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Statistics and central tendency

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Each of the three measures of central tendency-the mean, the median, and the mode-are more appropriate for certain populations than others.

For each type of measure, I need two additional examples of populations where it would be the most appropriate indication of central tendency.

I need to find the mean, median, and mode of the following data set:

5 15 9 22 67 42 2 72 81 53 6 70 41 9 42 23

Sometimes, we can take a weighted approach to calculating the mean. Take the example of high temperatures in July. Suppose it was 98°F on 7 days, 96°F on 14 days, 88°F on 1 day, 100°F on 6 days and 102°F on 3 days. Rather than adding up 31 numbers, we can find the mean by doing the following:

Mean = ( 1 x 88 + 14 x 96 + 7 x 98 + 6 x 100 + 3 x 102) / 31

...where 1, 14, 7, 6, and 3 are the weights or frequency of a particular temperature's occurrence. Then we divide by the total of number of occurrences.

Suppose we are tracking the number of home runs hit by the Boston Red Sox during the month of August:

Number of Games HRs Hit each Day

Games HR
2 3
5 2
6 1
7 0

Using the weighted approach, calculate the average number of home runs per game hit by the Sox.

When a pair of dice is rolled, the total will range from 2 (1,1) to 12 (6,6). It is a fact that some numbers will occur more frequently than others as the dice are rolled over and over.

Why will some numbers come up more frequently than others?

Each die has six sides numbered from 1 to 6. How many possible ways can a number be rolled? In other words, we can roll (2,3) or (3,2) or (6,1) and so on.

What are the total (x,y) outcomes that can occur?

How might you then estimate the percentage of the time a particular number will come up if the dice are rolled over and over?

Once these percentages have been calculated, how might the mean value of the all the numbers thrown be determined?

There is a very famous distribution that describes the frequency of the number of times a number comes up in a series of dice rolls. I need to see if I can find its name.

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Solution Summary

This provides several examples of how to work with various measures of central tendency.

Solution provided by:
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  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
  • "excellent work"
  • "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
  • "Thank you"
  • "Thank you very much for your valuable time and assistance!"
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