Linear regression models are statistical techniques used to determine the apparent relationship between two variable. It is built upon three techniques including scatter diagrams, line of best fit and correlation or extrapolation

Key Terms

Correlation is used to determine the relationship between data sets. It is a statistical process of establishing a relationship (or connection) between two or more variables.

Extrapolation is a sales forecasting technique that makes future predictions of sales (in units or dollars) based on correlations and trends identified from using past data.

The line of best fit is a linear line used to represent the best approximation of a scatter graph of different data points. It is used to study the nature of the relationship between two variables.

Identify underlying relationships.
Indicate the strength of correation.
Approximates the trend in data set.

A scatter diagram is a visual statistical tool used to show the relationship or correlation between two variables, such as marketing expenditure and sales revenues.

Market research could be performed.
Uses: Show patterns (correlation) and communicate visually.
Limitation: Does not reveal causation.

Negative correlation exists if the values of one variable in a data set increases whilst the values of another variable in the data set decreases.

Positive correlation exists if the values of both variables in a data set move in the same direction.

Time series analysis is a statistical technique used to identify trends in historical data, such as the figures for a firm’s monthly sales revenues.

Advantages of simple linear regression	Disadvantages of simple linear regression
Predictive analytics: Prepare for risks and opportunities. Forecast future outcomes.	Cause versus effect: Correlation does not establish correlation between 2+ variables.
Enhance decision-making: Enable greater levels of accuracy and trustworthiness, thus, supporting business strategies.	Time consuming and expensive to conduct.
Reveals new business opportunities: Enable business to gain new insights.	Large and representative data is needed to generate meaningful results.
Reduce errors and risk associated with business strategy: Enables business to test theories and strategies to see if they are successful or not based on evidence rather than intuitions and experiences.	Sensitive to outliers: Outliers can drastically deviate the data and line of best fit wich results in lower degree of accuracy
Improved management: Manage resources in businesses more efficiently.	Past is not indicative of the future.