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35 Cards in this Set
- Front
- Back
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Statistics |
the field that applies mathematical techniques to organizing data |
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Descriptive Statistics |
measures of central tendency, variability and association |
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Measures of Central Tendency |
Typical score representation; lets us know "average" A single value that describes the way in which a group of data cluster around a central value |
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Mode |
most frequently occurring value in a set of scores |
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Mean |
[average] the arithmetic average of a set of scores, considers all the value in a data set found by adding up all the scores and dividing them by the amount of scores |
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Median |
middle score in distribution of scores that have been ranked in numerical order - divides the score in half |
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Measures of Variability |
how spread apart the scores of distribution are and how much the scores vary from each other
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Range |
difference between the lowest and highest scores in the group subtract the lowest value in the set from the highest |
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Variance |
the average squared deviation from the mean of scores in the group |
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Standard Deviation (SD) |
takes the variance and calculates the square root; has an advantage due to changing the units back to their original state |
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Measures of Association |
different types of association between two variables |
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Correlation |
looks at the relation between two variables using a statistic called a correlation coefficient |
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Pearson's r |
used to determine the strength and the type of linear relationship between two variables Correlation Coefficient |
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Positive Correlation |
higher scores on one variable are associated with higher scores on the other variable range from +.01 to +1.00 |
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Negative Correlation |
higher score on one variable are associated with lower scores on a second variable range from -.01 to -1.00 |
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Is Correlation evidence of causation? |
correlation does not prove causation |
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What are the advantages of correlation? |
predictino - if you know the relation between variables and measure one, you can more reliably estimate the other |
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What are the disadvantages of correlation? |
It cannot determine cause and effect, it works both ways (bidirectionally) and the 3rd Variable Problem |
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3rd Variable Problem |
the possibility that there is a 3rd unknown variable causing the correlation as opposed to the two variables |
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The Bell Curve (the normal curve) |
the mean, median and mode will always be the centre of the curve if we know the mean and variation for a set of score we can use the normal curve to estimate the probability or frequency of any particular score |
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Distributions |
graphs and different types of visualizations for looking at data |
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Inferential Statistics |
help make decisions about the "meaning" of data obtained from samples used to make generalizations from a sample to a population |
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Hypothesis Testing |
formalized process involving the null hypothesis, an experimental hypothesis and statistical techniques statistical details differ depending on the characteristics of the data set and the exact questions being asked but the general logic of hypothesis testing is the same across experiments |
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Null Hypothesis |
the mean scores of population A and population B do not differ |
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Significance |
results that have a low probability are said to be significant, which means they indicate that the null hypothesis is probably not correct probabilities are called "p values" |
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What P values are used to qualify results as "unlikely" or "significant"? |
.05 or .01 |
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Experimental Hypothesis |
the mean scores of population A and population B do differ |
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What are the different ways of testing hypotheses? |
Chi-square test, t-test, analysis of variance (ANOVA), and nonparametric statistics |
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Chi-square Test |
a measurement of how expectations compare results data must be random, raw, mutually exclusive, drawn from independent variables and drawn from a large enough sample |
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T-Test |
an analysis of two populations means through the use of statistical examination |
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Analysis of Variance (ANOVA) |
a statistical procedure used to test the degree to which two or more groups vary or differ in an experiment |
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What is the difference between parametric and nonparametric statistics? |
one is a statistical test that makes assumptions about the defining properties while the other is one that makes no assumptions |
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What are some sources for flaws in statistical analysis? |
nonrandom sampling, confounding variables or experimenter error |
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Do statistics lie? |
No, but they can be misused to support conclusions that may in fact not deserve support despite what the numbers say |
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When can statistics be interpreted with full confidence? |
When you have an understanding of the procedures that generated the statistics like research design and statistical techniques |
