To perform statistics on data, you have to understand the variables and find out what should be measured using the variables. Statistics offers different kinds of measurement and they are usually classified into qualitative and quantitative data. To use a ratio scale or any other type of measurement, we need to understand what a variable is. Show
A variable is something whose value changes and can be measured. For example, if you are looking at the voters in a particular area, there are many variables that you can use. It could be area, age, sex, job, previous voting history, and so on. Here’s a ratio scale example to help you understand it better: Which age group do you fall into? In this blog, we’ll cover: What is Ratio Scale? The Four Levels of MeasurementThe level of measurement of a variable helps you understand the statistical test that you need to use. How you measure a variable is considered as the level of measurement.
Each level of measurement is used to capture data in the form of surveys and questionnaires, with each of them being a multiple-choice question. Since each scale is an incremental level of measurement, they fulfill the function of the previous scale. In this article, we are going to look at the ratio scale, the 4th level of measurement, which is the ratio scale of measurement. What is Ratio Scale?The ratio scale is regarded as the variable measurement scale that produces the order of variables, and it also makes the difference between the variables known. A zero on a ratio scale means there is no presence of the variable that you are measuring. It helps understand the intervals, values, true zero characteristics, and the ultimate order in calculating ratios. For this reason, the ratio scale is considered the most informative scale. Here’s a simple ratio scale questionnaire created with SurveySparrow. Sign up below to create similar ratio scale questions surveys. Plus, get a full-feature trial of SurveySparrow absolutely FREE for 14 days. 14-Day Free Trial • No Credit Card Required • No Strings Attached What is a true zero?On a ratio scale, zero represents the total absence of the variable. For example, the number of teenagers in a ward or high-rise buildings is a ratio variable. It implies that the ward does not have teenagers or high-rise buildings. If you have a true zero on your scale, then you can measure the ratios of values. Ratio Scale ExamplesThe following are some of the most commonly used ratio scale examples. What is your weight range?
What is your height on the metric scale?
How much time do you exercise in a day?
What is the amount of calories you consume every day?
Some of the other examples that could be used are sales figures, ruler measurements, income earned during a period of time, years of education, number of children. Characteristics of Ratio Scale
How to Measure Ratio Scale?The data that you get from the ratio scale can be used in statistical analysis. Once you collect the required input, you can collect descriptive and inferential statistics. For inferential statistics:When the ratio scale is of normal distribution, then parametric tests are best for analysis. The latter helps make strong conclusions using your data. Some of the common examples are:
For descriptive statistics:#1. Frequency distribution: To find the frequency distribution, you can group the data in a table or plot it in a graph. #2. Central Tendency: You can use mean, median, or mode to calculate this. Mode is the most repeating value in your data. The Median is the value that is in the middle of the data. Mean uses all the values to give the researcher a single value for a central tendency. If the data you are using is distributed quantitative data, then it is advisable to use mean since it uses a single value of the data to measure the result. #3. Variability: The standard deviation, range, and variance are pivotal to indicating the presence of variability. If you want a range, you need to subtract the lowest value from the highest value of data. #4. Standard deviation indicates how far the score in your data lies from the mean on average. It is considered the average amount of variability. Moreover, a variance is the average standard deviation from your data’s mean. The square of the standard deviation gives you the variance. What are some of the popular ratio data analysis techniques?SWOT analysis:It is used to calculate the strengths, weaknesses, opportunities, and threats of an organization. It is popularly used to evaluate ratio data. Strength and weaknesses constitute the internal aspects of an organization, while opportunities and threats come from external sources. Organizations measure ratio data to understand what are the areas that they need to be careful about and which are the ones that they should be taking advantage of. Conjoint Analysis:It is a market research technique that is popularly used to analyze how individuals make complicated decisions based on a ratio scale. It helps organizations understand which are the various purchasing factors for customers when they have several choices in front of them. Businesses use conjoint analysis to conduct price research, test websites, improve product functionalities, add better user interfaces, and so on. Trend Analysis:It is a popular ratio data analysis technique that is used to find out the various trends and insights by gathering data. It captures insights using the help of survey data that is conducted numerous times, using the same question. Trend analysis is also big on predictive analysis, it lets you capture time-bound data and uses it to predict future needs. TURF Analysis:It is abbreviated as Totally Unduplicated Reach and Frequency Analysis. Using the analysis method, the business can analyze the potential of combining products and services. TURF values the ratio data of customers who have been reached out to through a particular source of communication and frequency. Will a new product, service, or combination be accepted by the target market? TURF analysis will give a pretty comprehensive idea of that. It is of great help in product distribution and line analysis. Cross Tabulation:This method helps understand the relationship between multiple variables. It is also called the contingency table and helps establish a correlation between multiple ratio data variables in the form of a table. Using the contingency table, businesses can make data-driven decisions. Businesses employ cross-tabulation analysis to understand the correlation between customer intent and product performance. There are a number of descriptive and inferential statistics that can be applied to the ratio scale. A ratio scale can calculate all statistical analyses including mean, median, mode, variance, and standard deviation. It can also calculate statistical tests such as t-test, f-test, chi-square, correlation, and so on. Wrapping UpThe ratio scale has all the characteristics necessary to make it a research scale, especially for pure sciences. Not only does it offer everything that the interval scale does, but its importance is also even more so prominent in the field of market research because of a well-defined zero. The non-arbitrary zero in ratio scale allows for the easy calculation of the value behind the attributes collected in the data for research. If you are looking to find an online survey tool to capture data from your potential customers, you have come to the right place. SurveySparrow is one of the best online survey tools in the market, and you will be able to ask brilliant ratio scale survey questions and conduct simple to complex surveys using them. Get in touch with us to understand how we can help you. |