Vocab Flashcards
Confidence Interval:
interval or range of values centered around a sample statistic. The logic behind a confidence interval is that a sample statistic, such as sample mean should be relatively near to the corresponding population parameter.
ANOVA
Hypothesis testing procedure that is used to evaluate mean differences between two or more treatments (or populations)
F-ratio
test statistic for analyses of variances; compares differences (variance) between treatments w/ differences that are expected.
F-distribution
all possible F values when Ho is true
Logic of Anova
B(variance)/W(variance)=F
Within group variance
difference that exists inside each treatment condition
between group variance
value used to measure and describe between treatments mean differences
Independent Variable:
manipulated by the researcher
Levels of Independent Variable:
2 levels. The two different situations, environments, etc.
Dependent Variable:
What is being measured.
- Normal Distribution:
The mean, median, and mode of a normal distribution are equal and defined by two parameters, the mean (μ) and the standard deviation (σ).
- Probability of Occurrence:
For a situation in which several different outcomes are possible, the probability for any specific outcome is defined as a fraction or a proportion of all the possible outcomes. If the possible outcomes are identified as A, B, C, D, and so on, then Probability of A = #of outcomes classified as A/ Total # of possible outcomes
- Statistical Significance:
it is very unlikely to occur when the null hypothesis is true. That is, the result is sufficient to reject the null hypothesis.
- Significant Difference:
when p < .05
- Null Hypothesis:
states that in the general population there is no change, no difference, or no relationship. In the context of an experiment, predicts that the independent variable (treatment) has no effect on the dependent variable (scores) for the population.
- Research Hypothesis:
your prediction on what you believe the difference to be.
- Directional Hypothesis:
Predicting direction of the difference.
- Non-Directional Hypothesis
: Predict difference, but no direction. Ex. “This group will score different than the other”
- Reference Distribution:
used if deviations of the estimated parameter in either direction from some benchmark value are considered theoretically possible
- One-Tailed Test:
used if only deviations in one direction are considered possible
- Two-Tailed Test:
used if deviations of the estimated parameter in either direction from some benchmark value are considered theoretically possible
- Critical Region:
It is the area, or areas, of the sampling distribution of a statistic that will lead to the rejection of the hypothesis tested when that hypothesis is true.
- Cutoff Value:
where only those p-values less than or equal to the cutoff will result in rejecting null hypothesis.
- Region of Rejection:
range of values that leads the researcher to reject the null hypothesis
- Reject Null:
P < .05
- Fail to Reject Null:
P > .05
- Alpha:
alpha 05 is how significance is determined
05 Criterion:
p-value must be less than this for significant difference
- Between-Subjects Design (Independent Measures):
A research design that uses a separate sample for each treatment condition or each population being compared.
- Within Subjects Design:
1 group testing two different things such as before and after something
- SPSS interpretation:
put in on SPSS and get the results
- Results:
(APA format)
- Power:
of a statistical test is the probability that the test will correctly reject a false null hypothesis. That is, power is the probability that the test will identify a treatment effect if one really exists.
- Type I Error:
when a researcher rejects a null hypothesis that is actually true
- Type II Error:
when a researcher fails to reject a null hypothesis that is really false
- Effect Size:
is intended to provide a measurement of the absolute magnitude of a treatment effect, independent of the size of the sample(s) being used.
Omnibus F test
any statistical test in which the test statistic has an F-distribution under the null hypothesis
Tukey’s HSD test
A test that allows you to compute a single value that determines the minimum difference between treatment means that is necessary for significance. A commonly used post hoc test.
post hoc tests
A test that is conducted after an ANOVA with more than two treatment conditions where the null hypothesis was rejected. The purpose of post hoc tests is to determine exactly which treatment conditions are significantly different.
LSD
least significant difference
