![]() We can calculate common statistical measures like the mean, median, variance, or standard deviation. With the interval level of measurement, we can perform most arithmetic operations. Scores on the College Board's Scholastic Aptitude Test, which measures a student's scores on reading, writing, and math on a scale of 200 to 800.In addition to temperature on the Fahrenheit or Celsius scales, examples of interval scale measures include: But, because our measurement scale lacks a real, non-arbitrary zero, we cannot say the temperature today is twice as warm as the temperature thirty days ago. We can say that the difference between the high temperatures on these two days is 30 degrees. Let's suppose today's high temperature is 60º F and thirty days ago the high temperature was only 30º F. The classic example of the interval scale is temperature measured on the Fahrenheit or Celsius scales. The distances between the ranks are measureable.To repeat, here are three characteristics of the interval level: The interval level, however, lacks a real, non-arbitrary zero. But, unlike the ordinal level, we do have the distance between intervals on the scale. ![]() Like the ordinal level, the interval level has an inherent order. With the interval level of measurement we have quantitative data. And, we cannot perform parametric hypothesis tests using z values, t values, and F values. But, we cannot calculate common statistical measures like the mean, median, variance, or standard deviation. We can also perform a variety of non-parametric hypotheses tests. In terms of statistical analyses, we can count the frequency of an occurrence of an event, calculate the median, percentile, decile, and quartiles. And, as we said, we cannot, however, measure the distance between ranks. With the ordinal level of measurement, we can count the frequencies of items of interest and sort them in a meaningful rank order.
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