1 Elementary Statistics Larson Farber Descriptive Statistics Chapter 2.

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Presentation transcript:

1 Elementary Statistics Larson Farber Descriptive Statistics Chapter 2

2 Frequency Distributions Make a frequency distribution table with five classes. Minutes Spent on the Phone Key values: Minimum value = Maximum value =

3 §Decide on the number of classes ( For this problem use 5)5) §Calculate the Class Width l ( ) / 5 = 11.6 Round up to 12 §Determine Class Limits §Mark a tally in appropriate class for each data value Frequency Distributions  f = Do all lower class limits first. Class Limits Tally f

4 (67+ 78)/2 3/ Midpoint: (lower limit + upper limit) / 2 Relative frequency: class frequency/total frequency Cumulative frequency: Number of values in that class or in lower one. Other Information Midpoint Relative frequency Class f Cumulative frequency

5 Boundaries Frequency Histogram Time on Phone minutes f Class f

6 Frequency Polygon Time on Phone minutes f Class f Mark the midpoint at the top of each bar. Connect consecutive midpoints. Extend the frequency polygon to the axis.

7 Relative Frequency Histogram Time on Phone minutes Relative frequency Relative frequency on vertical scale

8 Ogive An ogive reports the number of values in the data set that are less than or equal to the given value, x Cumulative Frequency minutes Minutes on Phone

9 Stem-and-Leaf Plot 6 | 7 | 8 | 9 | 10| 11| 12| Stem Leaf Lowest value is 67 and highest value is 125, so list stems from 6 to

10 Stem-and-Leaf Plot 6 |7 7 |1 8 8 | | | | |2 4 5 Key: 6 | 7 means 67

11 Stem-and-Leaf with t wo lines per stem 6 | 7 7 | 1 7 | 8 8 | 2 8 | | 2 9 | | | | 2 11 | | | 5 Key: 6 | 7 means 67 1st line digits nd line digits st line digits nd line digits

12 Dotplot Phone minutes

13 The 1995 NASA budget (billions of $) divided among 3 categories. Pie Chart §Used to describe parts of a whole §Central Angle for each segment Construct a pie chart for the data.

14 Pie Chart 5.7/14.3*360 o = 143 o 5.9/14.3*360 o = 149 o Total

15 Measures of Central Tendency Mean: The sum of all data values divided by the number of values For a population: For a sample : Median: The point at which an equal number of values fall above and fall below Mode: The value with the highest frequency

Calculate the mean, the median, and the mode n = 9 Mean: Median: Sort data in order The middle value is 3, so the median is 3.3. Mode: The mode is 2 since it occurs the most times. An instructor recorded the average number of absences for his students in one semester. For a random sample the data are:

Calculate the mean, the median, and the mode n =8 Mean: Median: Sort data in order The middle values are 2 and 3, so the median is 2.5 Mode: The mode is 2 since it occurs the most. Suppose the student with 40 absences is dropped from the course. Calculate the mean, median and mode of the remaining values. Compare the effect of the change to each type of average

18 Shapes of Distributions Uniform Symmetric Skewed rightSkewed left Mean > medianMean < median Mean = median

19 Descriptive Statistics Closing prices for two stocks were recorded on ten successive Fridays. Calculate the mean, median and mode for each. Mean = 61.5 Median =62 Mode= 67 Mean = 61.5 Median =62 Mode= Stock AStock B

20 Range for A = = $11 Range = Maximum value - Minimum value Range for B = = $57 The range only uses 2 numbers from a data set. The deviation for each value x is the difference between the value of x and the mean of the data set. In a population, the deviation for each value x is: x -  In a sample, the deviation for each value x is: Measures of Variation

Deviations µ =  ( x - µ) = 0 Stock ADeviation The sum of the deviations is always zero.

22 Population Variance: The sum of the squares of the deviations, divided by N. Stock A Sum of squares Population Variance

23 Population Standard Deviation Population Standard Deviation The square root of the population variance. The population standard deviation is $4.34

24 Calculate the measures of variation for Stock B Sample Standard Deviation To calculate a sample variance divide the sum of squares by n-1. The sample standard deviation, s is found by taking the square root of the sample variance.

25 Summary Population Standard Deviation Sample Variance Sample Standard Deviation Range = Maximum value - Minimum value Population Variance

26 Empiricl Rule % rule Data with symmetric bell-shaped distribution has the following characteristics. About 68% of the data lies within 1 standard deviation of the mean About 99.7% of the data lies within 3 standard deviations of the mean About 95% of the data lies within 2 standard deviations of the mean % 2.35% 68%

27 Using the Empirical Rule The mean value of homes on a street is $125 thousand with a standard deviation of $5 thousand. The data set has a bell shaped distribution. Estimate the percent of homes between $120 and $135 thousand 68% 13.5% 68% $120 is 1 standard deviation below the mean and $135 thousand is 2 standard deviation above the mean. 68% % = 81.5% So, 81.5% of the homes have a value between $120 and $135 thousand %

28 Chebychev’s Theorem For k = 3, at least 1-1/9 = 8/9= 88.9% of the data lies within 3 standard deviation of the mean. For any distribution regardless of shape the portion of data lying within k standard deviations (k >1) of the mean is at least 1 - 1/k 2.  =6  =3.84 For k = 2, at least 1-1/4 = 3/4 or 75% of the data lies within 2 standard deviation of the mean.

29 Chebychev’s Theorem The mean time in a women’s 400-meter dash is 52.4 seconds with a standard deviation of 2.2 sec. Apply Chebychev’s theorem for k = standard deviations At least 75% of the women’s 400- meter dash times will fall between 48 and 56.8 seconds. Mark a number line in standard deviation units.

30 Grouped Data Class fMidpoint (x) To approximate the mean of data in a frequency distribution, treat each value as if it occurs at the midpoint of its class. x = Class midpoint. x f

31 Grouped Data To approximate the standard deviation of data in a frequency distribution, use x = class midpoint Class fMidpoint

32 Quartiles You are managing a store. The average sale for each of 27 randomly selected days in the last year is given. Find Q 1, Q 2 and Q quartiles Q 1, Q 2 and Q 3 divide the data into 4 equal parts. Q 2 is the same as the median. Q 1 is the median of the data below Q 2 Q 3 is the median of the data above Q 2

33 The data in ranked order (n = 27) are: Quartiles Median rank (27 +1)/2 = 14. The median = Q 2 = 42. There are 13 values below the median. Q 1 rank= 7. Q 1 is 30. Q 3 is rank 7 counting from the last value. Q 3 is 45. The Interquartile Range is Q 3 - Q 1 = = 15

34 Box and Whisker Plot A box and whisker plot uses 5 key values to describe a set of data. Q 1, Q 2 and Q 3, the minimum value and the maximum value. Q 1 Q 2 = the median Q 3 Minimum value Maximum value Interquartile Range

35 Percentiles Percentiles divide the data into 100 parts. There are 99 percentiles: P 1, P 2, P 3 …P 99. A 63nd percentile score indicates that score is greater than or equal to 63% of the scores and less than or equal to 37% of the scores. P 50 = Q2 Q2 = the median P 25 = Q1Q1 P 75 = Q3Q3

36 Percentiles falls on or above 25 of the 30 values. 25/30 = So you can approximate 114 = P 83. Cumulative distributions can be used to find percentiles.