Number, x 100 120 140 Percent, y 75 68 55
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.
A wildlife management team studied the reproduction rates of deer in three tracts of a wildlife preserve. The team recorded the number of females x in each tract and the percent of females y in each tract that had offspring the following year. The table shows the results.
(a) Find the least squares regression line for the data.
(b) Use a graphing utility to graph the model and the data in the same viewing window.
(c) Use the model to create a table of estimated values for y. Compare the estimated values with the actual data.
(d) Use the model to estimate the percent of females that had offspring when there were 170 females.
(e) Use the model to estimate the number of females when 40% of the females had offspring.
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