![]() For categorical data, the software uses descriptive statistics, and for continuous data, it uses linear regression, time-series, and many more. Statistical analysis software has the inbuilt features to identify the type of data it is processing, and based on it the software applies the required test. That is why continuous data is more important than the categorical one. It is the limitation of the categorical data, and that is why continuous data is required to give a clear view of the situation. He misses the point that the sales department will require more ice-cream in the months of May-July as it is a common fact that ice-cream sells more in Summer. He has categorized the production quantity from January to December equally. A production manager decides to divide the quantity of Ice-cream production month-wise equally. The statistical inference is that 20% of goods sold were returned. Continuous data can be analyzed for statistical inferences. If the company checks the revenue bills and finds that out of all its products, 6 million trolley bags were returned by customers in two years out of the 30 million sold, it means, the company is using the continuous data (variables of measurement) to derive at this conclusion. The problem with categorical data is that there is no mathematical meaning to it. This is an example of categorizing (discrete characteristics). A bag manufacturing company classifies its products into various categories.-Hand Bags, backpacks, trolley bags, ladies purse, wallet, etc. With categorical data, marketers may not find the relevant information required to make decisions. Statistical software has features to combat the common statistical errors related to categorical data analysis. A lot of data inaccuracies can creep in due to human errors. It is not possible for managers or statisticians to analyze the data manually. ![]() The scale at which businesses work today is quite large, and the data available is huge. They need something concrete to rely on while taking informed business decisions. Need for Statistical Analysis Software:īusinesses are constantly in search of statistics related to their fields. Statistical software is mostly used in quantitative research for data analysis. It can compare two or more data types to find statistical similarities or variations. It can apply multiple statistical tests and categorize data for finding unique readings. Statistical Analysis software is capable of integrating, analyzing, and interpreting a massive amount of data in a statistical framework. There is software that can analyze a huge amount of data for the final results. ![]() Fortunately, technology is there to provide relief to present-day businesses. However, collecting data and analyzing it for deriving statistical conclusions are not easy tasks. That is why statistics is important for making business decisions. Statistical analysis makes it easy for them by deriving conclusive figures that can help marketers to take important decisions. Here, statistical analysis comes to their rescue. Often marketers find themselves immersed in the flood of enormous data but no exact conclusion. “We are surrounded by data, but starved for insights.” -Jay Baer (American Author). Having Data does matter, but what you do with it matters more. Marketing Managers around the world have to take a lot of decisions every day based on the data available to them.
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