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11 Cards in this Set
- Front
- Back
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What is an alternative hypothesis? why? |
-A directional or non directional hypothesis -Because it is the alternative to the null hypothesis |
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What does the null hypothesis state? Give an example. |
-That there is no difference between the conditions -There is no difference in the amount of words a child speaks in five minutes after they've drunk 300ml of red bull to when they've drunk 300ml of water. |
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What does the statistical test determine? |
Which hypothesis is true and thus whether we accept ot reject the null hypothesis. |
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What is the level of significance is psychology and what does this mean? |
-0.05 / 5% -The probability that the observed effect (result) occured by chance is equal to or less than 5%. -When a researcher claims to have found a significant difference/correlation there's still up to 5% chance that the result is a fluke. -Psychologists can never be 100% certain about a particular result as they have not tested all members of the population under all possible conditions; prepared to accept that results may have occured by chance |
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Decribe the critical value: |
-The calculated value in compared to the critical value to check for statistical significance telling us whether or not we can reject the null hypothesis and accept the alternative hypothesis. |
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What is the rule of R? |
Statistical tests with the letter 'R' in the name are those where the calculated value must be equal to or more than the critical value to show significance. Tests without; the calculated value must be equal to or less than the critical value for significance. |
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What are the three criteria for knowing which critical value to use? |
1. One or two tailed test? One tailed= directional hypothesis, Two tailed= non directional hypothesis -Probability levels double in two tailed tests as they are a more conservative prediction 2. The number of participants in the study = N -For some tests degrees of freedom are calculated instead= (df) 3. The level of significance = p - 0.05 is the standard level |
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When is 0.01 used as the significance level? |
-In studies where there may be a human cost for example in drug trials or one off studies that could not, for practical reasons, be repeated in the future. -If there is a large difference between the calculated and critical values in the preferred direction the researcher will check more stringent levels; lower the p value is the more statistically significant the result is. |
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How are type I and type II errors possible? |
Reserchers can never be 100% certain they have found statistical significance so it is possible (up to 5% possible) that the wrong hypothesis may be accepted. |
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What is a Type I error? |
-When the null hypothesis is rejected and the alternative hypothesis is accepted when in fact the null hypothesis is actually true. -Optimistic error/ false positive -Researcher claims a significant difference or correlation when there isnt one -More likely if the significance level is too high (0.1) |
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What is a Type II error? |
-When the null hypothesis is accepted and the alternative hypothesis is rejected when in fact the alternative hypothesis is true. -Pessimistic error/ false negative -Researcher believes there is no difference or correlation when there is one. -More likely is the significance level is too low (0.01) as potentially significant values may be missed. |
