1. Statistics 1 Measures of central tendency and measures of spread

2. Data vs. Statistics Data is: Statistics are: mean, median, mode, range, variance, and standard deviation. numbers that gives information about a population (or a sample of the population). Examples of statistics are: information that is gathered from a population (or a sample of the population).

3. Measures of Central Tendency Three measures of central tendency, or “averages”, are used to describe data. Mean, Median and Mode

4. Measures of Central Tendency The arithmetic mean (the mean) of a set of numbers is the sum of the numbers, divided by the total number of numbers. The median is the middle entry in a set of data arranged in either increasing or decreasing order. If there is an even number of entries, the median is defined to be the mean of the two center entries. The mode is the most frequently occurring entry, or entries, in a set of data. If there is no one entry that occurs more than the others we say there is no mode. Sometimes, the data set will have more than one mode.

5. Example The ages of university students in a tutorial group are 20, 23, 18, 19, 28, 26, 22, 18 What is the average age? Mean = Median → Median = (20+22)/2 = 21 Mode = 18 18, 18, 19, 20, 22, 23, 26, 28

6. Example Find the ‘average’ speed along Mayberry Highway, in miles per hour? 4539554252 3946615433 50472957 60

7. Example Find the ‘average’ speed along Mayberry Highway, in miles per hour? 4539554252 3946615433 50472957 60 Mean = Median →29, 33, 39, 39, 42, 45, 46, 47, 50, 52, 54, 55, 57, 60, 61 Median = 47 mph Mode = 39 mph USE YOUR CALCULATOR

8. Two Types of Mean Sample mean: mean of a random sample. This mean is used most often when the population is very large. Denoted by x Population mean: mean for the entire population. The expected value of a random variable in a probability distribution is sometimes called the population mean. Denoted by µ. (Greek letter “mu”)

9. Mean formula where f = frequency x = variable

10. Who Has Better Scores? Adam and Bonnie are comparing their quiz scores in an effort to determine who is the “best”. Help them decide by calculating the mean, median, and mode for each. Adam’s ScoresBonnie’s Scores 8581 6085 1058685 7290 10080

11. The Winner? AdamBonnie Mean84.5 Median85 Mode85 So, who has the better quiz scores?

12. Another Way to Compare Sometimes the measures of central tendency (mean, median, mode) aren’t enough to adequately describe the data. We also need to take into account the consistency, or spread, of the data.

13. Range The range of the data is the difference between the largest and smallest number in a sample. Find the range of Adam and Bonnie’s scores. Adam: 105 – 60 = 45 Bonnie: 90 – 80 = 10 Based on the range, Bonnie’s scores are more consisent, and some might argue therefore, better than Adam’s.

14. Another Measure of Dispersion The most useful measure of variation (spread) is the standard deviation. First, we will look at the deviations from the mean.

15. Deviations from the Mean The deviation from the mean is the difference between a single data point and the calculated mean of the data. Data point close to mean: small deviation Data point far from mean: large deviation Sum of deviations from mean is always zero. Mean of the deviations is always zero.

16. Deviations from Mean for Adam and Bonnie Data Point Deviation from Mean 8585 - 84.5 = 0.5 6060 – 84.5 = -24.5 105105 – 84.5 = 20.5 8585 – 84.5 = 0.5 7272 – 84.5 = -12.5 100100 – 84.5 = 15.5 Sum = 0 Adam Data Point Deviation from Mean 8181 - 84.5 = -3.5 8585 – 84.5 = 0.5 8686 – 84.5 = 1.5 8585 – 84.5 = 0.5 9090 – 84.5 = 5.5 8080 – 84.5 = -4.5 Sum = 0 Bonnie

17. Variance Because the average of the mean deviation is always zero, we must modify our approach using the variance. The variance is the mean of the squares of the deviation.

18. Variance for Adam and Bonnie’s Scores Using the deviations from the mean we have already calculated for Adam and Bonnie, we will find the variance for each. Adam : s² = Bonnie: s² = s² = 1417.5 6 = 237 s² = 65.5 6 = 10.9

19. Standard Deviation To find the variance, we squared the deviations from the mean, so the variance is in squared units. To return to the same units as the data, we use the square root of the variance, the standard deviation. Standard Deviation Variance

20. Adam and Bonnie’s Standard Deviation Adam: s = √237 = 15.4 Bonnie: s = √10.9 = 3.30 Based on the standard deviation, Bonnie’s scores are better because there is less dispersion. In other words, she is more consistent than Adam.

21. Example = 1.80 Mean = 16.5

22. The meaning of standard deviation A small SD means the data is grouped closely together A large SD means the data is spread widely Approximately 68% of all data is within one SD of the mean (when normally distributed) Approximately 99% of all data is within two SDs of the mean (when normally distributed)

23. Now practice using your calc to find mean, median, mode & std dev Go to page 399 Exercise 15 C Every Question