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Running head: Linear Regression Exercise Linear Regression Analysis Name: College: Course: Date: 1) The total sample size was 378 2) The mean income is $1,485.49 and mean number of hours worked is 33.52 3) The correlation coefficient between the outcome and the predictor variables is 0.3.It is statistically significant at P< 0.001 because it falls between the range of 0-1.The association is positively correlated implying that it is directly proportional.

4) The coefficient of determination(R squared) is 0.09 it is statistically significant at P<0.001.This value means that 9% of the variation is related. Generally, the coefficient of determination (R square) is equal to the variation percent in one variable that is related to the variation in the other. 5) The standard error interpretation: In any mean, it is normally observed that every sample taken to estimate the unknown population parameter will always underestimate or overestimate the mean by certain amount (Bryman and Cramer, 1990). But interesting, as seen here, even if the population is not normally distributed, the distribution of these sample means will be normally distributed itself. According to the central limit theorem, the sampling distribution mean of the mean will be the unknown population means (Field, 2005). The sampling distribution standard deviation of the mean is referred to as the standard error. This is another standard deviation, it is referred to as standard error which is the standard deviation of the sample means instead of the raw data standard deviation. The data standard deviation is the average distance values are from the mean (Howell, 1992). ...

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