Analyzing Data
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| Correlation | A measure that defines the relationship between 2 variables
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| Descriptive Statistics | Statistics that describe and summarize data. When you run a descriptive statistics analysis test, it will look at demographic data (describes the study)
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| Homogeneity of variance | Situation in which the dependent variables do not differ significantly between or among groups
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| Inferential Statistics | Statistics that generalize findings from a sample to a population
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| Level of confidence | Probability level in which the research hypothesis is accepted with confidence. A 0.05 level of confidence is the standard among researchers
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| Mean | A measure of central tendency calculated by summing a set of scores and dividing the sum by the total number of scores; also called the average
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| Measures of central tendency | Descriptive statistics that describe the location or approximate center of a distribution of data
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| Measures of dispersion | Descriptive statistics that depict the spread or variability among a set of numerical data
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| Median | A measure of central tendency that represents the middle score in a distribution
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| Mode | The score or value that occurs most frequently in a distribution; a measure of central tendency used most often with nominal-level data
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| Negative correlation | Correlation in which high scores for one variable are paired with low scores for the other variable
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| Outlier | Data point isolate from other data points; extreme score in a data set
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| Parameter | Numerical characteristic of a population (e.g. population mean, population standard deviation)
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| Positive correlation | Correlation in which high scores for one variable are paired with high scores for the other variable, or low scores for one variable are paired with low scores for the other variable
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| Range | A measure of variability that is the difference between the lowest and highest values in a distribution
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| Robust | Referring to results from statistical analyses that are close to being valid even though the researcher does not rigidly adhere to assumptions associated with parametric procedures
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| Skewed distribution | A distribution of scores with a few outlying observations in either direction
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| Standard deviation (SD) | The most frequently used measure of variability; the distance a score varies from the mean (68% of values will fall within 1 SD from the mean, and 95% will fall within 2 SD's from the mean)
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| Symmetrical distribution | A distribution of scores in which the mean, median, and mode are all the same
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| Variance | Measure of variability, which is the average squared deviation from the mean
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