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- Inferential statistics are used to determine whether we can, in fact, make statements that the
results reflect what would happen if we were to conduct the experiment again and again with
- The null hypothesis is simply that the population means are equal – the observed difference is
due to random error.
- The research hypothesis is that the population means are, in fact not equal.
- DIFFERENCE: The null hypothesis states that the independent variable had no effect, the
research hypothesis states that the indepedent variable did have an effect.
- In the aggression modeling experiment, the null and research hypothesis are:
o H0(null hypothesis): The population mean of the no-model group is equal to the
population mean of the model group
o H1(research hypothesis): TH epopulation mean of the no-odel group is not equal to the
population mean of the model group.
- Statistical significance – a significant result is one that has a very low probability of occuring if
the population means are equal.
- Probability is the likelihood of the occurence of some event or outcome
- ESP (Extrasensort perception ability) in the case of probability
o A card that is presented with different symbols. In your experiment, lets say you have 10
trails each of the five cards is presented two in randomn order. So literally your task is
for you to know whether you friends answer is randomn eroor or they are indicating
something more than the randomn error occuring.
Hence the research hypothesis is that number of correct answrs shows more
than radomn or chance guessing.
o Lets say according to the experiment, two correct answers are expected under the null
o Lets say the participant gets three right then you can conclude its randomn guessing,
because the experimenter would recognize that there is a high probablility that your
participant will get 3 correct.
o If there is 7 right then you can conclude it is more than randomn guessing.
- The probability required for significance is called the alpha level
- NOTE: The sampling distribution is based on the assumption that the null hypothesis is true.
- To use this distribution or to evaluate our data, we need to calculate our data, we need to
calculate a value of t from the obtained data and evaluate the obtained t in terms of the
sampling distribution of t that is based on the null hupothesis. If the obtained t has a low
probability of occurence (0.05 of less) then the null hypothesis is rejected.