Writing the Results Section in Psychology

In this video, I'm going to give you some advice on how to prepare the results section of your psychology lab report. The results section of your lab report will generally consist of three components. The first component is a treatment of results, and this is where you explain to the reader how your data was prepared for analysis. The second component is description. statistics and these are used to summarize your data and to identify any trends or patterns that might be emerging from your data. The third component is inferential statistics and these allow you to you to identify whether any of the trends or patterns in your data are statistically significant. In other words, whether any of your findings would not be expected from chance alone. Let's have a look at each of these components in turn and see how they work in practice. Turning to the treatment of results first, it's very important that you explain to the reader how your data has been prepared for analysis. And this includes covering things such as how have the scores for each of the variables in your study been derived and calculated? What have you done to identify and deal with any outliers in your data? What have you done about any missing data? If you've got a particularly involved study, or you're dealing with numerous hypotheses, it's often a good idea to use this section to outline to the reader how you're going to approach dealing with the results of your study. So let's have a look at how this works in practice. So here's the treatment of results section from our example lab report. You might want to pause the video at this point just to give yourself the chance to read the text in full. Press play when you're ready to continue. Of course, the treatment of results for this particular study was very straightforward. All the experimenter had to do was calculate the totals for each of the four permutations of the two variables that the study entailed, i.e. whether the participants crossed the right line or the wrong line. road alone or with an acquaintance, and whether they crossed when the red pedestrian, do not cross light, was illuminated or not illuminated. When you're reporting the treatment of results for a study more involved in the example lab report we've been referring to, it's very important that you take the reader through the process by which your data was prepared for analysis. So for example, what were the steps involved in the collation of the data? How did you score the data? Did the data need to be transformed to get it ready for statistical analysis? Also, did you need to exclude any data from the analysis? If so, you should explain why. Turning our attention now to descriptive statistics. Generally speaking, in a results section, you wouldn't be presenting all of your raw data. Rather, you'd be summarising that data using descriptive statistics. So things like frequencies. measures of central tendency such as the mean and measures of dispersion such as standard deviation. At this point you'd probably also be using tables and or figures as appropriate to illustrate your data. You'd also be commenting on any trends or patterns you were observing in your data having reviewed your descriptive statistics. So let's have a look at how that works in practice. Your descriptive statistics should begin with a summary of your results in words. But in doing this, there are a couple of principles of good practice you should be aware of. The first principle is that you need to make sure that you're not describing in your results aimlessly. In other words, you need to focus your description of your results in such a way that you're picking on the patterns or trends that are relevant to the research question that you've posed. that when you comment on any patterns or trends you observe in the data, it's important not to describe them as significant or not significant at this stage, because you've yet to do the inferential statistics that are necessary to determine whether said patterns or trends are significant or not statistically. The second principle of good practice is when you're providing a summary of your descriptive statistics. To always remember to include a reference to some method of business. visualizing the data at some point in your summary. You can see that being achieved here where the author is referring to table 1. When providing the visualization of your data, there are a few principles of good practice you want to bear in mind. The first principle is quite simply to make sure you are using the right kind of visualisation method for the data that you have. So to present the data for this particular study, using a table is perfectly appropriate and helpful. But the data for your study might call for a different method of data visualization to help the reader understand any trends or patterns that emerge from your descriptive statistics. For example, it might be better for you to use something like a bar graph. or maybe even a line graph. The second principle of good practice is to always make sure that any figures or tables that you include in your report have a nice clear title, which should always include a number and this is so you can easily refer the reader to your table or figure within the body of your text. The third principle of good practice you should bear in mind is that whenever you're using a table, you need to make sure that your rows and columns are clearly labelled. Similarly, when you're using a graph, you need to make sure that your graph axes are clearly labelled. The fourth principle of good practice is to ensure that whenever you use a table or a graph, you ensure that the way you present them and their layout and their design is as clear and uncluttered and easy to interrogate for the reader as possible. What you definitely want to avoid doing is simply copying and pasting the outputs from statistical packages like SPSS straight into your results section. Turning our attention to the inferential statistics now. The information you provide is going to depend on the particular inferential statistical analysis you happen to be running, but there are a few principles of good practice that you should bear in mind. The first is to explain to the reader what particular inferential test you're using and what that test is looking for. The second is to make sure that you report the results of that inferential statistical test in the right format. The third thing you need to bear in mind is to remember to state whether the results of your inferential statistical test support or refute your hypothesis. And lastly, you should always avoid simply copying and pasting the contents of the statistical package you happen to be using, for example SPSS, into your results section. Here's an extract from the Inferential Statistics part of the results section of our example lab report. There is a little bit of text on screen so you might want to pause the video at this point to give yourself the chance to read the text and press play when you're ready to continue. In looking at this passage of text, try not to fixate on the specific statistical test being used and instead focus on the three types of information that are being conveyed to the reader. The colour coding should help you out in this regard. Hopefully having read this passage, you'll have noted that there are three types of information being conveyed. In the white text, the author is explaining to the reader what type of inferential test was used, what it was looking for, and what the outcome of that test was in words. in the orange text the formal numerical result of the inferential test that was used is being reported in the correct format and in the green text the relationship between the results of the inferential test and the hypothesis that has been put forward for the study is clearly stated This is the kind of information that you need to provide when you come to writing the inferential statistics part of the results section for your own lab report. I hope you found the contents of this video useful. If so, please do hit the like button. If you haven't already, why not subscribe to my channel for more information about how psychology can help you study more effectively. Turn on the bell notification if you want to know when I post new content. Thanks very much.

statistics and these are used to summarize your data and to identify any trends or patterns that might be emerging from your data. The third component is inferential statistics and these allow you to you to identify whether any of the trends or patterns in your data are statistically significant. In other words, whether any of your findings would not be expected from chance alone.

