In this work, you only need to write the Results and Discussion sections instead of a full lab report(abstract, introduction and methods are not required).
In “How to write Lab Report.docx”, there is a Youtube link, this is a pretty good description of what to include in a lab report. Information about Results & Discussion can be found after about minute 12 in the video. You also can find another link, that is for Finding Interactions, This link contains similar information to that which I’ve provided in Factorial Designs but sometimes it can help to get the same information from different sources. This link provides overview of how main effects and interactions are revealed in line and bar graphs. Each plot depicts a 2 (A: A1, A2) x 2 (B: B1, B2) factorial design. The summary to the left of each plot indicates whether the data depict a main effect of A, and/or a main effect of B, and/or an interaction of AxB. You can also click the “View as Bar Graph” to toggle between seeing the same data depicted as a line graph or a bar graph.
In “How to Writing Results.pdf”, this is a document I created to help students understand how thinking about the structure of their design/analysis can help them write an organized description of their results.
In”Parcelling_OneWay_Results.pdf”, I present results for published research that used one-way designs (a relative rarity in memory research). I’ve used font colour-coding to draw your attention to the elements of a good Results section.
In”ParcelingResults.pdf”, I present results for published research that used one-way designs (a relative rarity in memory research). I’ve used font colour-coding to draw your attention to the elements of a good Results section.
In”Factorial Designs.pdf”,This is a document I created to further help you get your head around factorial designs and the distinction between main effects and interactions.
In”Calculating Means For Main Effects.pdf”, In a factorial experiment, you have one mean for each intersection of factors. For example in a 2×2 study, you have 4 means. These 4 means describe the interaction. But how can you use these means to describe the 2 main effects? In this document, I use a familiar non-research analogy to help you better get your head around this calculation.
In”Discussion Example.pdf”
This PDF shows a discussion section for a 3-experiment paper written by a former student in my lab, Chelsea Quinlan. It isn’t that this is a perfect example of a discussion. But I chose it because many of the components of a discussion that you learned about in Psyo2000 are represented in this example, as revealed by my annotations. Not all of these components will be relevant for your own papers but hopefully this will give you a sense of what you’re trying to achieve when writing a discussion.
A discussion is meant to walk the reader through an interpretation of the results (or through multiple potential interpretations, if applicable), justify the (preferred) interpretation, consider any short-comings that might limit strong conclusions or temper the conclusion (if applicable), and do all of this while placing the result in the context of the wider literature.
As you read the literature, try do do the same thing that I’ve done here, by paying attention to HOW the discussion is structured. This will make it easier for you to write your own discussions.
*ABOVE ALL ARE Supplementary materials TO HELP YOU TO WRITE A GOOD RD.
*In lab instruction & tables data.docx, you can find calculated data and tables about this experiment that need to be written, including the experiment’s background and the introduction. I have also uploaded the excel version of the experiment data.
*This lab repeated-measures design is a two-by-two (2×2). You should check the uploaded course material section about 2×2 experimental measurements to help with the writing.
In this work, you only need to write the Results and Discussion sections instead
Need help Working on This or a Similar Assignment?
We specialize in custom-written, original papers. No prewritten essays here—order your plagiarism-free and AI-free paper today for guaranteed originality.