Professor Yema conducted a research to determine factors that influence environmental attitude. Table 1 below is a matrix of Pearson’s r correlation coefficients for the following variables used in the study: Environmental attitude (En), level of education (Le), and income (In). Table 1: Factors that influence environmental attitude ____________________________________________________________________ Variable En Le In ____________________________________________________________________ Environmental attitude (En) 1.0 Level of education (Le) 0.6** 1.0 Income (In) –0.3* 0.9*** 1.0 ____________________________________________________________________ ***Correlation is significant at .001 level; **correlation is significant at the .01 level (2-tailed); *correlation is significant at the .05 level (2-tailed) ***p<.001, *p<.05, **p<.01 Based on Table 1, formulate directional hypotheses showing the relationships between the following variables: Environmental attitude and level of education. Environmental attitude and income. Determine the extent to which variability in environmental attitude is explained by income. Determine the variance not explained between environmental attitude and income. Explain its significance. .
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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Professor Yema conducted a research to determine factors that influence environmental attitude. Table 1 below is a matrix of Pearson’s r
Table 1: Factors that influence environmental attitude
____________________________________________________________________
Variable En Le In
____________________________________________________________________
Environmental attitude (En) 1.0
Level of education (Le) 0.6** 1.0
Income (In) –0.3* 0.9*** 1.0
____________________________________________________________________
***Correlation is significant at .001 level; **correlation is significant at the .01 level (2-tailed); *correlation is significant at the .05 level (2-tailed)
***p<.001, *p<.05, **p<.01
- Based on Table 1, formulate directional hypotheses showing the relationships between the following variables:
- Environmental attitude and level of education.
- Environmental attitude and income.
- Determine the extent to which variability in environmental attitude is explained by income.
- Determine the variance not explained between environmental attitude and income. Explain its significance. .
- Outline a multivariate relationship between environmental attitude, level of education and income.
- Consider the following regression equation and other details:
y = 7.3 + 2.3x1 + 4.1x2 – 1.4x3 R2 = .78 F= 21.43, p<.01
where y = environmental attitude, x1 = level of education, x2 = income,
and x3 = trust in government.
How much of the variance in y (environmental attitude) is explained by x1, x2 and x3 ?
.
- Which of the three independent variables exhibits the largest effect on y?
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