Let's have a look at each of these components in turn and see how they work in practice. Turning to the treatment of results first, it's very important that you explain to the reader how your data has been prepared for analysis. And this includes covering things such as how have the scores for each of the variables in your study been derived and calculated?

What have you done to identify and deal with any outliers in your data? What have you done about any missing data? If you've got a particularly involved study, or you're dealing with numerous hypotheses, it's often a good idea to use this section to outline to the reader how you're going to approach dealing with the results of your study.

So let's have a look at how this works in practice. So here's the treatment of results section from our example lab report. You might want to pause the video at this point just to give yourself the chance to read the text in full. Press play when you're ready to continue. Of course, the treatment of results for this particular study was very straightforward.

All the experimenter had to do was calculate the totals for each of the four permutations of the two variables that the study entailed, i.e. whether the participants crossed the right line or the wrong line. road alone or with an acquaintance, and whether they crossed when the red pedestrian, do not cross light, was illuminated or not illuminated. When you're reporting the treatment of results for a study more involved in the example lab report we've been referring to, it's very important that you take the reader through the process by which your data was prepared for analysis. So for example, what were the steps involved in the collation of the data?

How did you score the data? Did the data need to be transformed to get it ready for statistical analysis? Also, did you need to exclude any data from the analysis? If so, you should explain why.

Turning our attention now to descriptive statistics. Generally speaking, in a results section, you wouldn't be presenting all of your raw data. Rather, you'd be summarising that data using descriptive statistics.

So things like frequencies. measures of central tendency such as the mean and measures of dispersion such as standard deviation. At this point you'd probably also be using tables and or figures as appropriate to illustrate your data. You'd also be commenting on any trends or patterns you were observing in your data having reviewed your descriptive statistics. So let's have a look at how that works in practice.

Your descriptive statistics should begin with a summary of your results in words. But in doing this, there are a couple of principles of good practice you should be aware of. The first principle is that you need to make sure that you're not describing in your results aimlessly. In other words, you need to focus your description of your results in such a way that you're picking on the patterns or trends that are relevant to the research question that you've posed. that when you comment on any patterns or trends you observe in the data, it's important not to describe them as significant or not significant at this stage, because you've yet to do the inferential statistics that are necessary to determine whether said patterns or trends are significant or not statistically.

The second principle of good practice is when you're providing a summary of your descriptive statistics. To always remember to include a reference to some method of business. visualizing the data at some point in your summary.

You can see that being achieved here where the author is referring to table 1. When providing the visualization of your data, there are a few principles of good practice you want to bear in mind. The first principle is quite simply to make sure you are using the right kind of visualisation method for the data that you have. So to present the data for this particular study, using a table is perfectly appropriate and helpful.

But the data for your study might call for a different method of data visualization to help the reader understand any trends or patterns that emerge from your descriptive statistics. For example, it might be better for you to use something like a bar graph. or maybe even a line graph. The second principle of good practice is to always make sure that any figures or tables that you include in your report have a nice clear title, which should always include a number and this is so you can easily refer the reader to your table or figure within the body of your text.

The third principle of good practice you should bear in mind is that whenever you're using a table, you need to make sure that your rows and columns are clearly labelled. Similarly, when you're using a graph, you need to make sure that your graph axes are clearly labelled. The fourth principle of good practice is to ensure that whenever you use a table or a graph, you ensure that the way you present them and their layout and their design is as clear and uncluttered and easy to interrogate for the reader as possible. What you definitely want to avoid doing is simply copying and pasting the outputs from statistical packages like SPSS straight into your results section. Turning our attention to the inferential statistics now.

The information you provide is going to depend on the particular inferential statistical analysis you happen to be running, but there are a few principles of good practice that you should bear in mind. The first is to explain to the reader what particular inferential test you're using and what that test is looking for. The second is to make sure that you report the results of that inferential statistical test in the right format. The third thing you need to bear in mind is to remember to state whether the results of your inferential statistical test support or refute your hypothesis.

And lastly, you should always avoid simply copying and pasting the contents of the statistical package you happen to be using, for example SPSS, into your results section. Here's an extract from the Inferential Statistics part of the results section of our example lab report. There is a little bit of text on screen so you might want to pause the video at this point to give yourself the chance to read the text and press play when you're ready to continue. In looking at this passage of text, try not to fixate on the specific statistical test being used and instead focus on the three types of information that are being conveyed to the reader.

The colour coding should help you out in this regard. Hopefully having read this passage, you'll have noted that there are three types of information being conveyed. In the white text, the author is explaining to the reader what type of inferential test was used, what it was looking for, and what the outcome of that test was in words.

in the orange text the formal numerical result of the inferential test that was used is being reported in the correct format and in the green text the relationship between the results of the inferential test and the hypothesis that has been put forward for the study is clearly stated This is the kind of information that you need to provide when you come to writing the inferential statistics part of the results section for your own lab report. I hope you found the contents of this video useful. If so, please do hit the like button. If you haven't already, why not subscribe to my channel for more information about how psychology can help you study more effectively. Turn on the bell notification if you want to know when I post new content.

Thanks very much.

Transcript for:Writing the Results Section in Psychology

Transcript for:
Writing the Results Section in Psychology