Year 1 2 3 4 5 7 8 Sales (in $100,000) U.S. births (in millions) 6.1 6.4 8.3 8.8 3.1 5.1 3.8 9.2 2.8 7.3 4.2 12.5 3.7 2.9 3.4 3.5
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Baby It’s You, a maker of baby foods, has found a high
a. Assuming that U.S. births represent the independent variable and sales the dependent variable, determine a regression equation for predicting sales based on births. Use years 2 through 8 as your baseline.
b. Suppose that births are forecasted to be 3.3 million in year 9. What forecast for sales revenue in year 10 do you obtain using the results of part (a)?
c. Suppose that simple exponential smoothing with a = .15 is used to predict the number of births. Use the average of years 1 to 4 as your initial forecast for period 5, and determine an exponentially smoothed forecast for U.S. births in year 9.
d. Combine the results in parts (a), (b), and (c) to obtain a forecast for the sum of total aggregate sales in years 9 and 10.
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