C) if a country increases its life expectancy, the happiness index will increase or decrease d) if the life expectancy is increased by 4.5 years in a certain country .how much will the happiness index change? Round two decimal places e) use the regression line to predict that happiness index of a country with a life expectancy of 89 years . Round to two decimal places use the space below to type your answers
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.
C) if a country increases its life expectancy, the happiness index will increase or decrease
d) if the life expectancy is increased by 4.5 years in a certain country .how much will the happiness index change? Round two decimal places
e) use the regression line to predict that happiness index of a country with a life expectancy of 89 years . Round to two decimal places
use the space below to type your answers
Simple linear Regression: Simple linear Regression analysis is used to measures the association or linear relationship between two variables.Where one variable is (dependent or response variable) and Another variable is (independent or explanatory variable). Generally, Regression analysis is used to predicts the dependent variable based on the independent variable by using the following Regression equations
y= a + b*x
Where a is the intercept
b is the slope of the regression equation
y is the (dependent or response) variable
And x is the (independent or explanatory) variable.
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