PYB110 Exam Revision Notes - Week 7

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Queensland University of Technology

PYB110 Week Seven Revision Notes Two Types of Hypotheses  Research Hypothesis o There has been demonstrated a relationship or effect between the two variables. o Also known as alternative hypothesis.  Null Hypothesis o There is no relationship or effect demonstrated between the two variables. We need to make an educated decision based on our results as to which hypothesis is more likely to be the case. At some point, we need to determine when our data is too unusual for it to be a coincidence and thus disprove the null hypothesis. Thus, a convention exists across most scientific research that if the probability of a score occurring is less than 5% (p < .05) then we interpret it as not occurring by chance. However, if we acknowledge that a result is significant at p < .05 then we are also acknowledging that we have a 5% chance of being incorrect in our decision. Just because something is improbable, does not make it impossible. Hypothesis Testing  Hypothesis testing is a systematic procedure for determining whether the results of an experiment (which examines a sample) provide support for a theory which applies to a population.  We always assume that the null hypothesis is correct and then try to disprove this by showing that the chance of no effect between the variables is unlikely. The process of hypothesis testing is as follows: 1. Formulating research and null hypotheses a. Think about the topic of research and formulate a hypothesis for both possible outcomes. b. µ e µ nethis is the research hypothesis. c. µ e µ ne this is the null hypothesis d. These statements are mutually exclusive – that is, it can only be one or the other. 2. Identifying the comparison distribution a. We now test the sample data against the distribution with the null hypothesis assumed. 3. Determining the cut-off score a. Before we begin collecting data we need to determine a cut-off score to reject the null hypothesis. This is often referred to as the critical value. b. When dealing with IQ, the cut-off is typically 2% (IQ of 132). A cut-off of 1% is used when you need to be very thorough. c. Typically the cut-off for scientific research is 5% which is written as p < .05. This is known as the significance level. d. When the obtained score exceeds the critical value we can reject the null hypothesis and have a statistically significant result. 4. Where does your sample scor
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