QUESTION 3 Suppose you wish to see if there is a relationship between the price (units-$1000) and the rating (units=10 points) of laptop computers tested by Consumer Reports. A regression analysis on 15 computers revealed Ex = 21.00, Ex = 33.30, Eyj = 119.40, Ey²; = 956.14, and Exy = 171.57. What is the interpretation of B1? O a. For an increase of 10 points in the Consumer Report rating, the mean price of a laptop increases by $771.5185. O b. For an increase of $1000 in price, the mean Consumer Report rating increases by 11.3077 points. OC. For an increase of 10 points in the Consumer Report rating, the mean price of a laptop increases by $113.0768. O d. For an increase of $1000 in price, the mean Consumer Report rating increases by 1.1308 points. O e. None of the answers is correct
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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