Spacecraft Weight (lb) Cost ($ million) i Xi Yi 1 400 278 530 414 3 750 557 4 900 689 5 1,130 740 1,200 851
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.
While cleaning out an old file, someone uncovers the first spacecraft manufactured by your company—30 years ago! It weighed 100 pounds and cost $600 million. Extend the spreadsheet to include this data point. How does adding this observation affect R and the standard error? How about the regression coefficients? Should this new data point be included in the model used for predicting future costs? (see Given below)
In the early stages of design, it is believed that the cost of aMartian rover spacecraft is related to its weight. Cost and weight data for six spacecraft have been collected and normalized and are shown in the given attached table. A plot of the data suggests a linear relationship. Use a spreadsheet model to determine the values of the coefficients for the CER.
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