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Chapter 13 (Quiz 3)
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Terms in this set (31)
Descriptive statistics
Collection and presentation of data that explain characteristics of variables found in the sample
Inferential statistics
Analysis of data as the basis for prediction related to the phenomenon of interest
Univariate analysis
The use of statistical tests to provide information about one variable
Bivariate analysis
The use of statistics to describe the relationship between two variables
Multivariate analysis
The use of statistics to describe the relationships among three or more variables
Population parameters
Characteristics of a population that are inferred from characteristics of a sample
Measures of central tendency
Measures (ex// mean, median, mode) that provide information about the typical case found in the data
Mean
The mathematical average calculated by adding all values and then dividing by the total number of values
Median
The point at the center of a data set
Mode
The most frequently occurring value in a data set
Frequency distributions
A method of tallying and representing how often certain scores occur
Percentage distributions
Descriptive statistics used to group data to make results more comprehensible; calculated by dividing the frequency of an event by the total # of events
Normal distribution
Data representation with a distinctive bell-shaped curve, symmetric about the mean
Skewed distribution
An asymmetrical distribution of data
Measures of variability
Measures providing information about differences among data within a set; measures of dispersion
Range
The difference between the maximum and minimum values in a data set
Standard deviation
A measure of variability used to determine the number of data values falling within a specific interval in a normal distribution
Rule of 68-95-99.7
Rule stating that for every sample 68% of the data will fall within one standard deviation of the mean; 95% of the data will fall within two standard deviations; 99.7% of the data will fall within three standard deviations
Confidence intervals
Ranges established around means that estimate the probability of being correct
Type I error
When the researcher rejects null hypothesis when it should have been accepted
Type II error
When the researcher inaccurately concludes that there is no relationship among the independent and dependent variables when an actual relationship do exist; when the researcher accepts the null hypothesis when it should have been rejected
Alpha level
Probability of making a type I error; typically designed as .05 or .01 at the end of the tail in a distribution
Parametric statistics
Inferential statistical tests involving interval- or ratio-level data to make inferences about the population
Non-parametric statistics
Inferential statistics involving nominal- or ordinal-level data to make inferences about the population
Chi square
A common statistic used to analyze nominal and ordinal data to find differences between group
t-test (t statistic)
Inferential statistical test to determine whether a statistically significant difference between group exists
Analysis of Variance (ANOVA)
Inferential statistical test used when the level of measurement is interval or ratio and more than two groups are being compared
Pearson's r
An inferential statistic used when two variables are measured at the interval or ratio level; Pearson product-moment correlation
Multiple regression
Inferential statistical test that describes the relationship of three or more variables
Statistically significant
When critical values fall in the tails of normal distributions; when findings did not happen by chance alone
Clinical significance
See page 383
Ex// Children in the guided imagery group had average pain ratings of 4.2, while children in the control group had average pain ratings of 5.2. Although the difference between these means is not statistically significant, it may be clinically significant to have pain ratings a whole point lower.
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