Copyright © 2009 Pearson Education, Inc. 4.1 What Is Average? LEARNING GOAL Understand the difference between a mean, median, and mode and how each is.

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Copyright © 2009 Pearson Education, Inc. 4.1 What Is Average? LEARNING GOAL Understand the difference between a mean, median, and mode and how each is affected by outliers. Also understand how these different types of “average” can lead to confusion and when it is appropriate to use a weighted mean.

Slide Copyright © 2009 Pearson Education, Inc. Mean, Median, and Mode Definitions—Measures of Center in a Distribution The mean is what we most commonly call the average value. It is found as follows: The median is the middle value in the sorted data set (or halfway between the two middle values if the number of values is even). The mode is the most common value (or group of values) in a data set. sum of all values total number of values mean =

Slide Copyright © 2009 Pearson Education, Inc. Figure 4.1 A histogram made from blocks would balance at the position of its mean.

Slide Copyright © 2009 Pearson Education, Inc. Rounding Rule for Statistical Calculations State your answers with one more decimal place of precision than is found in the raw data. Example: The mean of 2, 3, and 5 is , which we round to 3.3. Because the raw data are whole numbers, we round to the nearest tenth. As always, round only the final answer and not any intermediate values used in your calculations.

Slide Copyright © 2009 Pearson Education, Inc. EXAMPLE 1 Price Data Eight grocery stores sell the PR energy bar for the following prices: $1.09 $1.29 $1.29 $1.35 $1.39 $1.49 $1.59 $1.79 Find the mean, median, and mode for these prices. Solution: The mean price is $1.41: mean = = $1.41 $ $ $ $ $ $ $ $1.79 8

Solution: (cont.) To find the median, we first sort the data in ascending order: Because there are eight prices (an even number), there are two values in the middle of the list: $1.35 and $1.39. Therefore the median lies halfway between these two values, which we calculate by adding them and dividing by 2: Using the rounding rule, we could express the mean and median as $1.410 and $1.370 respectively. Slide Copyright © 2009 Pearson Education, Inc. EXAMPLE 1 Price Data $ $ median = = $ values below 2 middle values 3 values above

Slide Copyright © 2009 Pearson Education, Inc. EXAMPLE 1 Price Data Solution: (cont.) The mode is $1.29 because this price occurs more times than any other price.

Slide Copyright © 2009 Pearson Education, Inc. TECHNICAL NOTE If the measure of center has the same number of significant digits as the original data, you can either include an extra zero or use the exact result without the extra decimal place. For example, the mean of 2 and 4 can be expressed as 3 or 3.0.

To explore the differences among the mean, median, and mode, imagine that the five graduating seniors on a college basketball team receive the following first-year contract offers to play in the National Basketball Association (zero indicates that the player did not receive a contract offer): $3,500,000 The mean contract offer is mean = = $700,000 Slide Copyright © 2009 Pearson Education, Inc. Effects of Outliers $3,500,000 5

Slide Copyright © 2009 Pearson Education, Inc. Effects of Outliers Is it therefore fair to say that the average senior on this basketball team received a $700,000 contract offer? Not really. The problem is that the single player receiving the large offer makes the mean much larger than it would be otherwise. If we ignore this one player and look only at the other four, the mean contract offer is zero.

Slide Copyright © 2009 Pearson Education, Inc. Definition An outlier in a data set is a value that is much higher or much lower than almost all others. In general, the value of an outlier has no effect on the median, because outliers don’t lie in the middle of a data set. Outliers do not affect the mode either. (However, the median may change if we delete an outlier, because we are changing the number of values in the data set.)

Slide Copyright © 2009 Pearson Education, Inc.

Slide Copyright © 2009 Pearson Education, Inc. Confusion About “Average” A newspaper surveys wages for workers in regional high-tech companies and reports an average of $22 per hour. The workers at one large firm immediately request a pay raise, claiming that they work as hard as employees at other companies but their average wage is only $19. The management rejects their request, telling them that they are overpaid because their average wage, in fact, is $23. Can both sides be right? Explain. EXAMPLE 4 Wage Dispute

Slide Copyright © 2009 Pearson Education, Inc. Solution: EXAMPLE 4 Wage Dispute Both sides can be right if they are using different definitions of average. In this case, the workers may be using the median while the management uses the mean. For example, imagine that there are only five workers at the company and their wages are $19, $19, $19, $19, and $39. The median of these five wages is $19 (as the workers claimed), but the mean is $23 (as management claimed).

Slide Copyright © 2009 Pearson Education, Inc. Weighted Mean Suppose your course grade is based on four quizzes and one final exam. Each quiz counts as 15% of your final grade, and the final counts as 40%. Your quiz scores are 75, 80, 84, and 88, and your final exam score is 96. What is your overall score? weighted mean = = = Following the rounding rule, we round this score to (75 × 15) + (80 × 15) + (84 × 15) + (88 × 15) + (96 × 40)

Slide Copyright © 2009 Pearson Education, Inc. Definition A weighted mean accounts for variations in the relative importance of data values. Each data value is assigned a weight and the weighted mean is weighted mean = sum of (each data value x its weight) sum of all weights

Because the weights are percentages in the course grade example, we could think of the weights as 0.15 and 0.40 rather than 15 and 40. Calculate the weighted mean by using the weights of 0.15 and Do you still find the same answer? Why or why not? Slide Copyright © 2009 Pearson Education, Inc. TIME OUT TO THINK

Slide Copyright © 2009 Pearson Education, Inc. Means with Summation Notation (Optional Section) The symbol Σ (the Greek capital letter sigma) is called the summation sign and indicates that a set of numbers should be added. We use the symbol x to represent each value in a data set, so we write the sum of all the data values as sum of all values = Σx

Slide Copyright © 2009 Pearson Education, Inc. We use n to represent the total number of values in the sample. Thus, the general formula for the mean is The symbol x is the standard symbol for the mean of a sample. When dealing with the mean of a population rather than a sample, statisticians instead use the Greek letter μ (mu). x = sample mean = = sum of all values total number of values Σx n

Slide Copyright © 2009 Pearson Education, Inc. Summation notation also makes it easy to express a general formula for the weighted mean. weighted mean = Σ(x × w) Σw

Slide Copyright © 2009 Pearson Education, Inc. Means and Medians with Binned Data (Optional Section) The ideas of this section can be extended to binned data simply by assuming that the middle value in the bin represents all the data values in the bin. For example, consider the following table of 50 binned data values: BinFrequency

Slide Copyright © 2009 Pearson Education, Inc. BinFrequency The middle value of the first bin is 3, so we assume that the value of 3 occurs 10 times. Continuing this way, we have for the total of the 50 values in the table (3 × 10) + (10 × 10) + (17 × 10) + (24 × 20) = 780 Thus, the mean is 780/50 = 15.6.

Slide Copyright © 2009 Pearson Education, Inc. BinFrequency With 50 values, the median is between the 25 th and 26 th values. These values fall within the bin 14–20, so we call this bin the median class for the data. The mode is the bin with the highest frequency—the bin in this case.

Slide Copyright © 2009 Pearson Education, Inc. The End