![amos version 23 citation apa amos version 23 citation apa](https://www.cairn-int.info/vign_rev/E_AFCO/E_AFCO_269.jpg)
Residual (Standardised Residual) subheading. Look at the Minimum and Maximum values next to Std. Scroll through your results until you find the box headed Residual Statistics. If we have any they will need to be dealt with before we can analyse the rest of the results. The first thing we need to check for is outliers.
Amos version 23 citation apa how to#
As the assumption of non-zero variances is tested on a different screen, I will leave explaining how to carry that out until we get to it. This will allow you to check for random normally distributed errors, homoscedasticity and linearity of data. Then, under the Standardized Residual Plots heading, tick both the Histogram box and the Normal probability plot box. Move the option *ZPRED into the X axis box, and the option *ZRESID into the Y axis box. Click Continue and then click the Plots button. This will allow us to check for independent errors. Under the Residuals heading also tick the Durbin-Watson check box. This, unsurprisingly, will give us information on whether the data meets the assumption of collinearity. Tick the box marked Collinearity diagnostics. Click Continue and then click the Statistics button. This will allow us to check for outliers. Click this and then tick the Standardized check box under the Residuals heading.
![amos version 23 citation apa amos version 23 citation apa](https://cms.bibliography.com/wp-content/uploads/2020/01/Guide-in-text-citations-Turabian.png)
On the Linear Regression screen you will see a button labelled Save. Information on how to do this is beyond the scope of this post. Note: If your data fails any of these assumptions then you will need to investigate why and whether a multiple regression is really the best way to analyse it. But before we look at how to understand this information let’s first set SPSS up to report it. These assumptions deal with outliers, collinearity of data, independent errors, random normal distribution of errors, homoscedasticity & linearity of data, and non-zero variances. There are seven main assumptions when it comes to multiple regressions and we will go through each of them in turn, as well as how to write them up in your results section. We now need to make sure that we also test for the various assumptions of a multiple regression to make sure our data is suitable for this type of analysis. We are going to use the Enter method for this data, so leave the Method dropdown list on its default setting. Next move the two Independent Variables, IQ Score and Extroversion, into the Independent(s) box. The first thing to do is move your Dependent Variable, in this case Sales Per Week, into the Dependent box. In SPSS you need to click Analyse > Regression > Linear and you will get this box, or one very much like it depending on your version of SPSS, come up. However, I will show you how to calculate the regression and all of the important assumptions that go along with it. Now I am not going to show you how to enter the data into SPSS, if you don’t know how to do that I recommend you find out first and then come back. We want to see if IQ level and extroversion level can be used to predict the amount of money made in a week. Here we have a list of sales people, along with their IQ level, their extroversion level and the total amount of money they made in sales this week. Here is some that I pulled off the internet that will serve our purposes nicely. If you have no interest in statistics then I recommend you skip the rest of this post. So after two weeks of wading through websites, texts book and having multiple meetings with my university supervisors, I thought I would take the time to write up some instructions on how to report multiple regressions in APA format so that the next poor sap who has this issue doesn’t have to waste all the time I did. Sure I came across the odd bit of advice here and there and was able to work a lot of it out, but so many of the websites on this topic leave out a bucket load of the information, making it difficult to know what they are actually going on about. I am writing this because I have just spent the best part of two weeks trying to find the answer myself without much luck. So this is going to be a very different post from anything I have put up before.