Mean, Median, and Mode (Measures of Center)
A measure of center is one number that summarizes a whole list of numbers. There are three:
- Mean (the average): add up all the values, then divide by how many values there are.
- Median: the middle value once the numbers are put in order. If there are two middle values, take their mean (add them and divide by ).
- Mode: the value that appears most often. A data set can have one mode, several modes, or no mode at all.
Statistics summarizes data with a center (mean, median, mode) and a spread (range). Probability measures how likely an event is, as a fraction of equally likely outcomes: favorable over total. Listing the outcomes — a table for two dice, a tree for coin flips — is the reliable way to count them.
The three centers answer three different questions. The mean is the balance point: if the dots were equal weights on a ruler, the ruler would balance at the mean, because the distances below it exactly cancel the distances above it ( and sit below ; , , sit , , above, and ). The median is the middle position, and the mode is the most popular value.
Find the mean, median, and mode of .
Order first: .
Mean: .
Median: the middle of five ordered numbers is the rd one, so median .
Mode: appears twice, more than any other, so mode .
Taking the middle of the list as written: for , "the median is ." The median is the middle of the ORDERED list, , which is .
Find the median of . Order them: . There are two middle values, and , so the median is their mean: . Notice the median need not be a value in the list.
- Use the mean when the data are fairly even, with no extreme values.
- Use the median when there is an outlier (a value far from the rest), because the median is not pulled toward it.
- Use the mode for things you count or categories, like the most common shoe size or favorite color.
Four friends have $, $, $, and $. Mean ; median . Now a fifth friend joins with $ (an outlier). New mean , but the ordered list has median . The single big value pulled the mean way up, while the median barely moved. That is why the median better describes a “typical” friend here.
Tip: Always put the numbers in order before you find the median. Forgetting to order the data is the most common mistake in this whole topic.
The mean of four test scores is . Three of them are , and . What is the fourth score?
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A mean of over scores means the total is . The three known scores add to , so the fourth is .
Range (A Measure of Spread)
The range tells how spread out the data are. It is the largest value minus the smallest value:
A small range means the values are close together; a large range means they are spread far apart.
A center alone hides how consistent the data are: the scores and have the same mean and median, but the second set is far more spread out. The range measures that spread in the simplest way, as the width of the whole data set on the number line. Because it uses only the two extremes, one unusual value can change it a lot.
Test scores were . The maximum is and the minimum is , so the range .
Subtracting the first and last values as listed: . The range uses the largest and smallest values, wherever they appear: . A range is never negative.
Tip: Range is a single number, not an interval. Say “the range is ,” not “the range is to .”
Set A is and set B is . Compare their means and their ranges.
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Both means are : each. Set A has range (no spread at all); set B has range . Same center, very different spread.
Reading and Making Graphs
Different graphs are good for different jobs:
- Bar graph: compares separate categories (favorite fruits, sports). Taller bar means larger amount.
- Line graph: shows how something changes over time (temperature through the day). Look at whether the line rises, falls, or stays flat.
- Circle (pie) graph: shows parts of one whole. All the slices together make of the total.
- Dot plot / line plot: an or dot stacked above a number line for each data value; great for seeing repeats and the shape of the data.
- Frequency table: lists each value or category next to how many times it occurs (its frequency).
Each kind of graph makes one comparison easy by turning it into something the eye judges well: bar heights for comparing categories, the slope of a line for change over time, slice sizes for parts of a whole, and stacked dots for how data are distributed. Picking a graph means asking which comparison the reader should see first.
A class recorded how many pets each student has:
The frequency row tells us students answered. The mode is pet (highest frequency, ). The dot plot stacks dots above , dots above , and so on. To find the total number of pets, multiply each value by its frequency and add: pets, so the mean is pets.
Averaging the frequency row: " pets." Those numbers count students, not pets. The mean number of pets weights each value by how many students have it: .
A circle graph of how students get to school shows Walk , Bus , Car . Because the whole circle is of students, the bus slice stands for of students, and each slice stands for students. The slices , as they must.
Tip: On a circle graph the percents always add to . On any graph, first read the title and labels so you know what the numbers mean before you compare them.
In a circle graph of votes, one slice is . How many votes is that slice, and what fraction of the circle does it fill?
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The slice is of : votes. As a fraction of the circle, .
Interpreting Data from Tables and Graphs
To interpret data, read carefully and answer the exact question asked. Good questions to ask yourself:
- Which category is largest or smallest?
- What is the total, or the difference between two values?
- Is the data increasing, decreasing, or staying the same over time?
On a line graph the steepness of each segment is the rate of change for that interval: a steeper climb means more growth per week. That is why the biggest jump is visible before any subtraction, and why a flat segment always means "no change," whatever the height.
A plant's height was measured each week:
The plant grew every week, so the line rises the whole time. The weekly changes are , and cm, so the greatest growth was between Weeks and . Total growth over the whole period was cm.
