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glasses of water they drink on a typical day. 1. What is the median of the data set? 2. Organize the data into two groups: the top half and the bottom half. How many data values are in each group? 3. What is the median of each group? 4. Find the difference between the two numbers from Exercise 3. Measures of variation are
Measures of Variation -. Measures of Variation. Some Comments. • Range is the simplest, but is very sensitive to outliers. • Variance units are the square of the original units. • Interquartile range is mainly used with skewed data (or data with outliers). • We will use the standard deviation as a. f i i ft i hi measure of variation
Overview. Discuss Common Measures of Variability. ? Range. ? Semi-Interquartile Range. ? Variance. ? Standard Deviation. Derive Computational Formulas for the. Standard Deviation and Variance
Chapter 3: Measures of Variability. I. Measures of central tendency vs. Measures of variability a. Measures of central tendency (e.g., mean, median, mode) provide useful, but limited information. Information is insufficient in regards to the dispersion (i.e., variability) of scores of a distribution. b. Three measures of variability
I . Measures of Variability (Dispersion). -Allow us to summarize our data set with a single value. -Central Tendency + Variability = a more accurate picture of our data set. -The 3 main measures of variability: Range, Variance, and. Standard Deviation. • These formulas are the root formulas for many of the statistical tests that
Histograms are important tools for image processing. By doing statistics on the individual pixel values we can analyze an image, attempt to recognize features, or just make it “look better". center overall brightness of the image (mean pixel value) variation image contrast. 1
Measures of variability: the range, inter- quartile range and standard deviationar charts www.le.ac.uk/succeedinyourstudies. This guide outlines three methods used to summarise the variability in a dataset. It will help you identify which measure is most appropriate to use for a particular set of data. Examples are also given
Measures of variation refer to a group of statistics that is intended to provide us with information on how a set of scores are distributed. An examination of measures of variation is a logical extension of any description of a data set using the measures of central tendency that we examined in the previous chapter. Consider a
Summarizing Data: Measures of Variation. One aspect of most sets of data is that the values are not all alike; indeed, the extent to which they are unalike, or vary among themselves, is of basic importance in statistics. Consider the following examples: In a hospital where each patient's pulse rate is taken three times a day,
Characteristics of. Standard Deviation? s is usually positive and NEVER negative s is 0 only when all data values are the same number the larger value for (s) the greater amount the data varies s can increase dramatically with the inclusion of outliers the units (minutes, feet, etc) are the same as the units of original values
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