Linear Regression of Job Satisfaction

Linear regression plots a line between our data that minimizes the least squared difference between the data points and the regression line (Wooldridge 2009). This model allows us to generate estimates of the magnitude of impact of a one-unit increase in our independent variable on our dependent variable on average in the population of interest (Moore, McCabe Craig, 2009).Advertising We will write a custom essay sample on Linear Regression of Job Satisfaction specifically for you for only $16.05 $11/page Learn More It makes a few key assumptions, mostly that the individuals—and specifically, the residuals, or the distances between these data points and the line—are independently and identically distributed (Wooldridge 2009). If these assumptions are met, this approach is the best linear unbiased estimator. This generalized linear model is the basis for other statistical procedures, like ANOVA and t-tests (Trochim 2006a). We plan to analyze our data using this method of analysis to assess three research questions: how self-rated satisfaction on intrinsic, extrinsic, and overall job satisfaction scales, respectively, predicts satisfaction with employer benefits. Specifically, these variables are all continuous variables that measure how people rank their satisfaction on a range from 1 to 7. Association of Benefits and Intrinsic Job Satisfaction In order to assess the extent to which intrinsic job satisfaction predicts satisfaction with benefits, we can fit the following regression line: where benefits is our dependent variable (or â€Å"y†), represents the constant, or the intercept; represents the coefficient associated with the effect of a unit increase in the intrinsic score, and is the error term for each individual in the regression. Our results suggest that there is a small, positive, non-significant relationship between intrinsic satisfaction and benefits. Specifically, our intercept is 5.199 and the slop e of the line, or the one unit difference in the intrinsic score, is 0.033. In other words, a score of 0 on the intrinsic scale would be associated with a 5.2 (though this is out of the range of our data, since the scale does not go to 0), and a one unit increase in the intrinsic score would raise the benefits score, on average, by 0.032 points. While the intercept is significantly different from 0 (p0.001), the intrinsic variable is not significantly different than 0 (p=0.49). The correlation coefficient of this model, or the extent of the variation in the benefits outcome explained by theis model, is 0.016, which is quite small.Advertising Looking for essay on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Association of Benefits and Extrinsic Job Benefits In order to assess the extent to which intrinsic job satisfaction predicts satisfaction with benefits, we can fit the following regression line: where benefits is ou r dependent variable (or â€Å"y†), represents the constant, or the intercept; represents the coefficient associated with the effect of a unit increase in the extrinsic score, and is the error term for each individual in the regression. Our results suggest that there is a small, negative, significant relationship between extrinsic satisfaction and benefits. Specifically, our intercept is 6.35 and the slope of the line, or the one unit difference in the intrinsic score, is -0.19. In other words, a score of 0 on the extrinsic scale would be associated with a 6.4 (though this is out of the range of our data, since the scale does not go to 0), and a one unit increase in the extrinsic score would lower the benefits score, on average, by -0.19 points. The intercept and extrinsic score are both significantly different from 0 (p0.001. The correlation coefficient of this model, or the extent of the variation in the benefits outcome explained by this model, is 0.42, which is quite larg e. Association of Benefits and Overall Job Benefits In order to assess the extent to which overall job satisfaction predicts satisfaction with benefits, we can fit the following regression line: where benefits is our dependent variable (or â€Å"y†), represents the constant, or the intercept; represents the coefficient associated with the effect of a unit increase in the overall score, and is the error term for each individual in the regression. Our results suggest that there is a small, positive, non-significant relationship between overall satisfaction and benefits. Specifically, our intercept is 5.73 and the slope of the line, or the one unit difference in the overall score, is -0.13. In other words, a score of 0 on the overall scale would be associated with a 5.7 (though this is out of the range of our data, since the scale does not go to 0), and a one unit increase in the overall score would lower the benefits score, on average, by -0.13 points. While the intercept is si gnificantly different from 0 (p0.001), the overall variable is not significantly different than 0 (p=0.18).Advertising We will write a custom essay sample on Linear Regression of Job Satisfaction specifically for you for only $16.05 $11/page Learn More The correlation coefficient of this model, or the extent of the variation in the benefits outcome explained by this model, is 0.06, which is quite small. Comparing Results The results were markedly different with respect to the direction and magnitude of the effect of the satisfaction scales. For example, intrinsic had a very small, positive effect, though it was not significant, while the other two scales had a negative relationship. It might be that the extrinsic perceptions of satisfaction are inversely related with benefits—for someone who really likes their work, benefits matter less. However, for someone’s instrinsic satisfaction, benefits are positively associated—the intrinsic ly happier with the job, the happier with the benefits. However, it could also be that the direction of the intrinsic variable is due to chance. It wasn’t significantly different from 0 and could be a function of small sample size. The extrinsic regression produced a very high correlation coefficient, which further makes the point that its association with benefits satisfaction is strong. As mentioned earlier, it could be that extrinsic satisfaction and benefits are strongly correlated in a way that other factors are not necessary for explaining their effects. References Moore, D.S., McCabe G.P., Craig, B.A. (2009). Introductionto the practice of statistics.6th Ed.New York : W.H. Freeman. Trochim, W.R. (2006a). Research Methods Knowledge Base.  http://www.socialresearchmethods.net/kb/dummyvar.php Trochim, W.R. (2006b). Research Methods Knowledge Base.  http://www.socialresearchmethods.net/kb/genlin.phpAdvertising Looking for essay on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Wooldridge, J.M. (2009). Introductory Econometrics. 4th Ed. Mason, OH: South-Western Cengage. This essay on Linear Regression of Job Satisfaction was written and submitted by user Carter B. to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Choosing an I Essay Sample

Choosing an I Essay SampleOne of the most crucial parts of writing an I essay is choosing an appropriate essay sample. Some people prefer to choose a sample that was given to them by a college, while others choose one that is free to access on the Internet. Regardless of which you choose, you need to make sure that you learn as much as you can about this particular topic. It is the best way to find out what essay writers will expect and want from you, if not how much they are willing to pay for it.There are many sources that offer sample essays for almost any topic that you can think of. Usually these will cost money, but a lot of people don't mind paying for something that is of high quality. You should choose one that fits your level of knowledge.Although writing an I essay can be very difficult, especially if you do not have enough knowledge about the subject, you can still choose one of the many sample essays for your practice. This will let you know if you have chosen the right topic for your own essay. It will also let you know if you understand all of the material given in the essay.If you have already decided to write an essay about that topic, there are a couple of things that you need to do before you start writing. First of all, you need to choose a topic that you know a little bit about. You can choose it based on your own interests or those of the reader. The more information you can gather about a topic, the better.For some students, their coursework will give them plenty of information, but for others they can't get enough of it. Most good essay writers usually find themselves at a point where they need to write an essay, but they do not have enough information to begin. As long as you can supply them with enough information to begin, that will help them with their topic.When you do choose a sample essay, you will want to make sure that you check it carefully. You need to make sure that you read through it as often as possible, making notes. This will help you with your writing, since you will be able to remember where you came from and what the essay is actually about. A good essay writer will know that they are supposed to be writing about something that they know, so a note when reading a sample will be very helpful.Just remember that the more information you can gather, the better. You should not forget to take notes when doing your writing process, so that you can refer back to what you have learned and use it to improve your essays.