Reading the tallest point as the fastest growth. Week is the highest point, but "fastest" asks about change, which is the steepest segment. A plant that is tall but barely growing has a high, flat line.
Tip: Watch the scale. If a bar graph counts by s, a bar reaching the third line means , not .
Using the plant data, what was the average growth per week from Week to Week ?
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Total growth is cm over weeks, so the average is cm per week. (Not : there are only three weekly steps between four measurements.)
Basic Probability
Probability measures how likely an event is. An outcome is one possible result; a favorable outcome is a result you are hoping for. When every outcome is equally likely,
The fraction works only because the outcomes are equally likely: each face of a fair cube has the same chance, so each carries of the total certainty, and three favorable faces carry . When outcomes are not equally likely (a spinner with unequal sections, the sum of two dice), counting them is not enough; you must first break the experiment into outcomes that are.
A number cube has faces , so there are equally likely outcomes. What is ? The favorable outcomes are , so of them.
What is ? Only one face works, so .
Saying the sum of two dice is with probability because there are possible sums ( to ). The sums are not equally likely: of the equally likely rolls, give , so .
Tip: Every probability is a number between and . If your answer is negative or bigger than , you made a mistake. Count the total before you count the favorable outcomes.
The letters of the word PROBABILITY are put in a bag, one per tile. What is the probability of drawing a B? An I? A vowel?
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There are tiles. B appears twice: . I appears twice: . The vowels are O, A, I, I: tiles, so (Y is not counted as a vowel here).
Probability as a Fraction, Decimal, and Percent
A probability can be written three equivalent ways. Start with the fraction, divide to get the decimal, then multiply by to get the percent. On the “likelihood” line:
- means the event is impossible.
- (that is, ) means it is certain.
- () means it is equally likely to happen or not. Larger than is likely; smaller is unlikely.
Probability always lies between and because the favorable outcomes are some of the total outcomes: at best all of them (a fraction equal to ), at worst none (a fraction equal to ). The three forms are just three names for that same position on the scale from impossible to certain.
A bag has marbles, and are red. Then
Since is less than , drawing red is unlikely. Drawing “a marble” at all is certain: . Drawing a green marble is impossible (there are none): .
Writing a probability of as or as . ; move the decimal point two places, not one or three.
Tip: To turn a fraction into a percent, divide top by bottom, then move the decimal point two places right. .
A spinner has equal sections, of them blue. Write as a fraction, a decimal and a percent. Is blue likely or unlikely?
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. As a decimal, ; as a percent, . That is less than , so blue is unlikely.
Compound Events and the Counting Principle
A compound event involves more than one thing happening (such as flipping a coin and rolling a cube). The Counting Principle says: if one choice can happen in ways and a second choice in ways, then together they can happen in
This gives the total number of outcomes, which you can then use in a probability fraction.
The tree shows why the numbers multiply: each of the coin results starts its own full set of cube results, so the total is branches. With more stages the branching repeats, which is why three stages with , and choices give outcomes.
You have shirts and pairs of shorts. How many different outfits? By the Counting Principle, outfits.
Counting outcomes that are not equally likely as if they were. Two coins have four outcomes (HH, HT, TH, TT), not three; "one head" happens two ways, so , not .
Flip a coin ( outcomes: H, T) and roll a cube ( outcomes). Total outcomes . What is ? Only one pair works out of , so
Tip: For “and” with the Counting Principle you multiply the numbers of ways. A tree diagram is a great way to list every outcome when the numbers are small.
A lunch special offers sandwiches, sides and drinks. How many different lunches are there? If one is chosen at random, what is the probability it includes the one soup side?
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By the Counting Principle there are lunches. Exactly half of them use the soup side (for each sandwich and drink, the side is soup or the other one), so the probability is .
Real-World Data and Probability Problems
Word problems combine these ideas. Read slowly and decide what is being asked: a center (mean, median, mode), a spread (range), a reading from a graph, or a probability. Then set up the matching calculation and check that your answer makes sense.
Real questions rarely name the tool. "What was typical?" asks for a center, "how consistent?" for a spread, and "how likely?" for a probability. Deciding which question is being asked comes before any computing, and a sanity check comes after: a mean must sit between the smallest and largest values, and a probability between and .
In five games a player scored points.
Mean: points.
Median (order ): the middle value is .
Mode: (it appears twice). Range: .
If the coach picks one of these five games at random to rewatch, the probability it is a game where the player scored more than points (the , , and games games) is — likely.
Reporting the mean as "typical" when one value is far from the rest. For the mean and median differ because the drags the mean down; the median describes a typical game better here.
Tip: After solving, reread the question. Answers should have the right units (points, students, %) and land in a sensible range — probabilities between and , and a mean somewhere between the smallest and largest data values.
