For the first week back writing blogs I have decided to go with hypothesis testing, a nice topic to get back into the swing of things. So, for this blog I’ll define what hypothesis testing is, then talk about the steps giving examples as I go.
What is a hypothesis test? Well basically a hypothesis test is a method used in statistics whereby data is collected from a sample to evaluate a hypothesis about a population. Obviously we can not sensibly test an entire population (well not usually) and so we have to use samples which can bring issues with them.
Four Step Procedure
There are four main steps in the hypothesis testing procedure and I will briefly mention all here. One thing we must remember when hypothesis testing is that, statistically, we test the null hypothesis not the experimental hypothesis.
To demonstrate the hypothesis testing procedure I’m going to use Loftus and Palmer’s (1974) study of eyewitness testimony. For anyone who isn’t sure what this study did I’ll briefly describe it…
Participants were assigned to different conditions and all viewed a slideshow of a head on collision between two cars. They were then asked questions such as “how fast were the two cars going when they hit?” In some conditions the verb “hit” was replaced by “smashed”, “collided”, “bumped” or “contacted”. (The findings are displayed below.) For more information on Loftus and Palmers (1974) study have a look at this http://www.simplypsychology.org/loftus-palmer.html it goes into a lot more detail than I will here.
- Firstly, we need to state our hypothesis about the intended population. So using the Loftus and Palmer example; it was hypothesized that: the language used when questioning eyewitnesses can alter memory (with the null hypothesis being that: the language used when questioning eyewitnesses will have no effect on memory).
- We must then use our hypothesis to make predictions about a sample, such as its particular characteristics. So if our hypothesis is that the language used when questioning eyewitnesses can alter memory we are suggesting that the memory of people in the general population will be affected by the language used in eyewitness testimony and therefore we should see that in our sample. REMEMBER: our sample should be similar but may not be exactly the same as the greater population.
- Next we need to select our sample. To do this we should aim to sample individuals randomly from the population. We should use as random a sample as possible to try and avoid biases in participants (e.g. we don’t want to end up with a sample full of individuals who are very similar as this may not reflect the general population). Loftus and Palmer used a sample of n=45 American students, who were more of an opportunity sample than a random sample and this may therefore affect the generalisability of the results. It is not always possible to use a random sample and so we must be aware of that when testing a hypothesis as different samples have different limitations.
- And finally we compare the data we have collected from our sample with our hypothesis. If we find that our data are consistent with the predictions made by our hypothesis then we can assume that our hypothesis is good and we should reject the null hypothesis. However if we find that our data are inconsistent with the hypothesis then we must conclude that our hypothesis is not correct and we will fail to reject the null hypothesis. Loftus and Palmer found that the speed judged by participants increased significantly from approximately 32mph when the verb “contacted” was used compared to approximately 41mph when it was replaced by “smashed”. As their results were significant we can confidently reject the null hypothesis. (This link shows a graph that represents the results from the study: http://www.simplypsychology.org/loftus-results.jpg)
Next week I will carry on with the general theme of hypothesis testing and go into more detail about samples and the various strengths and weaknesses of different samples and methods used for testing a hypothesis.