Pregunta | Respuesta |
Nominal or categorical variable | Numbers = Discrete categories Numbers don't signify higher or lower. Correlations can not be done with this type of data, unless it is dichotomous, such as, gender. |
Ordinal data | order or rank. These do signify high or low. Differences between ranks are not equivalent. Can do phi correlations, can't do pearsons correlations. |
Interval, or continuous data | Most common in Psychology, e.g., Likert scale. Note; singular Likert scale data is ordinal but when data is multiplied and combined then it becomes continuous. Ratings are more sensitive than rankings. However, rankings can be easier to do. |
Ratio | interval scale with a zero point, e.g., height, weight, etc. Psychology does not use this much. |
Categorical data is good for? | Frequencies within the data, i.e., the numbers of individuals within each group. Can use then as an IV in an analysis of variance (ANOVA, MANOVA), can do a chi square. You can't generate a mean with categorical data. |
Ordinal Data good for? | It is a mixture of both categorical and interval data. Usually just reporting the rank ordering |
Continuous data good for? | It is the most flexible data for quantitative analysis. You can derive a mean and a standard deviation. Can do correlations, t-tests, ANOVAs |
Making sense of data requires; Description | Descriptive statistics, what the data looks like. This is where you report where the distributions of your data are. No hypotheses should be mentioned. |
Making sense of data requires; Analysis | Inferential Statistics. What the data is referring to about the hypotheses. |
How to present frequency distributions | Graphs such as bar graphs and pie graphs are good for presenting frequency distributions. |
Discriptive statistics with interval data | Mean, Median, Mode (measures of central tendency). |
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Positive skew. Normally occurs when asking about things which occur rarely, e.g., how often do you kill people. |
Negative Skew | When the data is bunched to the right. Usually occurs when there is something that happens often, e.g., how often do you smile |
Skews are ___ for analysis of variance | Bad for analysis of variance. Normal distributions are better |
Variability is? | How much the score varies around the mean, ST is the average variance away from teh mean, this is essential for discriptive and inferential statistics. |
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