In six games a team scored . Find the mean, median, mode and range. Which center best describes a typical game?
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Mean: . Median: the middle two are and , so . Mode: . Range: . The is far from the rest and pulls the mean up to , above four of the six scores, so the median is the better description of a typical game.
Going Deeper: Advanced Statistics & Probability
A plain mean treats every value equally. A weighted mean lets some values count more than others. If each value has a weight (how many times it counts), then
This is exactly how a course grade works when tests count more than homework.
Homework is worth , quizzes , and the final exam . A student earns , , and on these. Multiply each score by its weight (as a decimal) and add:
The plain average would be , but because the heavily weighted final was lowest, the weighted grade drops to . The weights must add to (that is ).
Range uses only two values. Two better measures of spread use every value's distance from the mean.
- Mean Absolute Deviation (MAD): average how far each value is from the mean, using positive distances. @@BLOCK0@@
- Standard deviation (): instead of absolute values, square each distance, average the squares (this average is the variance), then take the square root. @@BLOCK1@@
For both, a larger value means the data are more spread out. Standard deviation is the one you will meet most in later courses.
Find the MAD and standard deviation of . First the mean: . Now each distance from :
MAD: .
Standard deviation: the squared distances sum to , so the variance is and . Both numbers describe the “typical” distance of a value from the mean.
The median splits ordered data in half. The quartiles split it into quarters:
- (lower quartile) is the median of the lower half.
- is the overall median.
- (upper quartile) is the median of the upper half.
The interquartile range is ; it measures the spread of the middle of the data and ignores extremes. A value is usually called an outlier if it lies below or above .
For (already in order, ), the median is the th value, . The lower half is , so ; the upper half is , so . Then
Outlier fences: and . Since , the value is an outlier.
When the Counting Principle is used to arrange or choose from one group, two special cases appear. Write (read “ factorial”).
- A permutation counts arrangements where order matters (like finishing st, nd, rd): @@BLOCK0@@
- A combination counts selections where order does not matter (like choosing a team): @@BLOCK1@@
Because order matters in more cases, is always at least as large as .
From runners, how many ways can they take gold, silver, and bronze? Order matters, so
From those same runners, how many ways can we pick to form a relay team (no ordering)? Now
Each unordered team of can be ordered in ways, and indeed , matching the permutation count.
The expected value is the long-run average outcome of a random situation. Multiply each outcome's value by its probability, then add:
It need not be a possible single outcome; it is what you would average over many, many repeats.
A game costs $ to play. You roll a number cube: rolling a wins you $; anything else wins nothing. The expected winnings are
Since the expected win $ is less than the $ cost, the game favors the house: on average you lose about $ each play.
Two events are independent if one happening does not change the other's probability (like two separate coin flips). They are dependent if it does (like drawing cards without replacing them).
- Independent “and”: .
- Dependent “and”: , where is the conditional probability of once has happened.
A bag has red and blue marbles ( total). You draw two marbles without putting the first back. Find . The first draw is red with probability . Now only red remain out of marbles, so the second is red with probability . These are dependent, so multiply:
If instead you replaced the first marble, the draws would be independent and .
Tip: The word “and” tells you to multiply probabilities; the word “or” (for events that cannot both happen) tells you to add them. Always ask whether the second event's probability changed — if it did, the events are dependent.
The complement of an event is everything except that event, and . Problems that ask for the probability of “at least one” success are usually far easier through the complement, because “at least one” is the opposite of “none”:
Flip a fair coin times. Find . Listing all the winning cases is tedious, so use the complement. The only way to get no heads is all tails: . Therefore
Tip: Whenever a probability question contains the phrase “at least one,” try the complement first: find and subtract from . It almost always saves work.
Why It Works
Probability as favorable/total only works when every outcome is equally likely, which is why organized listing matters: it makes the outcomes genuinely equal. The mean balances the data (deviations sum to zero), so an outlier shifts it; the median only counts positions, so an outlier cannot move it more than one place. Choosing the right summary depends on which kind of question you are answering.
Do not read a proof the way you read a rule. Cover the last line, ask what the previous line forces, and only then uncover it. If a step feels like magic, that is the step to work by hand with a concrete number.
Formulas, Proofs & Tips
What it means. The mean is the balancing point; the median is the middle value once sorted; the mode is the most frequent value; the range is largest minus smallest.
Example. For : mean , median , mode , range .
Why it works. The mean shares the total equally among the values: if everyone had , the total would still be .
Tip. Sort the list before taking a median. With an even count the median is the average of the two middle values. One extreme outlier drags the mean but barely moves the median.
What it means. The typical distance of a value from the mean.
Example. For : mean , so .
Why it works. Raw deviations sum to zero, so they are squared to stop cancellation, averaged to get a typical squared distance, then square-rooted to return to the original units.
Tip. Adding a constant to every value leaves unchanged; multiplying every value by multiplies by .