Week 8, 9, & 10 Flashcards
Allows researchers to describe or summarize their data
Univariate descriptive statistics
Used to estimate a parameter and to determine whether the results of statistical tests based on the sample drawn from a population can be generalized to that population
Inferential statistics
A statistic used to estimate a parameter based on the data from the sample to say something about a population parameter that is unknown
Confidence interval
A way of quantifying the size of difference between two groups
Effect size
Involves assigning a numerical value to each category of each variable in your study
Coding
Used to describe or summarize the data related to a specific variable of interest
Univariate descriptive analyses
Shows the researcher the number of observations in each category of the variable of interest
Frequency distribution
A measure of symmetry or lack thereof
Skewness
A measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution
Kurtosis
Derived by adding all the individual scores, and then dividing the answer by the total number of scores
Mean
The middle score in the frequency distribution
Median
The most frequently occurring score in the frequency distribution
Mode
The distance between the lowest and highest scores
Range
A single, numerical value indicating how scores distribute themselves around the mean and the distance of the scores from the mean
Standard deviation
Used to determine the association between an interval or ratio (a scale) independent variable and an interval or ratio (a scale) dependent variable
Pearson’s correlation
The normal distribution of scores on the independent and dependent variable
Assumption of normality
The variance around the regression line is the same for all values of the independent variable
Homoscedasticity
Everyone in the population to whom you want to generalize the results had an equal chance of being included in the sample
Simple random sampling
A relationship where the independent and dependent variable change together but not at a constant rate
Monotonic relationship
A test conducted when researchers are examining the association between an independent and a dependent variable, where both are measured on the nominal level
Chi-square test of independence
Appropriate to use when you have more than one independent variable (nominal, ordinal, interval, or ratio) and one dependent variable (interval or ratio)
Multiple regression analysis
The independent variables should not be too highly correlated
Absence of multicollinearity
A way of turning categories associated with a nominal variable into something a regression can treat as having a high and low score
Dummy coding
An inferential statistical test that determines whether there is a statistical significant difference between the mean in two groups, where both the means and standard deviations are estimated from the data
Independent-sample t-test
An inferential statistical test that determines whether there is a statistically significant difference between the means of the observations of the dependent variable, which was assessed twice
Dependent-sample t-test
The purpose of this is to assess for differences between the means for three or more groups
One way analysis of variance (ANOVA)
This is used when there is only one independent variable and two or more dependent variables
One way multivariate analysis of variance (MANOVA)
Produces results indicating that there are true differences between groups, when no such differences exists
Type I error
Produces results indicating that there are no differences between study groups when really there are true group differences
Type II error
