probability

• a numerical measure of the likelihood that certain events will occur
• a null hypothesis is an assumption that there is no relationship in the population from which a sample is taken with respect to the variables being studied
• an alternative hypothesis is a testable statement about the relationship between two or more variables
• type 1 error occurs when a researcher rejects a null hypothesis that is true
• Type 2 error occurs when a researcher accepts a null hypothesis that is not true
• when it comes to chance, there is variability- researcher must decide if data collected is strong enough before rejecting the alternate hypothesis, even in a well-controlled experiment, there will always be some natural variability in the data collected- researchers use probability to minimise the chance that they reject the null and accept an alternative in error due to natural variability
• Type 1 error- researcher accepts alternate hypothesis (reject the null) in error, the data collected has passed the level of significance but the findings were due to chance variation, using P<0.05 means this will happen in around 1 to 20 studies