Question

When you collect data to learn about a population, why do you worry about whether the data collected are categorical or numerical?

Short answer

Understanding whether the data is categorical or numerical is crucial in determining the appropriate statistical analysis technique to use, which in turn influences the conclusions drawn from the data.

Step-by-step solution

Understanding types of data

Different datasets have different types of data which could be categorical or numerical. Categorical data can be segregated into various groups or categories while numerical data is measurable and can be operated on mathematically.

Identify appropriate statistical techniques

The type of data dictates the statistical methods we can use for analysis. For instance, the mean, standard deviation etc. can't be calculated for categorical data but can be for numerical data. On the other hand, we can calculate the mode and relative frequencies for categorical data. Specific tests like chi-square tests are designed for categorical data, while t-tests and Z-tests are generally designed for numerical data.

Recognizing the implication of different types of data

In the interpretation phase, it is important to consider the type of data. As the techniques used for analysis vary between categorical and numerical data, the inferences from them are also inherently different.