Psychology: Statistics for Psychology 6th Edition
Log-linear models where at least one variable is treated as an independent variable and at least one variable is treated as a dependent variable. A stepwise regression procedure in which we start with all predictors and them eliminate those that do not contribute significantly or up to some predetermined standard. An old name given to the problem of how to compare two independent means when we can not assume homogeneity of variance.
The distribution in which each of a number of independent trials results in one of two mutually exclusive outcomes. The correlation between a continuous variable and a dichotomous variable, where we assume an underlying normality to the dichotomous variable. Rarely used. An inequality on which the Bonferrone test is based. It states that the probability of the occurrence of one or more events can never exceed the sum of their individual probabilities.
A multiple comparison procedure in which the familywise error rate is divided by the number of comparisons. The effect of previous trials conditions on a subject's performance on subsequent trials. The combination of a particular row and column; the set of observations obtained under identical treatment conditions. Data that have been categorized into two or more groups on the basis of a cutoff score on some criterion variable. Often a consideration in logistic regression. The distribution of the chi-square c 2 statistic. The condition in which the independent variables are usually highly correlated with each other.
The branch of mathematics dealing with the number of different ways objects can be selected or arranged.
Statistics for Psychology: Pearson New International Edition
The condition with constant variances on the main diagonal of a matrix, and constant covariances off the main diagonal. An interval, with limits at either end, with a specified probability of including the parameter being estimated. Two variables are said to be confounded when they are varied simultaneously and their effects cannot be separated. A coefficient, based on chi-square, reflecting the degree of relationship exhibited in a contingency table. A comparison between two levels or two sets of levels of the independent variable following an analysis of variance. A measure of the degree of relationship between two variables that are each at least ordinal.
The result of taking a regression equation from one set of data, applying it to a new set of data, and examining the correlation between the predicted and obtained values on the new set of data. The number of independent pieces of information remaining after estimating one or more parameters. Height of the curve for a given value of X- closely related to the probability of an observation in an interval around X.
Statistics which describe the sample data without drawing inferences about the larger population. The set of scores representing the difference between the subjects' performance on two occasions. Also known as "gain scores. A procedure for developing a procedure for optimally discriminating between two groups. This technique often being replaced with logistic regression.
Pin on Test Bank
An interaction in which group differences reverse their sign at some level of the other variable. The vertical distance between a point and the regression line. Usually known as the "residual. Statistical tests that do not rely on parameter estimation or precise distributional assumptions. A distribution that represents the frequencies of individual points by stacking dots about the axis--similar to a histogram. A test similar to the Bonferroni test which is based on a more precise inequality and has slightly more power.
A multiple comparison procedure for comparing each mean against a standard control group mean. The difference between two population means divided by the standard deviation of either population. The sample size needed in equal-sized groups to achieve the power when we have groups of unequal sizes. It will generally be less than the total number of subjects in the unequal groups. An analysis of variance in which cell means all carry the same weight in determining row and column means, regardless of the number of subjects in each cell. The probability of making a Type I error on any specific comparison when using multiple comparison procedures.
An experimental design in which every level of each variable is paired with every level of each other variable. A multiple comparison technique that requires a significant overall F , and that involves standard t tests between pairs of means. Also known as the "protected t test.
The situation in which the marginal totals in a contingency table are known before the data are collected and are not subject to sampling error. An analysis of variance model in which the levels of the independent variable are treated as fixed. A variable that takes on a specific set of values. An independent variable who levels are assigned by the experimenter. A distribution in which the values of the dependent variable are tabled or plotted against their frequency of occurrence.
A mean of n objects that is computed by taking the n th root of the product of the n terms. The number of elements to be averaged divided by the sum of the reciprocals of the elements. A distribution with a higher percentage of scores in the tails than we would expect in a normal distribution. Data in which the sample of observations could be subdivided into two distinct sets on the basis of some other variable. A model in which the presence of an interaction requires the inclusion of any main effects that comprise that interaction. Sums of squares in the analysis of variance where later terms in the model are adjusted only for terms that precede them.
Graph in which rectangles are used to represent frequencies of observations within each interval. The assumption that the regression line expressing the dependent variable as a function of a covariate is constant across several groups or conditions. The requirement that the variance in Y associated with one value of X is the same as the variance in Y associated with other values of X.
Events are independent when the occurrence of one has no effect on the probability of the occurrence of the other. Various software packages are available for statistical methods for psychological research.
- The Bone Bed (Scarpetta 20);
- Top Authors.
- Crating and Kenneling For Dummies®, Portable Edition.
- You are here?
- Dillons Promise.
- The Surgery Book: For Kids (Happy Kids Books Book 1)!
- From Then to Now: A Short History of the World (Governor Generals Literary Awards Childrens Literature (Tex).
They can be classified as commercial software e. Among the free-wares, the R software is most popular one.
- Beyond Diversity Day: A Q&A on Gay and Lesbian Issues in Schools (Curriculum, Cultures, and (Homo)Sexualities Series).
- Everlastin (Everlastin Series Book 1)!
- Statistics for Psychology, 6th Edition.
There are many online references for R and specialised books on R for Psychologist are also being written e. The "psych" package of R is very useful for psychologists. Among others, "lavaan", "sem", "ltm", "ggplot2" are some of the popular packages. From Wikipedia, the free encyclopedia. This article needs more links to other articles to help integrate it into the encyclopedia. Please help improve this article by adding links that are relevant to the context within the existing text.
December Learn how and when to remove this template message. Basic types. Applied psychology. Main article: Psychometrics. Main article: Classical test theory. Main article: Reliability research methods. Main article: Test validity. Main article: Item Response Theory.
hukusyuu-mobile.com/wp-content/secret/1726-cell-phone-number.php Main article: Factor Analysis. Main article: Exploratory Factor Analysis. Main article: Confirmatory Factor Analysis.