Section 1: A study was conducted to explore factors affecting the annual income of Australian adult workers. The researchers proposed that people with more years of tertiary education would have higher annual incomes. They also suggested that older people would have higher annual incomes. Finally, they suggested that males would have higher annual incomes than females. A multiple regression was performed on this data with income as the dependent variable. Three predictors were included in the model: age, years of tertiary education and sex (male/female). The intercorrelations between the variables are given in Table 1, and the regression statistics are given in Table 2.

Table 1: Intercorrelations among the variables

	Income	Age	Year T.Edu
Age	.43***
Year T.Edu	.77***	.44***
Sex	-.06	-.04	-.02

Note: *p < .05, **p < .01, ***p < .001; N = 150

Sex coded as 0 = male, 1 = female

Table 2: Results of regression for workers, with income as the DV

Variable	Squared part correlations	Partial correlations	Stand. regression coefficient
Age	.09	.15	.11
Year T.Edu	.65	.72	.73***
Sex	-.04	-.06	-.04
	R = .61***

Note: *p < .05, **p < .01, ***p < .001; N = 150

Sex coded as 0 = male, 1 = female

Question 1:

Identify one error (there can be more than one) and comment on what should have been written instead (you will have to run an analysis on the data yourself to check). Note: the error that you need to identify in each section is NOT associated with format or grammatical errors.

Please use the below format to answer.

Error:

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Section 2 - QUESTION 2

As can be seen from Table 1, only sex was not significantly correlated with income. There were, however, significant positive relationships between income and the other predictors. People with more years of tertiary education tend to have higher annual incomes, as did younger workers.

Error:

Why it is an error:

Change to: