PSY302-300116886
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TESTS
Two-sample t-test: between (independent)
Definition: Testing the relationship between a categorical independent variable and a continuous dependent variable, in which the categorical independent variable is a between-subjects design with two levels.
Example: http://news.bbc.co.uk/2/hi/health/7453167.stm
Application: This experiment tested the relationship between taking Gingko Biloba and progression of dementia. Gingko Biloba was the categorical independent variable and progression of dementia was the dependent variable. There was a control group, which took a placebo, and an experiment group, which took the Gingko Biloba supplements.
Two-sample t-test: within (related)
Definition: Testing the relationship between a categorical independent variable and a continuous dependent variable, in which the categorical independent variable is a within-subjects design with two levels.
Application: Eight children participated in this memory study twice, once when they were 5 and once when they were 7. The independent variable was time and the dependent variable was spatial memory development.
One-Way ANOVA test
Definition: Testing the relationship between a categorical independent variable and a continuous dependent variable, in which the categorical independent variable is a between-subjects design with three or more levels.
Example: http://www.medicalnewstoday.com/articles/75016.php
Application: This experiment tests a new type of gene therapy to treat Parkinson's disease. 12 Parkinson's patients were involved. The patients were separated into three groups, each receiving a different dose of the treatment. The categorical independent variable was the different levels of treatment and the continuous dependent variable was the progression of the Parkinson's disease.
Two-Way ANOVA test
Definition: Testing the relationship between two categorical independent variable and a continuous dependent variable.
Application: This was a study about cognitive dissonance. The two categorical independent variables are incentive and choice. The participants either had low or high incentives and low or high choice. The continuous dependent variable was the participants' agreement with the issue they were supposed to write an essay about.
Correlation test
Definition: Testing the relationship between two continuous variables, either of which can be considered the independent or dependent variable.
Example: http://www.cnn.com/HEALTH/9905/12/children.lights/index.html
Application: A survey showed that there was a correlation between night lights and nearsightedness.
Chi-square test
Definition: Testing the relationship between two categorical variables, either of which can be considered the independent or dependent variable.
Application: A chi-squared test found that gender was found to be associated with the level of personal accomplishment.
Concepts
Standard Score
Definition: A score obtained by using the transformation z = (X-mean)/S
Example: http://www.iqcomparisonsite.com/criteria.aspx
Application: The website details the GRE, SAT, and IQ scores needed for various high IQ societies. The IQ requirement for Mensa is 130 for an IQ test with a standard deviation of 15, which would mean that the standard score (z) for the IQ would be 2.
Confidence Interval
Definition: A range of score values expected to contain the value mu with a certain level of confidence.
Example: http://www.nhs.uk/news/2010/03March/Pages/The-pill-and-womens-lifespan.aspx
Application: The mean relative cancer risk of women who never use birth control is 0.85 with a 95% confidence interval between 0.78 and 0.93.
Parametric Test
Definition: A statistical test involving hypotheses that state a relationship about a population parameter.
Example: http://news.bbc.co.uk/2/hi/health/7453167.stm
Application: A study was done to find the relationship between taking Ginkgo Biloba supplements and the progress of dementia.
Nonparametric Test
Definition: A statistical test involving hypotheses that do not state the relationship about a population parameter.
Application: A nonparametric test found that gender was associated with level of personal accomplishment.
Statistically significant difference
Definition: The observed value of the test statistic falls into a rejection and null hypothesis is rejected.
Example: http://www.medicalnewstoday.com/articles/75016.php
Application: An experiment involving a new type of gene therapy to treat Parkinson's disease showed a significant difference (improvement) before and after the treatment.
Nonsignificant difference
Definition: Observed value of the test statistic did not fall in the rejection region and the null hypothesis is not rejected.
Example: http://news.bbc.co.uk/2/hi/health/7453167.stm
Application: A study showed that taking Ginkgo Biloba did not have a significant effect on dementia so there was a nonsignificant difference.
Between-subjects Design, with two groups
Definition: An experiment in which two groups are created and tested against each other.
Example: http://news.bbc.co.uk/2/hi/health/7453167.stm
Application: Two groups were created for the experiment about whether or not Ginkgo Biloba affected the progress of dementia, a control group that took the placebo and the experiment group that took Ginkgo Biloba supplements.
Between-subjects Design, with three or more groups
Definition: An experiment in which three or more groups are created and tested against each other.
Application: Four groups were created for the study about cognitive dissonance, free-decision low incentive, free-decision high incentive, no-choice low incentive, and no-choice high incentive.
Random sampling
Definition: A sampling method in which individuals are selected so that each member of the population has an equal chance of being selected for the sample, and the selection of the member is independent of any other member of the population.
Example: http://pewresearch.org/pubs/483/muslim-americans
Application: This survey of Muslim Americans was done through random sampling.
Random Assignment
Definition: A method of assigning subjects to treatment groups so that any individual selected for the experiment has an equal probability of assignment to any of the groups and the assignment of one subject to a group does not affect the assignment of any other individual to that same group.
Example: http://www.time.com/time/health/article/0,8599,1968874,00.html?xid=rss-topstories
Application: In a study about educational DVD's for babies, two groups of babies were randomly assigned to a control group and a group that watched Baby Wordsworth.
