Five Tips For Doing An Excellent Statistical Analysis Of Data

Statistical Analysis of Data: Data-driven has become a rule of thumb for any business that wants to get ahead in the market. And this is only possible thanks to the statistical analysis of data, capable of pointing out patterns and trends related to your activities.

This study is crucial for the company’s plans, from increasing sales conversion to improving customer relationships. Statistical analysis is divided into two categories based on data collection and evaluation: descriptive and modeling. The first summarizes and describes the data, while the second tests hypotheses and concludes the samples evaluated.

If you still have difficulties with the statistical analysis of data, do not leave this screen, as we have made a list of the best tips to avoid mistakes. Check out!

How To Do An Efficient Statistical Analysis Of Data?

To gain valuable insights, the data analysis process needs to be very well structured. So, follow the topics below to get this task right.

Calculate The Arithmetic Mean And Standard Deviation

The arithmetic mean is the total of a list of numbers divided by the number of items presented in the report. Its objective is to point out general trends in analyzing a given data group. You can calculate what is beneficial or not for your organization.

The standard deviation is characterized as the measure of a data set that refers to an average. If it is high, the data are far from the arithmetic mean. But if the pattern is too low, there is probably more data in line with the arithmetic mean.

Interpret And Apply The Regression

If not interpreted correctly, numbers alone don’t say much. Therefore, it is essential to interpret and apply regression — an action that models the existing associations between the variables considered dependent and explanatory.

To plot the variables, it is necessary to use a scatter plot. The regression line will show whether the associations can be interpreted as weak (distant from reality) or strong (likely to happen).

Do The Hypothesis Test

In the business world, it is hazardous to rely solely on intuition, as there is a risk that the manager will make wrong decisions that can have consequences that are difficult to reverse. Therefore, applying the hypothesis test, also called the T-test, is essential for checking whether a premise related to a data group is accurate.

During the statistical evaluation, the hypothesis test result is considered relevant only when it could not have occurred at random. Once done, it will be able to guide business decisions with greater precision.

Use Descriptive Analysis And Modeling Analysis

As is known, statistical analysis of data is structured through graphs and contingency tables. It turns out that these elements do not draw exact conclusions about the analyzed data. For that, one must resort to descriptive analysis and modeling analysis.

The description describes and summarizes the data, facilitating its visualization and interpretation. Modeling, on the other hand, is responsible for making statistical propositions, which may indicate:

  • estimates: values ​​that are close to a specific parameter;
  • confidence interval: extracts a dataset from a group of samples with effective parameters, demonstrating a high confidence level;
  • Prediction ranges represent a set of values ​​with a high value in the influential parameter.

Bet On Technology

Even for those who are used to dealing with data, doing a complex statistical analysis can be a headache, not to mention that manual operations are also subject to errors. In this sense, technology is indispensable to simplify the research and make it more accurate.

With the help of specific software for the statistical analysis of data, you can perform in-depth research with a high degree of accuracy. More than avoiding errors in calculations, state-of-the-art technological tools based on compatible methodologies facilitate and add security to data collection.

How Do You Organize And Interpret The Data?

The success of statistical analysis depends on two critical factors: the organization and interpretation of data. The organization takes place through stages. The first is to define which topic will be analyzed in the company, such as ROI. Next, it is time to choose the ideal method to collect, such as online surveys, polls, or even taking samples from the company’s database.

The third step consists of analyzing the collected data, which will give rise to the interpretation of data, transforming them into rich information for the development of strategies and improvements for business results.

When working with your database, keeping it organized is essential. First, you need to pay attention to the format in which the raw data should be stored. It is necessary to consider that the raw data are different from the processed data.

To avoid inconsistencies, the raw data should not be altered until they are treated, as this characterizes the destruction of the essence of the data. This factor modifies the interpretation of the information.

Also Read: Five Reasons Why Digital Marketing Is Best For Your Business

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