Research Methods- Probability and significance Flashcards
Probability -
A measure of the likelihood that a particular event will occur where 0 indicates statistical impossibility and 1 statistical certainty.
Significance -
A statistical term that tells us how sure we are that a difference or correlation exists. A ‘significant’ result means that the researcher can reject the null hypothesis.
Critical value -
When testing a hypothesis, the numerical boundary or cut-off point between acceptance and rejection of the null hypothesis.
Type I error -
The incorrect rejection of a true null hypothesis (a false positive).
Type II error -
The failure to reject a false null hypothesis (a false negative).
What is the null hypothesis (H₀)?
The null hypothesis states that there is no difference or no effect between the conditions being studied. For example, “There is no difference in the number of words spoken between participants who drink SpeedUpp and those who drink water.”
What is the significance level in psychological research?
The significance level is the threshold at which a researcher can claim a significant difference or correlation. The standard level in psychology is 0.05 (5%).
What is the alternative hypothesis (H₁)?
The alternative hypothesis predicts a difference or effect between the conditions. For example, “Participants who drink SpeedUpp will speak more words than those who drink water.”
What is the purpose of statistical testing in relation to hypotheses?
Statistical testing determines whether to accept or reject the null hypothesis based on the probability of the observed effect occurring by chance.
What does p ≤ 0.05 mean?
p ≤ 0.05 means there is a 5% or less probability that the observed effect occurred by chance, allowing the researcher to reject the null hypothesis.
Why can psychologists never be 100% certain about their results?
Psychologists cannot test every member of the population under all possible conditions, so there is always a chance (up to 5%) that results are due to chance.
What is a critical value in statistical testing?
The critical value is a number from statistical tables that the calculated value (from the statistical test) is compared to, to determine if the result is significant.
What are the three criteria for selecting a critical value?
- Whether the test is one-tailed (directional hypothesis) or two-tailed (non-directional hypothesis).
- The number of participants (N value) or degrees of freedom (df).
- The level of significance (usually p ≤ 0.05).
What is a one-tailed test?
A one-tailed test is used when the hypothesis is directional, predicting the specific direction of the difference or effect.
What is a two-tailed test?
A two-tailed test is used when the hypothesis is non-directional, predicting a difference or effect without specifying the direction.
When might a more stringent significance level (e.g., 0.01) be used?
A more stringent significance level (e.g., 0.01) is used in studies with potential human costs (e.g., drug trials) or in “one-off” studies that cannot be repeated.
What is a Type I error?
A Type I error occurs when the null hypothesis is rejected (and the alternative hypothesis accepted) when it should not have been, also known as a false positive or optimistic error.
What is a Type II error?
A Type II error occurs when the null hypothesis is accepted (and the alternative hypothesis rejected) when it should not have been, also known as a false negative or pessimistic error.
What increases the likelihood of a Type I error?
A Type I error is more likely if the significance level is too lenient (e.g., 0.1 or 10%).
What increases the likelihood of a Type II error?
A Type II error is more likely if the significance level is too stringent (e.g., 0.01 or 1%).
Why do psychologists favor the 5% significance level?
The 5% significance level balances the risk of making Type I and Type II errors, minimizing the chance of both false positives and false negatives.
