Skip to main content
K12 LibreTexts

4.1: Introduction to Mean, Median, and Mode

  • Page ID
    5715
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

    ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\id}{\mathrm{id}}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\kernel}{\mathrm{null}\,}\)

    \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\)

    \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\)

    \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    \( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

    \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

    \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vectorC}[1]{\textbf{#1}} \)

    \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

    \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

    \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

    \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)

    Measures of Central Tendency and Dispersion

    Suppose the heights in inches of the students in your class are as follows: 58, 58, 59, 60, 62, 64, 64, 65, 66, 66, 66, 66, 68, 68, 69, 70, 71, 72, 72, 74, 75, 77. What would be the mean of this data? How about the median and mode? Would you be able to calculate the variance for this data? How about the standard deviation?


    Central Tendency and Dispersion

    The majority of this textbook centers upon two-variable data, data with an input and an output. This is also known as bivariate data. There are many types of situations in which only one set of data is given. This data is known as univariate data. Unlike data you have seen before, no rule can be written relating univariate data. Instead, other methods are used to analyze the data. Three such methods are the measures of central tendency.

    Measures of central tendency are the center values of a data set.

    • Mean is the average of all the data. Its symbol is x¯.
    • Mode is the data value appearing most often in the data set.
    • Median is the middle value of the data set, arranged in ascending order.

    Let's find the mean, median, and mode of the following data representing test scores:

    90, 76, 53, 78, 88, 80, 81, 91, 99, 68, 62, 78, 67, 82, 88, 89, 78, 72, 77, 96, 93, 88, 88

    Find the mean, median, mode, and range of this data.

    • To find the mean, add all the values and divide by the number of values you added.

    mean=80.96

    • To find the mode, look for the value(s) repeating the most.

    mode=88

    • To find the median, organize the data from least to greatest. Then find the middle value.

    53, 62, 62, 67, 68, 72, 76, 77, 78, 78, 78, 78, 80, 81, 82, 88, 88, 88, 88, 89, 90, 91, 93, 96, 99

    median=81

    • To find the range, subtract the highest value and the lowest value.

    range=99−53=46

    When a data set has two modes, it is bimodal.

    If the data does not have a “middle value,” the median is the average of the two middle values. This occurs when data sets have an even number of entries.

    Which Measure Is Best?

    While the mean, mode, and median represent centers of data, one is usually more beneficial than another when describing a particular data set.

    For example, if the data has a wide range, the median is a better choice to describe the center than the mean.

    • The income of a population is described using the median, because there are very low and very high incomes in one given region.

    If the data were categorical, meaning it can be separated into different categories, the mode may be a better choice.

    • If a sandwich shop sold ten different sandwiches, the mode would be useful to describe the favorite sandwich.

    Measures of Dispersion

    In statistics, measures of dispersion describe how spread apart the data is from the measure of center. There are three main types of dispersion:

    • Variance - the mean of the squares of the distance each data item (xi) is from the mean.

    σ2=(x1−x¯)2+(x2−x¯)2+…+(xn−x¯)2n

    The symbol for variance is σ2.

    • Standard deviation - the square root of the variance.
    • Range - the difference between the highest and lowest values in the data.

    Let's find the variance for the following data: 11, 13, 14, 15, 19, 22, 24, 26:

    First find the mean (x¯).

    x¯=11+13+14+15+19+22+24+268=18

    It’s easier to create a table of the differences and their squares.

    xi xi−x¯ (x1−x¯)2
    11 –7 49
    13 –5 25
    14 –4 16
    15 –3 9
    19 1 1
    22 4 16
    24 6 36
    26 8 64

    Compute the variance:

    Screen Shot 2020-05-27 at 8.55.09 PM.png

    The variance is a measure of the dispersion and its value is lower for tightly grouped data than for widely spread data. In the example above, the variance is 27. What does it mean to say that tightly grouped data will have a low variance? You can probably already imagine that the size of the variance also depends on the size of the data itself. Below we see ways that mathematicians have tried to standardize the variance.

    The Standard Deviation

    Standard deviation measures how closely the data clusters around the mean. It is the square root of the variance. Its symbol is σ.

    Screen Shot 2020-05-27 at 9.02.36 PM.png

    Now, let's calculate the standard deviation of the data set that you found the variance of:

    The standard deviation is the square root of the variance.

    σ2=27 so σ=5.196

    Examples

    Example 1

    Earlier, you were asked what the mean, median, and mode of the heights of the students in your class would be. Additionally, you were asked if you could calculate the variance and standard deviation for this data.

    The heights in inches of the students in your class are as follows: 58, 58, 59, 60, 62, 64, 64, 65, 66, 66, 66, 66, 68, 68, 69, 70, 71, 72, 72, 74, 75, 77.

    • To find the mean, add all the values and divide by the total number of values (22 in this case).

    Mean=66.81

    • To find the mode, look for the value(s) that repeat the most.

    Mode=66

    • To find the median, organize the data from least to greatest. Then find the middle value.

