Question

3. From a paddy field, 36 plants were randomly selected. Panicle lengths and number of grains per panicle were recorded. The researcher chose to examine the relationship between the two variables using Regression Analysis. Was this an appropriate statistical tool for the purpose? If not, why not and what alternative would you suggest and why?

Answer 1

Dear student, please comment in the case of any doubt and I would love to clarify it.

Regression analysis is all about data. It helps businesses understand the data points they have and use them – specifically the relationships between data points – to make better decisions, including anything from predicting sales to understanding inventory levels and supply and demand. Of all the business analysis techniques, regression analysis is often referred to as one of the most significant. One business analyst puts it this way:

“Most companies use regression analysis to explain a phenomenon they want to understand (e.g. why did customer service calls drop last month?); predict things about the future (e.g. what will sales look like over the next six months?); or to decide what to do (e.g. should we go with this promotion or a different one?)”

In this case, regression analysis can be used to find the relationship between panicle lengths and the number of grains per panicle.

Other than just finding the relationship between those variables, regression analysis can be used for-

1. Understanding other patterns

2. Correcting errors

3. Optimizing processes

Understanding the relationships between business happenings and other variables can be exceedingly important to make sure your business is prepared and effective. That’s why regression data analysis in business is a key component to making sound decisions at just about every level of business.