1. Statistics for Everyone Workshop Fall 2010 Part 2 Descriptive Statistics: Measures of Central Tendency and Variability Workshop presented by Linda Henkel and Laura McSweeney of Fairfield University Funded by the Core Integration Initiative and the Center for Academic Excellence at Fairfield University

2. Descriptive Statistics Once you know what type of measurement scale the data were measured on, you can choose the most appropriate statistics to summarize them: Measures of central tendency: Most representative score Measures of dispersion: How far spread out scores are

3. Measures of Central Tendency Central tendency = Typical or representative value of a group of scores Mean: Average score Median: middlemost score; score at 50 th percentile; half the scores are above, half are below Mode: Most frequently occurring score(s)

4. Measures of Central Tendency MeasureDefinition Takes Every Value Into Account?When to Use Mean M =  X / n YesNumerical data BUT… Can be heavily influenced by outliers so can give inaccurate view if distribution is not (approximately) symmetric MedianMiddle valueNoOrdinal data or for numerical data that are skewed ModeMost frequent data value NoNominal data

5. Three Different Distributions That Have the Same Mean Sample ASample BSample C 086 276 666 1056 1246 Mean666

6. Measures of Variability Knowing what the center of a set of scores is is useful but…. How far spread out are all the scores? Were all scores the same or did they have some variability? Range, Standard deviation, Interquartile range

7. Variability = extent to which scores in a distribution differ from each other; are spread out

8. The Range as a Measure of Variability Difference between lowest score in the set and highest score Ages ranged from 27 to 56 years of age There was a 29-year age range The number of calories ranged from 256 to 781

9. Sample Standard Deviation Standard deviation = How far on “average” do the scores deviate around the mean? s = SD = In a normal distribution, 68% of the scores fall within 1 standard deviation of the mean (M  SD) The bigger the SD is, the more spread out the scores are around the mean

10. Variations of the Normal Curve (larger SD = wider spread)

11. Interquartile Range Quartile 1: 25 th percentile Quartile 2: 50 th percentile (median) Quartile 3: 75 th percentile Quartile 4: 100 th percentile Interquartile range = IQR = Score at 75 th percentile – Score at 25 th percentile So this is the midmost 50% of the scores

12. Interquartile Range on Positively (Right) Skewed Distribution IQR is often used for interval or ratio data that are skewed (do not want to consider ALL the scores)

13. Measures of Variability MeasureDefinition Takes Every Value Into Account?When to Use RangeHighest - lowest score No, only based on two most extreme values To give crude measure of spread Standard Deviation 68% of the data fall within 1 SD of the mean Yes, but describes majority For numerical data that are approximately symmetric or normal Interquartile Range Middle 50% of the data fall within the IQR No, but describes most When numerical data are skewed

14. Presenting Measures of Central Tendency and Variability in Text The number of fruit flies observed each day ranged from 0 to 57 (M = 25.32, SD = 5.08). Plants exposed to moderate amounts of sunlight were taller (M = 6.75 cm, SD = 1.32) than plants exposed to minimal sunlight (M = 3.45 cm, SD = 0.95). The response time to a patient’s call ranged from 0 to 8 minutes (M = 2.1, SD =.8)  Sentences should always be grammatical and sensible. Do not just list a bunch of numbers. Use the statistical information to supplement what you are saying

15. Presenting Measures of Central Tendency and Variability in Tables (Symmetric Data) RangeMSD Number of Fruit Flies0 to 5725.325.08 Weight (lbs)118 to 208160.3110.97 Response time to Patient’s Call (mins) 0 to 82.1.8 Be sure to include the units of measurement! You can include an additional column to put the sample size (N)

16. Presenting Measures of Central Tendency and Variability in Tables (Skewed Data) RangeMedianIQR Number of Fruit Flies0 to 57279 Weight (lbs)118 to 208155.612 Response time to Patient’s Call (mins) 0 to 81.51 Be sure to include the units of measurement! You can include an additional column to put the sample size (N)

17. What’s the Difference Between SD and SE? Sometimes instead of standard deviation, people report the standard error of the mean (SE or SEM) in text, tables, and figures Standard deviation (SD) = “Average” deviation of individual scores around mean of scores Used to describe the spread of your (one) sample Standard error (SE = SD/  N) = How much on average sample means would vary if you sampled more than once from the same population (we do not expect the particular mean we got to be an exact reflection of the population mean) Used to describe the spread of all possible sample means and used to make inferences about the population mean  Standard error usually looks better in figures because it is not as large

18. Dangers of low N: Be sure to emphasize to students that with a small sample size, data may not be representative of the population at large and they should take care in drawing conclusions Dangers of Outliers: Be sure your students look for outliers (extreme values) in their data and discuss appropriate strategies for dealing with them (e.g., eliminating data because the researcher assumes it is a mistake instead of part of the natural variability in the population = subjective science) Teaching Tips

19. Finding descriptive statistics Teaching tips: Hands-on practice is important for your students Sometimes working with a partner helps Time to Practice