192 Chapter 4 Summarizing Bivariate Data 5. Energy effici ency: A sample of 10 households was monitored for one year. The household income (in $1000s) and the amount of energy consumed (in 1010 joules) were determined. The results follow. Income 31 40 28 48 195 96 70 100 145 78 Energy 16 40 30 46 185 98 94 77 115 67 a. Compute the least-squares regression line for predicting energy consumption from income. b. Construct a residual plot. Verify that a linear model is appropriate. c. If two families differ in income by $12,000, by how much would you predict their energy consumptions to differ? d. Predict the energy consumption for a family whose income is $50,000.
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.
How would I do part a?
How do I construct a residual plot for part b?
And how would I do part D?
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