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| are simply describing what is or what the data shows. |
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| you are trying to reach conclusions that extend beyond the immediate data alone (generalize). |
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| Descriptive statistics are Are a means of organizing and summarizing data through |
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Tables
Graphs
Numerical summary measures |
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| identity, magnitude, and exponential |
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| identity, magnitude, exponential, and true value |
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| categorical and scale/metrics |
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| Two types of categorical data |
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| all subjects assigned a value, those with the same value are the same on that characteristic but categories are not necessarily the same. |
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| Scale data can be converted into |
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Persons or objects with the same value are the same on some attribute.
The values of the scale have no 'numeric' meaning |
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People or objects with a higher scale value have more of some attribute.
The intervals between adjacent scale values are indeterminate.
Scale assignment is by the property of "greater than," "equal to," or "less than." |
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| Intervals between adjacent scale values are equal with respect the attribute being measured. |
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| Using the wrong type of data may violate the assumptions of statistical tests which then makes interpreting your results __________/________ |
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List of variables
Assigned values
Level of measurement |
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| Facilitates data entry into SPSS |
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| two types of nonparametric data |
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| Two types of parametric data |
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| the set of elements we are planning study |
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| Organizes ungrouped data by indicating the number of times (frequency) each score was obtained |
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| Frequency distribution is ranked from |
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| Frequency distribution, table of results that shows the |
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| number of times a characteristic comes up |
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| A type of bar graph, in which lines or bars represent each score or set of scores rather than lines connecting the frequencies of each score |
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| The degree to how the scores fall disproportionately to one end of the distribution |
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| normal, unimodal and symmetric |
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, , , ,
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| Three measures of central tendency |
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| The score in the distribution that occurs most frequently |
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| Middle score of the distribution that divides the distribution into halves containing an equal number of scores |
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Arithmetic average of ALL the scores in the distribution
Add all the scores and divide by the number of scores |
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| Central tendency for nominal data |
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| Central tendency for ordinal data |
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| Central tendency for scale data |
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| Two measures of variability |
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| range and standard deviation |
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| The numerical difference between the highest and lowest scores in the distribution (doesn’t make sense for nominal data but works for ordinal and scale level data). |
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| A statistic that indicates the average distance of the scores from the mean of the distribution (only works for scale level data). |
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| Variation measure for ordinal data |
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| Variation measure for scale data |
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| range and standard deviation |
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| Variation measure for nominal data |
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Degree to which the scores of TWO or more variables are RELATED
A measure of the relationship between two variables |
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| the DIRECTION and STRENGTH of a relationship between 2 variables |
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| Two types of correlation tests |
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Spearman Rank Order Correlation
Pearson Product-Moment Correlation |
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| Increase in one variable is accompanied by an increase in the other variable |
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As one variable increases, the other variable decreases
Inverse relationship |
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| Two aspects of correlation coefficient |
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| direction and strength/magnitude |
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| To find direction look at |
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| to find magnitude look at |
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| When do you use Spearman's |
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