Independent Variable
Definition: A variable manipulated and administered to subjects in different groups in order to determine its effect on the dependent variable.
Example: http://news.bbc.co.uk/2/hi/health/7453167.stm
Application: In this experiment about whether or not Ginkgo Biloba affected the progress of dementia, the Ginkgo Biloba was the independent variable in the study.
Levels of the Independent Variable
Definition: One value of the independent variable. To be a variable, an independent variable must take on at least two different levels.
Example: http://www.medicalnewstoday.com/articles/75016.php
Application: This experiment tests a new type of gene therapy to treat Parkinson's disease. There were three levels of independent variable. The patients were separated into three groups, each receiving a different dose of the treatment.
Confounds
Definition: An extraneous variable that is covarying with the independent variable, potentially masking the true effects of the independent variable on the depenedent variable.
Example: http://www.queendom.com/tests/access_page/index.htm?idRegTest=1112
Application: This IQ test claims to minimize cultural and educational biases, which are confounding variables in a test.
Dependent Variable
Definition: Variable expected to be affected by the independent variable.
Example: http://news.bbc.co.uk/2/hi/health/7453167.stm
Application: In this experiment about whether or not Ginkgo Biloba affected the progress of dementia, the effect on dementia was the dependent variable.
Within-subjects Design, with two groups
Definition: A research design in which two groups of subjects are exposed to and measured under each level of an independent variable. In within-subject design, each subject receives each treatment condition.
Application: Eight children participated in this memory study twice, once when they were 5 and once when they were 7.
Within-subjects Design, with three or more groups
Definition: A research design in which three or more groups of subjects are exposed to and measured under each level of an independent variable. In within-subject design, each subject receives each treatment condition.
Application: Ninety-three women with metastatic breast cancer participated in a large intervention trial examining the effect of the group therapy on their symptoms. They completed measures of depression, pain, life stress, and sleep disturbance at baseline, 4, 8 and 12 months.
Main effect
Definition: The mean of all subjects given one level of the independent variable, ignoring the classification by the other independent variable in a factorial design.
Application: In this study about cognitive dissonance, no main effect was shown. The MS for choice was 0.9 and the F was less than 1. The MS for incentive was 1.02 and the F was less than 1.
Interaction
Definition: A situation in a factorial design in which the effect of one independent variable depends on the level of the other independent variable with which it is combined.
Application: In this study about cognitive dissonance, there was an interaction between choice and incentive with regards to cognitive dissonance. The MS for the interaction was 10 and the F was 8.7.
Strength of Effect (Eta squared)
Definition:
Example:
Application:
Scatterplot
Definition: A plot of a bivariate distribution in which the X variable is plotted on the horizontal axis and the Y variable is plotted on a vertical axis.
Example: http://www.pdl.cmu.edu/PDL-FTP/Failure/CMU-PDL-06-111.pdf
Application: A scatterplot of the occurrences of hard drive autocorrections over time is graphed on page 12.
Positive relationship
Definition: A relationship between two variables in which, as the value of one variable increases the value of other variable intends to increase also.
Example: http://www.cnn.com/HEALTH/9905/12/children.lights/index.html
Application: A survey found a positive relationship between night lights and nearsightedness in children.
Negative relationship
Definition: A relationship between two variables in which ,as the variable of one value increases, the value of the other variable tends to decrease.
Example: http://ajp.psychiatryonline.org/cgi/reprint/164/8/1268.pdf
Application: There is a negative relationship between obesity and alcohol addiction.
No relationship
Definition: No relationship between two variables that are observed.
Example: http://researchnews.osu.edu/archive/nitelite.htm
Application: This survey found that there was no relationship between night lights and nearsightedness in children.
Linear relationship
Definition: A relationship between two variables where when one changes by a constant amount relative to the other.
Example: http://ajp.psychiatryonline.org/cgi/reprint/164/8/1268.pdf
Application: There is an inverse linear relationship between obesity and alcohol use.
Curvilinear relationship
Definition: A relationship between two or more variables which is depicted graphically by anything other than a straight line.
Example: http://www.unu.edu/unupress/food2/uid10e/uid10e04.htm
Application: There is a curvilinear relationship between body mass index and percent body fat.
Coefficient of Determination
Definition: The value of r^2, indicating the variance of variables X and Y.
Example: http://www.unu.edu/unupress/food2/uid10e/uid10e04.htm
Application: The correlation between number of hard drive failures and time (weeks) is 0.79, so the coefficient of determination is 0.62.
Correlation does not equal causation
Definition: A correlation between two variables does not automatically prove or imply that one causes the other.
Example: http://www.cnn.com/HEALTH/9905/12/children.lights/index.html http://researchnews.osu.edu/archive/nitelite.htm
Application: The first survey found a positive relationship between night lights and nearsightedness in children. However, it did not take into account whether or not the parents were nearsighted. The second survey accounted for that and found no relationship between night lights and nearsightedness.
Extra-Credit (3 points each)
Normal Distribution
Symmetrical
Asymptotic
Continuous
Sampling Error
Null Hypothesis
Alternative Hypothesis
Significance level
Two-tailed test
One-tailed test
Degrees of Freedom
Type I Error
Type II Error
Power
Pairwise comparisons
Post-hoc comparisons
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