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29 Cards in this Set
- Front
- Back
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Statistics |
Organize and interpret the data we collect from participants. |
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Descriptive Statistics |
Helps us describe a set of data. May organize data into visual forms such as tables and graphs. |
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Inferential Statistics |
Making inferences on whether or not our hypothesis has been supported or not. Looking for generalization for populations. |
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Relative Frequency (Rel .F) |
Proportion of occurrences of a particular data point in a data set. |
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% Ile |
Percentage of participants with particular score or lower score. |
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Central Tendency |
Where the middle of the data set is. |
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Average |
Mathematical middle of the data set. |
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Mode |
Most frequently occurring value/scale in a data set. Especially essential for data measured on a nominal scale. |
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Median |
The midpoint if the data set. Organizing scores into ascending order. |
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Mean |
Mathematical average of the data set, located in the mathematical centre of the data set. |
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Positive Skew |
When the right tail is longer than the left tail. |
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Negative Skew |
When the left tail is longer than the right tail. |
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Skewness |
Symmetry of distribution. |
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Modality |
Number of peaks in a visual graph. |
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Kurtosis |
How concentrated scores are in the centre of the distribution. |
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Width ( Variability/ dispersion) |
The extent to which the scores differ from one another. Looking at how homogenous the data set is. |
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Zscores |
Describes where a score fits in a distribution using the mean and the standard deviation. Allowing to quickly interpret scores in terms of how they measure up to the while distribution. |
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Probability |
Helps determine whether scores are actually different, or if they are caused by random chance. |
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Research Hypothesis |
States how we expect our groups to differ. First hypothesis |
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Null Hypothesis |
Suggests that our groups are the same and the came from the same population, differences come from chance. |
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A Priori |
When we calculate probability in advance before any observations are made. |
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A Posteriori |
Basing probability after observations based on those observations. |
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Parameter |
Any characteristic of a population, any measure of a central tendency, shape or modality. |
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Hypothesis testing |
Trying to determine whether there is a relationship between two variables, using statistics to test the data. |
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Sampling Error |
Difference between population statistics and sample statistics. |
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Distributions of means |
Collection of sample means where all possible random samples of a particular size that cane be obtained from a population. |
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Central Limit Theory |
Gives and exact distribution and descriptions of means that we would get if we randomly drew every sample population. |
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Ztests |
Used to make inferences about populations using sample data. |
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Raw scores/ Critical values |
Score in the distribution that mark the edge of the region of rejection that define a value required for a sample to be in the region of rejection. |
