## Data Crash Course: Types of Data and Scales of Measurement

Before you begin to collect data for your thesis or dissertation, it may be helpful for you to review the different types of data and scales of measurement available to you. You can use the following cheat sheet as a reference guide as you prepare to collect your dissertation data.

### Scales of Measurement

**Nominal:**(a.k.a., categorical) refers to characteristic data that have no numeric value (i.e., ethnicity)

** Dichotomous:** refers to types of nominal data that only have two categories (i.e., alive or dead)

**Ordinal:** refers to numeric values of rank order (i.e., first, second, third, etc.) that have indeterminate intervals between adjacent values

**Interval:** refers to values that are continuous in nature and that are in the same metric

**Ratio:** refers to values that are continuous in nature and that are in the same metric and includes a nonarbitrary zero

### Measures of Central Tendency

**Mean:** arithmetic average of a variable

**Median:** midpoint of a distribution (i.e., the same number of scores are above and below the median)

**Mode:** most frequently occurring value

### Variability

**Variability:** quantitative measure of the degree to which data in a distribution are spread out or clustered together, which is used to describe distribution

**Range:** difference between the upper limit and lower limit of a variable

**Deviation:** distance from the mean

**Variance:** mean of the squared deviation scores

**Standard deviation:** standardized measure of the variability of a variable and the square root of variance

**Kurtosis:** refers to the sharpness of the peak of a distribution

** Mesokurtic:** normal frequency

** Leptokurtic:** sharp peak (i.e., little variability)

** Platykuritc:**flat peak (i.e., much variability)

### Distribution

**Distribution:** arrangement of values that variables take in a sample (i.e., the shape of the data)

#### Types of Distribution

**Normal distribution:** (a.k.a., the normal curve) occurs when the mean, median, and mode are the same value; normally distributed data will have a mean of 100 and a standard deviation of 15

**Negatively skewed:** occurs when the mode is greater than the median and the mean and when the median is greater than the mean

**Positively skewed:** occurs when the mean is greater than the median and the mode and when the median is greater than the mode

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