Consider the following model that relates the percentage of a household’s budget spent on milk MK to total expenditure TOTEXP, age of the household head AGE, and the number of children in the household NK. MK = ?1 + ?2ln(??????)+ ?3??+ ?4???+? This model was estimated using 1400 observations from Bahrain. An incomplete version of this output is provided in the following table. Regressor Coefficient Standard Error T-Ratio C 1.4515 2.2019 0.212 ln(??????) 2.7648 0.4842 2.206 ?? -1.4541 0.6395 -0.2141 ??? -0.1503 0.0235 -5.5214 Instructions: Interpret each of the estimates ?2 ,?3 ??? ?4
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.
Consider the following model that relates the percentage of a household’s budget spent on milk MK to total expenditure TOTEXP, age of the household head AGE, and the number of children in the household NK.
MK = ?1 + ?2ln(??????)+ ?3??+ ?4???+?
This model was estimated using 1400 observations from Bahrain. An incomplete version of this output is provided in the following table.
Regressor Coefficient Standard Error T-Ratio
C 1.4515 2.2019 0.212
ln(??????) 2.7648 0.4842 2.206
?? -1.4541 0.6395 -0.2141
??? -0.1503 0.0235 -5.5214
Instructions:
Interpret each of the estimates ?2 ,?3 ??? ?4
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