The following graph shows the percentage of U.S. residents who used the Internet at home in 2010 as a function of income (the data points) and a logistic model of these data (the curve).t 100 90 80 70 e 60 50 40 30 20 10 20 40 60 80 100 120 140 Household income ($1,000) The logistic model is given by 86.2 P(x) = 1+ 2.49(1.054)-x percent where x is the household income in thousands of dollars. (a) According to the model, what percentage of extremely wealthy people used the Internet at home? (Round your answer to one decimal place.) 86.2 (b) For low incomes, the logistic model is approximately exponential. Which exponential model best approximates P(x) for small x? (Round numeric values to four significant digits.) P(x) = 24.7(1.054)* (c) According to the logistic model, 46% of individuals with what household income used the Internet at home in 2010? (Round the answer to the nearest $1,000.) $21000 X U.S. Residents using Internet (%) +++
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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