Ratio Analysis With IBM SPSS

Introduction

Ratio statistical analysis is a great analytical method to infer a difference in a situation having gone through different phases. For instance, consider a group of employees with initial approximately zero knowledge about leadership and later sent on a leadership training for a month. Now their company want to investigate their efficiency before and after the training. Also, consider a company with different branches at different region of a country. After two years of operation at these regions, the company wish to evaluate the productivity of branch over the two years. In summary, ratio statistical analysis is very useful for evaluation.

To perform ratio analysis, you need the numerator variable which has to be a scale measure, denominator variable also a scale measure then a grouping variable which has to be a nominal variable.

Ratio analysis is a highly essential analysis in finances as it can be used to evaluate an organization’s profitability, liquidity, and the efficiency of the employees by using financial documents such as the balance sheet and revenue income.

Data

This tutorial uses automobile data from Kaggle: Kaggle Detaset

The aim of the analysis is to evaluate the horsepower category of the cars by the ratio of the number of cylinders and the price of the car. There are three categories of the horsepower: high, low, and medium. Which of this category has more of variability by the number of cylinders to the price of the car.

SPSS NAVIGATION

Analyze >>> Descriptics Statistics >>> Ratio

From the navigation, it can be inferred that ratio analysis falls under the descriptive analysis. In other words, it can be used to fore-understand your data prior advanced analysis.

In the next section, the variables for the analysis will be selected and these are the num ofcylinders_tr, price, and horsepowerbinned. The numerator is the number of cylinders, the denominator is the price of the vehicle, and the grouping variable is the binned horsepower (high, low, and medium).

Then, the statistics to be evaluated are chosen.

In the next navigation, the desired results for the analysis will be selected and, in this case, we are selecting the Median, Confidence intervals, COD, and COV (Mean and Median). The rationale for choosing these parameters and most especially COD and COV is that COD enables us to study how disperse a variable is, in other words, the larger the COD the higher the nonuniformity of the data of the variable. Hence, we can use this to study if there is significant difference in a variable before and after a process. While COV is the coefficient of variation, and it could be mean or median.

Simply, COD is the ratio variance to mean while COV is the ratio of standard to mean.

RESULTS

The result of the analysis is primarily in two places:

1. Case Processing Summary
2. Ratio analysis parameters result

In the first case, the “High” horsepower makes 11.5% of the data, 57.5% for the “Low” horsepower, and 31.0% for the “Medium” horsepower. Therefore, “Low” horsepower takes about average of the data.

From the ratio analysis as shown below, the COD result shows that “High” horsepower has the highest COD, followed by the “Medium” horsepower, and “Low” horsepower. What this means is that there is more variability in the ratio of the number of cylinders to the price of the vehicles with “High” horsepower than the “Low” and “Medium” horsepower.

The p-values imply that the variability in the horsepower categories is statistically significant.

Conclusion

In this blog, we have applied ratio analysis on a real-world data of automobile. As earlier stated, ratio analysis falls under the descriptive statistics, and this implies that ratio analysis can be used to describe your data. The result in this analysis has shown that there is more variability in the ratio of the number of cylinders to the price of the vehicles with “High” horsepower.

This analysis can be coupled with other analysis approaches such as Exploratory Data Analysis (EDA).

Related blog: Factor Analysis