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Descriptive Statistics: Numerical Methods, Part 1

Descriptive Statistics: Numerical Methods, Part 1. Measures of Location The Mean The Median The Mode Percentiles Quartiles. Mean. The mean (or average) is the basic measure of location or “central tendency” of the data. The sample mean is a sample statistic.

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Descriptive Statistics: Numerical Methods, Part 1

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  1. Descriptive Statistics: Numerical Methods, Part 1 • Measures of Location • The Mean • The Median • The Mode • Percentiles • Quartiles

  2. Mean The mean (or average) is the basic measure of location or “central tendency” of the data. • The sample meanis a sample statistic. • The population mean  is a population statistic.

  3. Sample Mean Where the numerator is the sum of values of n observations, or: The Greek letter Σ is the summation sign

  4. Example: College Class Size We have the following sample of data for 5 college classes: 46 54 42 46 32 We use the notation x1, x2, x3, x4, and x5 to represent the number of students in each of the 5 classes: X1 = 46 x2 = 54x3 = 42 x4 = 46 x5 = 32 Thus we have: The average class size is 44 students

  5. Population Mean () The number of observations in the population is denoted by the upper case N. The sample mean is a point estimator of the population mean 

  6. Median The median is the value in the middle when the data are arranged in ascending order (from smallest value to largest value). • For an odd number of observations the median is the middle value. • For an even number of observations the median is the average of the two middle values.

  7. The College Class Size example First, arrange the data in ascending order: 32 42 46 46 54 Notice than n = 5, an odd number. Thus the median is given by the middle value. 32 42 46 46 54 The median class size is 46

  8. Median Starting Salary For a Sample of 12 Business School Graduates A college placement office has obtained the following data for 12 recent graduates:

  9. First we arrange the data in ascending order 2710 2755 2850 2880 2880 2890 2920 2940 2950 3050 3130 3325 Notice that n = 12, an even number. Thus we take an average of the middle 2 observations: 2710 2755 2850 2880 2880 2890 2920 2940 2950 3050 3130 3325 Middle two values Thus

  10. Mode The mode is the value that occurs with greatest frequency The mode is Coke Classic. A mean or median is meaningless of qualitative data Soft Drink Example

  11. Using Excel to Compute the Mean, Median, and Mode • Enter the data into cells A1:B13 for the starting salary example. • To compute the mean, activate an empty cell and enter the following in the formula bar:=Average(b2:b13) and click the green checkmark. • To compute the median, activate an empty cell and enter the following in the formula bar:= Median(b2:b13) and click the green checkmark. • To compute the mode, activate an empty cell and enter the following in the formula bar:=Average(b2:b13) and click the green checkmark.

  12. The Starting Salary Example

  13. Percentiles The pth percentile is a value such that at least p percent of the observations are less than or equal to this value and at least (100 – p) percent of the observations are greater than or equal to this value. I scored in the 70th percentile on the Graduate Record Exam (GRE)—meaning I scored higher than 70 percent of those who took the exam

  14. Calculating the pth Percentile • Step 1: Arrange the data in ascendingorder (smallest value to largest value). • Step 2: Compute an index i where p is the percentile of interest and n in the number of observations. • Step 3: (a) If i is not an integer, round up. The next integer greater than i denotes the position of the pth percentile. (b) If i is an integer, the pth percentile is the average of values in i and i + 1

  15. Example: Starting Salaries of Business Grads Let’s compute the 85th percentile using the starting salary data. First arrange the data in ascending order. Step 1: 2710 2755 2850 2880 2880 2890 2920 2940 2950 3050 3130 3325 Step 2: Step 3: Since 10.2 in not an integer, round up to 11.The 85thpercentile is the 11th position (3130)

  16. Quartiles Quartiles are just specific percentiles Let: Q1 = first quartile, or 25th percentile Q2 = second quartile, or 50th percentile (also the median) Q3= third quartile, or 75th percentile Let’s compute the 1st and 3rd percentiles using the starting salary data. Note we already computed the median for this sample—so we know the 2nd quartile

  17. 2710 2755 2850 2880 2880 2890 2920 2940 2950 3050 3130 3325 Now find the 25th percentile: Note that 3 is an integer, so to find the 25th percentile we must average together the 3rd and 4th values: Q1 = (2850 + 2880)/2 = 2865 Now find the 75th percentile: Note that 9 is an integer, so to find the 75th percentile we must average together the 9th and 10th values: Q1 = (2950 + 3050)/2 = 3000

  18. Quartiles for the Starting Salary Data 2710 2755 2850 2880 2880 2890 2920 2940 2950 3050 3130 3325 Q1 = 2865 Q3 = 3000 Q1 = 2905 (Median)

  19. Using Excel to Compute Percentiles and Quartiles Enter Data: Labels and starting salary data are entered into cells A1:B13 • Step 1: Activate any cell containing data in column B. • Step 2: Select the Data menu • Step 3; When the Sort dialog box appears:Sort by box, make sure that Starting Salary appears andthat Ascending is selected> Click OK

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