Chapter 9 Flashcards
Inferential Statistics
Statistical procedures designed to determine if differences and relationships found in sample data are sufficiently large that they can be assumed to be true at the population level
Degree of Uncertainty
All inferences from samples to populations involve a degree of uncertainty. The amount of uncertainty is determined by a number of factors, including sampling error and measurement error.
Measurement Error
This is differences in estimates of a population parameter based upon different testings of the same sample using the same instrument. These differences are the result of unreliability in our measurement instrument.
Sampling Error
This is the differences in estimates of a population parameter based upon different samples drawn from the same population. If the samples were randomly drawn and all of the same size, the amount of error (at a certain probability level) can be calculated.
Null Hypothesis
There is no difference between the groups (or the difference is in the unpredicted direction)
Alternative Hypothesis
There is a difference between the groups (or the difference is in the predicted direction)
level of significance
also known as a level
If the _____________ would have generated the sample statistic less often by chance than the a level, the researcher rejects the ______ and affirms the alternative.
null hypothesis, null
Type I Error
Rejecting the null when it is in fact true
Type II Error
Failing to reject the null when it is in fact false
Difference between group means
larger differences make it easier to achieve significance, all other things being equal
Sample size (N)
larger sample sizes reduce sampling error and make it easier to achieve significance, all other things being equal
Reliability of the instruments
more reliable instruments reduce measurement error, and make it easier to achieve significance, all other things being equal
Confidence Intervals
An interval within which we believe the true population parameter falls, at a given level of confidence (usually 95% or 99%)
Effect Size
Statistical significance answers the question, “Are the results likely to be due to sampling error?”