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56 Cards in this Set
- Front
- Back
- 3rd side (hint)
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hypothesis testing
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whether a hypothesis is supported by the results of a research project
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inferential statistics
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drawing conclusions about a population based on data collected form a sample
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compare measure of dependent variable in each group
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null hypothesis
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predicts that there is no difference between the groups being compared
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there's no difference!
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alternative hypothesis
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a significant difference exists between the groups being compared
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difference!!
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one tailed hypothesis
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researcher predicts the direction of the expected difference between groups
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for a directional alternative hypothesis
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two-tailed hypothesis
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groups being compared differ but doesn't predict the direction of the difference
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non-directional alternative hypothesis
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type I error
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difference, but in reality, there isnt
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false alarms
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type II error
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there is a difference, when in reality there is
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failed to reject null hypothesis
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statistical significance
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2 descriptive statistics that's unlikely to have occurred by chance
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single-group design
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one group of participants
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z test
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compare a sample with a population to assess whether the sample differs significantly from the population
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tesing the null hypothesis on a single sample
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sampling disitribution
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a distribution of sample means based on random samples of a fixed size from a population
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a distribution of statistics obtained by selecting all possible samples of a specific size from a population
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standard error of the mean
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standard deviation of the sampling distribution
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critical value
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value of a test statistic that marks the edge of the region of rejection in a sampling distribution, where values equal to it or beyond it fall in the region of rejection
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region of rejection
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area of sampling distribution that lies beyond the test statistic's critical value; when a score falls within this region, Ho is rejected
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statistical power
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probability of correctly rejecting a false Ho
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test will correctly reject a false null hypothesis
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confidence interval
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interval of a certain width which we feel confident will contain population mean
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t test
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test of the null hypothesis for a single sample where population variance is not known
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student's t distribution
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curve was symmetrical, but it wasn't the standard normal curve
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degrees of freedom
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number of scores in a sample that are free to vary
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z test
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compare a sample with a population to assess whether the sample differs significantly from the population
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how many SD above or below the mean score falls
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sampling disitribution
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a distribution of sample means based on random samples of a fixed size from a population
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estimated standard error of the mean
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standard deviation of the sampling distribution
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chi-square
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comparing categorical information against what we would expect based on previous knowledge
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observed frequency
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frequency with which participants fall into a category
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expected frequency
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requency expected in a category if the sample data represent the population
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independent-groups t test
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a parametric inferential test for comparing sample means of two independent groups of scores
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between participants when participants are NOT matched
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effect size
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how big a role the conditions of the independent variable play in determining scores on the dependent variable
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an estimate of the effect of the IV, regardless of sample size. is difference meaningful?
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cohen's d
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inferential statistic for measuring effect size
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correlated-groups t test
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compares the means of participants in 2 groups
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comparing mean difference of correlated scores
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difference scores
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scores represnting the difference between participants' performance in a second condition
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wilcoxon rank-sum test
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nonparametric inferential test for comparing sample medians of 2 independent groups of scores
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teacher ranks the female and male giving the student who read the fewest a rank of 1, and who read the most the highest rank.
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chi-square test of independence
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comparing how well an observed breakdown of people over various cateogries fits some expected breakdown
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comparing how well an observed breakdown of people over various categories fits some expected breakdown
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phi coefficient
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an inferential test used to determine effect size for a chi-square test
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bonferroni adjustment
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desire alpha level is divided by the number of tests or comparisons, is typically used to accomplisht his
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minimize chance of a type I error when making multiple comparisons, but increases type II error
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ANOVA (analysis of variance)
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comparing means of 3 or more groups
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allows us to analyze the variance in a study
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one-way randomized ANOVA
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comparing means of 3 or more groups using a between-participants design and one IV
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grand mean
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the mean performance across all participants in a study
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error variance
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amount of variability among the scores caused by chance or uncontrolled variables
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such as individual differences between participants
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within-groups varaince
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variance w/in each condition; an estimate of the population error variance
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within-subjects: same people exposed to each level of IV
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between-groups variance
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estimate of the effect of the independent variable and error variance
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between-subjects: different people are exposed to the each level of the IV
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f-ratio
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ratio of between-groups variance to within-groups variance
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total sum of squares
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sum of squared deviations of each score for the grandmean
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how much each individual participant varies from the grand mean
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within-groups sum of quares
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sum of the squared deviations of each score from its group mean
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between-groups sum of squares
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sum of the squared deviations of each group's mean form the gran mean, multiplied by the number of participants in each group
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post hoc test
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comparing each of the groups in the study with each of the other groups to determine which ones differ significantly from each other
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permits multiple compariosns and still manitain alpha (the probablity of a type I error) at .05
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Tukey's honestly significant difference (HSD)
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post hoc test used w/ ANOVAs for making all pairwise comparisons when conditions have equal n
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allows a researcher to make all pairwise comparisons among the sample means in a study while mantaining an acceptable alpha (usually .05 but could be .01)
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one-way repeated measure ANOVA
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comparing the means of 2 or more groups using a correlated-groups design and one IV
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mesares are taken repeatedly on the same individuals; same participants serve in all conditions
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factorial design
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more than one IV
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factorial notation
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how may IVs are used in a study and how many levels are use for each variable
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each number in the notation specifies the number of levels of a single IV. 3 x 6 has 2 IVs, one IV has 3 levels the other 6.
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main effect
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an effect of a single independent variable
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2 IVs may have 2 main effects, an effect of word type and an effect of rehearsal type
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interaction effect
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effect of each IV across the levels of the other IV
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interaction between 2 IVs, effect of 1 IV depends on the level of the otehr IV
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treatment carryover effect
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earlier treatment affects later treatment
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sensitization effect
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performance changes due to hypothesis guessing
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practice effect
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performance improves later mesaures
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fatigue effect
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performance declines on later measures
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