    This data set is already organized from least to greatest, so you can go straight to finding the middle value.

    Median=66

    • To find the variance, calculate the mean of the squares of the distance each value is from the mean.

    Screen Shot 2020-05-27 at 9.03.47 PM.png

    It's easiest to set this up in a table.

    xi xi−x¯ (x1−x¯)2
    58 -8.81 77.6161
    58 -8.81 77.6161
    59 -8.81 77.6161
    60 -6.81 46.3761
    62 -4.81 23.1361
    64 -2.81 7.8961
    64 -2.81 7.8961
    65 -1.81 3.2761
    66 -0.81 0.6561
    66 -0.81 0.6561
    66 -0.81 0.6561
    66 -0.81 0.6561
    68 1.19 1.4161
    68 1.19 1.4161
    69 2.19 4.7961
    70 3.19 10.1761
    71 4.19 17.5561
    72 5.19 26.9361
    72 5.19 36.9361
    74 7.19 51.6961
    75 8.19 67.0761
    77 10.19 103.8361

    Now, plug these values into the equation for variance and solve.

    Variance=28.15

    • To find the standard deviation, take the square root of the variance.

    Standard deviation=28.150.5=5.31

    Example 2

    Find the mean, median, mode, range, variance, and standard deviation of the data set below.

    Address Sale Price
    518 CLEVELAND AVE $117,424
    1808 MARKESE AVE $128,000
    1770 WHITE AVE $132,485
    1459 LINCOLN AVE $77,900
    1462 ANNE AVE $60,000
    2414 DIX HWY $250,000
    1523 ANNE AVE $110,205
    1763 MARKESE AVE $70,000
    1460 CLEVELAND AVE $111,710
    1478 MILL ST $102,646

    Screen Shot 2020-05-27 at 9.06.36 PM.png

    Use a table to find variance.

    xi xi−x¯ (x1−x¯)2
    117,424 1387 1,923,769
    128,000 11,963 143,113,369
    132,485 16,448 270,536,704
    77,900 –38,137 1,454,430,769
    60,000 –56,037 3,140,145,369
    250,000 133,963 1.7946×1010
    110,205 –5832 34,012,224
    70,000 –46,037 2,119,405,369
    111,710 –4327 18,722,929
    102,646 –13,391 179,318,881

    variance=2,530,769,498

    standard deviation=50,306.754


    Review

    1. Define measures of central tendency. What are the three listed in this Concept?
    2. Define median. Explain its difference from the mean. In which situations is the median more effective to describe the center of the data?
    3. What is bimodal? Give an example of a set of data that is bimodal.
    4. What are the three measures of dispersion described in this Concept? Which is the easiest to compute?
    5. Give the formula for variance and define its variables.
    6. Why may variance be difficult to use as a measure of spread? Use the housing example to help you explain.
    7. Describe standard variation.
    8. Explain why the standard deviation of 2, 2, 2, 2, 2, 2, and 2 is zero.
    9. Find the mean, median, and range of the salaries given below.
    Professional Realm Annual income
    Farming, Fishing, and Forestry $19,630
    Sales and Related $28,920
    Architecture and Engineering $56,330
    Healthcare Practitioners $49,930
    Legal $69,030
    Teaching & Education $39,130
    Construction $35,460
    Professional Baseball Player* $2,476,590

    (Source: Bureau of Labor Statistics, except (*) - The Baseball Players' Association (playbpa.com)).

    Find the mean, median, mode,and range of the following data sets.

    1. 11, 16, 9, 15, 5, 18
    2. 53, 32, 49, 24, 62
    3. 11, 9, 19, 9, 19, 9, 13, 11
    4. 3, 2, 6, 9, 0, 1, 6, 6, 3, 2, 3, 5
    5. 2, 17, 1, –3, 12, 8, 12, 16
    6. 11, 21, 6, 17, 9.
    7. 223, 121, 227, 433, 122, 193, 397, 276, 303, 199, 197, 265, 366, 401, 222

    Find the mean, median, and standard deviation of the following numbers. Which, of the mean and median, will give the best average?

