorize people by hair color, people with brown hair do not have more or less of a characteristic than those with blonde hair. Nominal sounds like name, so it is easy to remember that at a nominal level you are simply naming categories. Nominal data may be considered dichotomous or categorical. Dichotomous data falls into one of two categories, like male and female, or yes and no. Categorical data have more than two possible values, such as marital status or group membership. Sometimes researchers refer to nominal data as categorical or qualitative because it is not numerical.

Since nominal data is simply categorical it allows for the few statistical tests. It makes sense to report the number or percentage of people who are male or female in a particular group. This data is often presented in bar or pie charts. The only measure of central tendency that makes sense with nominal data is the mode. Many other statistical tests just do not make sense from nominal data.

For example, since there is no natural way to order nominal d