A store manager wants to know the demand for a product as a function of the price. The table shows daily sales y for different prices x of the product. Price, x Demand, y $1.00 42 $1.20 37 $1.50 24 (a) Find the least squares regression line y = ax + b for the data by solving the system 3.00b + 3.70a = 103.00 3.70b + 4.69a = 122.40 for a and b. (Round all numerical values to two decimal places.) y = Use a graphing utility to confirm the result. (Round all numerical values to two decimal places.) y = (b) Use the linear model from part (a) to predict the demand when the price is $1.75. (Round your answer to the nearest whole number.) units
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.
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