    1. 15, 19, 15, 16, 11, 11, 18, 21, 165, 9, 11, 20, 16, 8, 17, 10, 12, 11, 16, 14
    2. 11, 12, 14, 14, 14, 14, 19
    3. 11, 12, 14, 16, 17, 17, 18
    4. 6, 7, 9, 10, 13
    5. 121, 122, 193, 197, 199, 222, 223, 227, 265, 276, 303, 366, 397, 401, 433
    6. If each score on an algebra test is increased by seven points, how would this affect the:
      1. Mean?
      2. Median?
      3. Mode?
      4. Range?
      5. Standard deviation?
    1. If each score of a golfer was multiplied by two, how would this affect the:
      1. Mean?
      2. Median?
      3. Mode?
      4. Range?
    1. Henry has the following World History scores: 88, 76, 97, 84. What would Henry need to score on his fifth test to have an average of 86?
    2. Explain why it is not possible for Henry to have an average of 93 after his fifth score.
    3. The mean of nine numbers is 105. What is the sum of the numbers?
    4. A bowler has the following scores: 163, 187, 194, 188, 205, 196. Find the bowler’s average.
    5. Golf scores for a nine-hole course for five different players were: 38, 45, 58, 38, 36.
      1. Find the mean golf score.
      2. Find the standard deviation to the nearest hundredth.
      3. Does the mean represent the most accurate center of tendency? Explain.
    1. Ten house sales in Encinitas, California are shown in the table below. Find the mean, median, and standard deviation for the sale prices. Explain, using the data, why the median house price is most often used as a measure of the house prices in an area.
    Address Sale Price Date Of Sale
    643 3RD ST $1,137,000 6/5/2007
    911 CORNISH DR $879,000 6/5/2007
    911 ARDEN DR $950,000 6/13/2007
    715 S VULCAN AVE $875,000 4/30/2007
    510 4TH ST $1,499,000 4/26/2007
    415 ARDEN DR $875,000 5/11/2007
    226 5TH ST $4,000,000 5/3/2007
    710 3RD ST $975,000 3/13/2007
    68 LA VETA AVE $796,793 2/8/2007
    207 WEST D ST $2,100,000 3/15/2007
    1. Determine which statistical measure (mean, median, or mode) would be most appropriate for the following.
      1. The life expectancy of store-bought goldfish.
      2. The age in years of the audience for a kids' TV program.
      3. The weight of potato sacks that a store labels as “5-pound bag.”
    1. James and John both own fields in which they plant cabbages. James plants cabbages by hand, while John uses a machine to carefully control the distance between the cabbages. The diameters of each grower’s cabbages are measured, and the results are shown in the table. John claims his method of machine planting is better. James insists it is better to plant by hand. Use the data to provide a reason to justify both sides of the argument.
    James John
    Mean Diameter (inches) 7.10 6.85
    Standard Deviation (inches) 2.75 0.60
    1. Two bus companies run services between Los Angeles and San Francisco. The mean journey times and standard deviations in those times are given below. If Samantha needs to travel between the cities, which company should she choose if:
      1. She needs to catch a plane in San Francisco.
      2. She travels weekly to visit friends who live in San Francisco and wishes to minimize the time she spends on a bus over the entire year.
    Inter-Cal Express Fast-dog Travel
    Mean Time (hours) 9.5 8.75
    Standard Deviation (hours) 0.25 2.5

    Mixed Review

    1. A square garden has dimensions of 20 yards by 20 yards. How much shorter is it to cut across the diagonal than to walk around two joining sides?
    2. Rewrite in standard form: y=x/6−5.
    3. Solve for m: −2=(x+7).25
    4. A sail has a vertical length of 15 feet and a horizontal length of 8 feet. To the nearest foot, how long is the diagonal?
    5. Rationalize the denominator: 220.5.

    Review (Answers)

    To see the Review answers, open this PDF file and look for section 11.9.


    Vocabulary

    Term Definition
    bivariate data So far we have seen two-variable data, which is data with an input and an output. This is also known as bivariate data.
    measures of dispersion In statistics, measures of dispersion describe how spread apart the data is from the measure of center. There are three main types of dispersion:
    Median The median of a data set is the middle value of an organized data set.
    range Difference between highest and lowest values in data.
    standard deviation The square root of the variance.
    univariate data There are many types of situations in which only one set of data is given. This data is known as univariate data.
    variance is the mean of the squares of the distance each data item is from the mean, or σ2.
    arithmetic mean The arithmetic mean is also called the average.
    descriptive statistics In descriptive statistics, the goal is to describe the data that found in a sample or given in a problem.
    inferential statistics With inferential statistics, your goal is use the data in a sample to draw conclusions about a larger population.
    measure of central tendency In statistics, a measure of central tendency of a data set is a central or typical value of the data set.
    Mode The mode of a data set is the value or values with greatest frequency in the data set.
    multimodal When a set of data has more than 2 values that occur with the same greatest frequency, the set is called multimodal .
    Outlier In statistics, an outlier is a data value that is far from other data values.
    Population Mean The population mean is the mean of all of the members of an entire population.
    resistant A statistic that is not affected by outliers is called resistant.
    Sample Mean A sample mean is the mean only of the members of a sample or subset of a population.

    Additional Resources

    PLIX: Play, Learn, Interact, eXplore - The Tree Conundrum

    Video: Mean, Median, and Mode

    Activities: Measure of Central Tendency and Dispersion Discussion Questions

    Study Aid: Describing Data

    Practice: Introduction to Mean, Median, and Mode

    Real World: Mean or Median?


    This page titled 4.1: Introduction to Mean, Median, and Mode is shared under a CK-12 license and was authored, remixed, and/or curated by CK-12 Foundation via source content that was edited to the style and standards of the LibreTexts platform.

    CK-12 Foundation
    LICENSED UNDER
    CK-12 Foundation is licensed under CK-12 Curriculum Materials License