Comps stats/research/etc

Maturation

any biological or psychological change that occurs within subjects during the course of a study as a function of time (fatigue, boredom, hunger, physical/cognitive development)

What type of validity does maturation affect:

internal validity

History affects which type of validity:

internal

A change in the accuracy or sensitivity of measuring devices or procedures during the course of the study impacts

A change in the accuracy or sensitivity of measuring devices or procedures during the course of the study impacts internal validity (instrumentation)

Statistical regression impacts

internal validity

•Selection impacts

Selection impacts internal validity

Attrition affects

internal validity

Internal validity is

the ability to draw a conclusion

external validity is

the ability to generalize conclusion

Pretest sensitization affects ___ validity

Pretest sensitization affects external validity as results cannot be generalized to those who have not taken the pretest

Interaction between selection and treatment can impact which type of validity

External (subjects can have characteristics that make them respond to the variable in a certain way; results cannot be generalized to those without the characteristics)

Reactivity (reactive arrangements) affects which type of validity

External (part. may respond to an independent variable in a particular was bc they know their beh is being observed)

Multiple treatment interferences (order effects, carryover effects) impact which type of validity

external validity

Multiple treatment inference affects which type of valdity

external

Psychologist studying effects of drugs. She uses BPRS to eval the patient's symptoms once each week for 6 weeks during the baseline and for 6 weeks during the treatment phase. What type of design did she use?

AB design example

Psych. is studying effects of a drug. She uses the BPRS to eval symptoms one a week for 6 weeks during the baseline, then for 6 weeks during treatment, then 6 weeks during baseline, then 6 weeks during treatment. What study design is this

ABAB example

Descriptive Statistics are used to

describe and summarize data collected on a variable or the relationship between variables

Inferential statistics are used to

determine if obtained sample values can be generalized to the population from which the sample was drawn

Kurtosis

relative peakedness of a distribution

Leptokurtic

distribution is more peaked than the normal distribution

Platykurtic

distribution is flatter than the normal distribution

Variance (mean square) provides

a measure of the avg amount of variability in a distribution by indicating the degree to which the scores are dispersed around the distribution's mean

Why is standard deviation used rather than variance

Because variance requires squaring each deviation score, the variance represents a unit of measurement that differs from the og unit of measurement

_____ is the square root of the variance

standard deviation is

What % of scores falls b/w (+/-) 1 standard deviation from the mean

68.26%

What % of scores fall betweeen (+/-) 2 standard deviations from the mean

95.44%

What % of scores fall between (+/-) 3 standard deviations from the mean

99.72%

Central limitation theorem makes 3 predictions:

1. regardless of the shape of the distribution of indiv scores in the population, as the sample size increases the sampling distribution of the mean approaches a normal distribution

2. The mean of the sampling distribution of the mean is equal to the population mean

3. The SD of the sampling distribution of the mean is equal to the population SD/ square root of the sample size

Standard deviation of a sampling distribution of the mean is known as the

standard error of the mean

What does the SEM provide an estimate of

the extent to which the mean of any one sample randomly drawn from a population can be expected to vary from the population mean as the result of sampling error

the size of SEM is affected by

population standard deviation and the sample size

"when the results of a study are ""statistically significant"", this means that the obtained sample value is in the ______ of the sampling distribution and that the investigator has rejected the _____"

rejection region; null hypothesis

Type I error is ___ and related to ___

false positive; alpha

Type II error is ___ and is related to ___

false negative; beta (affected by low alpha, small sample size, and independent variable not administered in sufficient intensity)

Statistical power

when a statistical test enables an investigator to reject a false null hypothesis

Methods for maximizing statistical power (6)

1. increase alpha 2. increase sample size 3. increase effects of the IV 4. minimize error 5. use a one-tailed test when appropriate 6. use a parametric test (t-test or ANOVA)

Homoscedasticity

assumption that the variances of the populations that the different groups represent are equal

With nominal data, what test can be used

chi- square: single-sample or multiple-sample

Parametric tests

used to evaluate hypotheses abt population means, variances, or other parameters

Nonparametric tests

"distribution-free tests""; used to evaluate hypotheses about the shape of a distribution rather than its mean, variance, or other parameter"

What tests are considered non-parametric tests (3)

chi-square, Mann-Whitney U test, and Wilcoxon matched-pairs test

Mann-Whitney U Test

Which test is used when a study includes

One IV: two independent groups

One DV: rank-ordered data

Which test is used when a study includes 2 correlated (matched) groups (1 IV) and the difference scores on the DV for pairs of subjects are converted to ranks

Wilcoxon Matched-Pairs Signed-Ranks Test

Which test is used when a study includes two or more independent groups and the data being analyzed is ranks

Kruskal-Wallis Test

student's t-test

evaluate hypotheses abt the differences between TWO means

Analysis of Variance (ANOVA)

used to compare two or more means

Analysis of Covariance (ANCOVA)

combines the analysis of variance with regression analysis and allows an investigator to control an extraneous variable by statistically removing the portion of variability in the dependent variable that is due to the extraneous variable

When is trend analysis used

when the study involves one or more quantitative independent variables and the researcher wants to evaluate the shape or form of the relationship b/w the IVs and DVs (determines if there is a linear or nonlinear relationship)

Multivariate Analysis of Variance (MANOVA)

study includes one or more independent variables and two or more dependent variables that are each measured on an interval or ratio scale

Correlation coeeficient

summarizes the degree of association between variables with a single number

Most correlation coefficients require that 3 assumptions must be met:

1. Linearity 2. Unrestricted range 3. Homoscedasticity: range for y scores is abt the same for all values of x

Pearson r variables

V1: interval or ration

V2: interval or ratio

Spearman rho variables

V1: rank-ordered V2: rank-ordered

Point biserial correlation coefficient variables

V1: true dichotomy (male or female)

V2: interval or ratio

Biserial

V1: artifical dichotomy (company climate: favorable/unfavorable) V2: interval or ratio

Eta correlation coefficient

used when relationship b/w variables is nonlinear V1: interval or ratio

V2: interval or ratio

Coefficient of determination

squared correlation coefficient indicating the proportion of variability in Y that is explained by or accounted for by variability in X (r-squared)

"When the # of observations is 10, the correlation coefficient must be at least ____ to be statistically significant"

.63

"When the # of observations is at least 50, a correlation coefficient of only ____ is statistically significant"

.28

Regression analysis

the technique that allows such predictions to be made when there is one predictor (X) and one criterion (Y)

Multiple regression

the appropriate multivariate technique when two or more continuous or discrete predictors will be used to predict status on a single continuous criterion

Multicollinearity

high correlation between two or more predictors

Benefits of multiple regression vs. ANOVA (3)

1. compare groups unequal in size without reducing power 2. can use when IVs are on continuous scale vs ANOVA requires they are changed to categories 3. add or subtract IV to analysis to determine which set of variables best explains variability

Discriminant function analysis

two or more continuous predictors will be used to predict or estimate a person's status on a single discrete (nominal) criterion

Logistic regression

used to predict status on a single discrete criterion using two or more continous or discrete predictors. assumes relationships are nonlinear