Correlation & regression analysis
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This document discusses correlation and regression analysis to forecast sales for Pizza Hut in Pune, India. It provides background on the company and variables that could influence sales such as number of delivery boys, advertising spend, number of outlets, pizza varieties, and competitor activity. It defines correlation as any statistical relationship between random variables and notes correlation analysis examines whether relationships are positive or negative. Regression analysis estimates the relationship between dependent and independent variables and can be used for prediction, understanding variable relationships, and identifying causal relationships. Methods discussed are linear and ordinary least squares regression.
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- 1. Correlation & Regression Analysis Anubhab Tiwari &Arjama Mukherjee Core-marketing
- 2. SCPS model Sector Product Company Area of operation Population Foods & beverage Pizza Pizza hut Pune, Koregaon park 2 lakh [Source : Plazacentre.in]
- 3. Why research methodology ? Helps in providing information to assist managers to make better decisions Helps in demand forecasting Helps in new product development
- 4. Forecast sales of pizza hut Pizza Hut in Pune, Koregaon park desires to build a practically implementable Sales forecasting model that would enable the firm to forecast Sales territory-wise , month-wise based on the following Causative variables : Number of Delivery boys Advertising Spend Number of Outlets Pizza varieties served Competitor Activity (1= V Low; 5= V High) Customer base for Home deliveries
- 5. Correlation analysis • In statistics, dependence is any statistical relationship between two random variables or two sets of data. • Correlation refers to any of a broad class of statistical relationships involving dependence
- 6. Steps in Correlation analysis • Fits the straight line data • Weather the slope is negative or positive • Quality of fit Scatter along the y axis Scatter along the fitted line
- 9. Regression analysis • Statistical process for estimating the relationship among variables • The focus is on the relationship between a dependent variable and one or more independent variables • It shows that how a changes in independent variable varies the typical value of the dependent variables which is held fixed • It estimates the conditional expectation of the dependent variable given in the independent variable
- 10. Uses of regression analysis • Prediction and forecasting • Helps in understanding which among the independent variables are related to the dependent variable • Casual relationship between the independent and dependent variables
- 11. Methods of regression analysis • Linear regression: Refers to any two models where the increasing or decreasing any model n times will cause a corresponding increase or decrease of n times in the other variables too. • Ordinary least square regression : Where doubling one variable will not double the other variable.
- 12. Thank You