Assumptions
A characteristic that we ideally require the population from which we are sampling to have so that we can make accurate inferences
Parametric Test
An inferential statistical analysis based on a set of assumptions about the population
Nonparametric Test
An inferential statistical analysis that is not based on a set of assumptions about the population
Robust Hypothesis Test
One that produces fairly accurate results even when the data suggest that the population might not meet some of the assumptions
Critical Value
A test statistic value beyond which we reject the null hypothesis; often called the cutoff
Critical Region
Refers to the area in the tails of the comparison distribution in which we reject the null hypothesis if our test statistic falls there
P Level
The probability used to determine the critical values in hypothesis testing; often called alpha
Statistically Significant
A finding where if the data differ from what we would expect by chance if there were, in fact, no actual difference
One Tailed Test
A hypothesis test in which the research hypothesis is directional, positing either a mean decrease of a mean increase in the dependent variable, but not both, as a result of the independent variable
Two Tailed Test
A hypothesis test in which the research hypothesis does not indicate a direction of the mean difference or change in the dependent variable, but merely indicates that there will be a mean difference
Point Estimate
A summary statistic from a sample that is just one number used as an estimate of the population parameter
Interval Estimate
Based on a sample statistic and provides a range of plausible values for the population parameter
Confidence Interval
An interval estimate, based on the sample statistic, that would include the population mean a certain percentage of the time if we sampled from the same population repeatedly
Effect Size
Indicates the size of a difference and is unaffected by sample size
Cohen's d
A measure of effect size that assesses the difference between 2 means in terms of standard deviation, NOT standard error
P-rep
The probability of replicating an effect given a particular population and sample size
Statistical Power
A measure of our ability to reject the null hypothesis given that the null hypothesis is false
Meta-Analysis
A study that involves the calculation of a mean effect size from the individual effect sizes of many studies
File Drawer Analysis
A statistical calculation, following a meta-analysis, of the number of studies with null results that would have to exist so that a mean effect size is no longer statistically significant
t Statistic
Indicates the distance of a sample mean from a population mean in terms of the standard error
Single Sample t Test
A hypothesis test in which we compare data from one sample to a population for which we know the mean but not the standard deviation
Degrees of Freedom
The number of scores that are free to vary when estimating a population parameter from a sample
Dot Plot
A graph that displays all the data points in a sample, with the range of scores along the x-axis and a dot for each data point above the appropriate value
Paired Sample t Test
Used to compare 2 means for a within-group design, a situation in which every participant is in both samples; also called a dependent-samples t test
Order Effects
Refer to how a participants behavior changes when the dependent variable is presented for a second time, sometimes called practice effects
Counterbalancing
Minimizes order effects by varying the order of presentation of different levels of the independent variable from one participant to the next
Independent Samples t Test
Used to compare 2 means for a between-groups design, a situation in which each participant is assigned to only one condition
Square Root Transformation
Reduces skew by compressing both the negative and positive sides of a skewed distribution