ataset temperature is available here. The average January temperatures (y) and geographic latitudes (x) of 20 cities in the United States are given in the dataset. The regression equation for these data is ŷ = 126 − 2.34x. Use the regression equation given above to answer the following question. (a) What is the slope of the line? Interpret the slope in terms of how mean January temperature is related to change in latitude. The slope gives the average January temperature at the equator.The slope gives the average latitude of cities with an average January temperature is 0 degrees. The slope gives the average change in average January temperature for each one unit increase in latitude.The slope gives the average change in latitude for each one degree increase in the average January temperature. (b) Pittsburgh, Pennsylvania, has a latitude of 40, and Boston, Massachusetts, has a latitude of 42. Use the slope to predict the difference in expected average January temperatures for these two cities. Compare your answer to the actual difference in average January temperatures for these two cities using the data. (Use Boston − Pittsburgh.) The predicted difference in average January temperatures was . This indicates that the predicted average January temperature in Pittsburgh is than the predicted average January temperature in Boston. The actual average Janurary temperature in Pittsburgh is the average January temperature in Boston. Thus, the results . (c) Predict the average January temperature for a city with latitude 41.
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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