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Univariate and Bivariate Data Analysis

bivariate data analysis examples online

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It is most definitely true that there are highly sophisticated forms of quantitative analysis. However, there are some that are very basic or clear as graphical data analysis. Bivariate and univariate data analysis happen to be fairly simple in format. The former will concern itself with the analysis of two variables to find out if there’s empirical relationship, and the latter will only be concerned with the analysis of a single variable. Univariate data analysis happens to be more descriptive.

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The Differences between Univariate and Bivariate Data Analysis

In a real-life research situation, univariate data analysis puts all of its eggs in one basket. Only one aspect is observed in a given period of time, and this can be put into a list. For example, if we have a group of people, and we are looking at the physical attributes, we can do univariate data analysis. We may look at the weight only, or the height only, or the color of eyes. Only one of the traits is going to be examined.

With a bivariate analysis. We are looking at two variables. With the same group of people we would be looking at height and weight, or weight and color of eyes, or any other combination of two traits that we determined before. Whereas with the univariate analysis we place the information in a list, the bivariate information can be placed in a table that has two columns.

Bivariate Data Analysis Examples

Percentage tables and scatterplot graphs are highly used forms of bivariate analysis. The correlation coefficient may be computed, and exploration of the dependent and independent variable may be explored. An bivariate data analysis example here would be determining the correlation between the hours of swimming practice and the time a swimmer registers for fifty yard race. The independent, or predictor, variable would be the hours of practice and the dependent would be the actual times which will change with each swimmer.

Education is another area where bivariate data analysis is important. When it comes to test scores, bivariate analysis can explain outcomes which would match the independent variable. This might be a standardized test score against the grade-point average achieved in the marking period immediately after the test. Marketing research might also use bivariate data analysis to determine what day of the week has the most customers coming into a store.

Easier Can Make Better Sense

Simplicity does not mean bad data or poor information. It means that the analysis being conducted does not have to be very sophisticated in order to get the desired information. Software packages such as SPSS can make use of bivariate data analysis with cross tabs. Pattern of relationships and strength of relationships can be determined with the use of such software. Bivariate data analysis in its columns and tables produce information that is easily understood by anyone viewing it. That makes bivariate data analysis rather advantageous. It doesn’t take a lot of explanation to tell the story that the data in a bivariate table is providing. Comprehension is very quick. It goes without saying also that the collection and preparation of data in a bivariate data analysis study is fairly easy.

Check out our bivariate data analysis examples today!