Lesson 5: Mathematics

Complete IMAT Guide

Introduction to IMAT Mathematics

The mathematics section of the IMAT tests your logical reasoning, numerical agility, and deep understanding of fundamental concepts rather than rote memorization of obscure formulas. This comprehensive module covers the three most heavily tested pillars: Euclidean Geometry, Probability (including Combinatorics), and Statistics.

Mastery of these topics is absolutely crucial, as they frequently intertwine. For example, calculating the probability of a specific genetic outcome often requires combinatorial mathematics and binomial expansion. Let's build this foundation step-by-step.

📐 Part 1: Euclidean Geometry

Euclidean Geometry is the study of flat space and the relationships between points, lines, and shapes. We will focus strictly on the high-yield formulas and concepts that appear on the exam.

2. Triangles: Notable Points and Segments

A triangle is the most fundamental polygon. Inside any triangle, drawing specific line segments reveals geometric "centers" known as notable points. You must memorize which segment creates which point.

1. Altitude (Height) $\rightarrow$ Orthocenter

The perpendicular segment dropped from a vertex to the opposite side (or its extension). The intersection of all three altitudes is the Orthocenter. In an obtuse triangle, the orthocenter lies outside the triangle.

2. Median $\rightarrow$ Centroid

The segment joining a vertex to the exact midpoint of the opposite side. The intersection is the Centroid (Center of Mass). Crucial Property: The centroid divides each median exactly in a 2:1 ratio (vertex to side).

3. Angle Bisector $\rightarrow$ Incenter

A ray that perfectly cuts an interior angle in half. The intersection is the Incenter. It is equidistant from all three sides and represents the exact center of the inscribed circle (incircle).

4. Axis (Perpendicular Bisector) $\rightarrow$ Circumcenter

A line perpendicular to a side passing through its midpoint. The intersection is the Circumcenter. It is equidistant from all three vertices and represents the center of the circumscribed circle.

Visualizing the Geometric Segments

ALTITUDE MEDIAN (Midpoint) BISECTOR (Angle) AXIS (Perp. Bisector)
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Official Paper: 2021 - Q55

PQR is a right-angled triangle with angle PRQ = $90^{\circ}$. Point S is on PR, T is on RQ. ST is parallel to PQ. RS=2.5 cm, PS=1 cm, RT=5 cm. What is the perimeter of the trapezium PQTS?

3. Polygons & Circles

A regular polygon is a geometric figure with $n$ equal sides and $n$ equal angles. Circles represent the limit as $n \to \infty$.

Polygon Angles

The sum of the exterior angles is ALWAYS $360^\circ$, regardless of the number of sides. Imagine walking around the perimeter; you turn a full circle.

The sum of the interior angles is found by dividing the polygon into $(n-2)$ triangles.

$\sum \text{Int} = (n-2) \cdot 180^\circ$
Diagonals & Perimeter

From each of $n$ vertices, you can draw a diagonal to $(n-3)$ other vertices. We divide by 2 to prevent double-counting.

$d = \frac{n(n-3)}{2}$

The perimeter is simply $2p = n \cdot l$.

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Official Paper: 2022 - Q59

Two concentric circles with centre O. The radius of the larger circle is 50% greater than the smaller. Area of smaller is $36\text{ cm}^2$. The area of the shaded sector is $27/8\text{ cm}^2$. What is the value of $\theta$?
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Official Paper: 2018 - Q54

A pentagon has one line of symmetry. All five sides are 6 cm, and the interior angles, in anticlockwise order, are $60^{\circ}, 150^{\circ}, 90^{\circ}, 90^{\circ}$ and $150^{\circ}$. What is the area of this pentagon?
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Official Paper: 2013 - Q60

The diagram shows a quarter of a circle surrounded by an isosceles triangle. The radius is $r$. Which expression represents the unshaded area?
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Official Paper: 2011 - Q80

A square piece of metal has a semicircular piece cut out of it. The area remaining is $100\text{ cm}^2$. What is the side of the square?

🎲 Part 2: Probability & Combinatorics

Probability theory is the mathematical framework for quantifying uncertainty and calculating likelihoods. In the IMAT, calculating complex probabilities often requires combining basic probability axioms with advanced counting techniques (Combinatorics). Because medical diagnostics and genetics heavily rely on probability, this section is universally high-yield.

4. Basic Concepts & Set Theory

Probability is defined mathematically on a scale between 0 (an absolute impossibility) and 1 (absolute certainty). The foundational theoretical formula is:

$P(E) = \frac{\text{Number of favorable outcomes}}{\text{Total number of possible outcomes in Sample Space } (S)}$
📝 Basic Example

If you roll a standard, fair 6-sided die, what is the probability of rolling a prime number?

Solution Step-by-Step:

1. Determine the total sample space (S): $S = \{1, 2, 3, 4, 5, 6\}$. Total outcomes = 6.

2. Determine the favorable outcomes (E): The prime numbers on a die are 2, 3, and 5. (Note: 1 is NOT a prime number). $E = \{2, 3, 5\}$. Favorable outcomes = 3.

3. Calculate: $P(E) = \frac{3}{6} = \frac{1}{2} = 50\%$

Set Theory Logic (AND / OR)

IMAT questions rarely ask for the probability of a single event. You must know how to combine probabilities using the rules of sets.

  • The Union (OR Rule / Addition Rule) The probability that event A OR event B occurs. If events are mutually exclusive (they cannot happen simultaneously, like drawing a card that is both a Heart and a Spade), you simply add them: $P(A \cup B) = P(A) + P(B)$.

    If they are NOT mutually exclusive (they can overlap, like drawing a card that is a Heart AND a King), you must subtract the overlap so you don't double count:
    General Addition Rule: $P(A \cup B) = P(A) + P(B) - P(A \cap B)$
  • The Intersection (AND Rule / Product Rule) The probability that event A AND event B occur simultaneously or sequentially. For independent events (where A does not affect B), you simply multiply them.
    Product Rule for Independent Events: $P(A \cap B) = P(A) \times P(B)$
  • The Complement Rule (NOT) The probability that event A does NOT occur. Sometimes, calculating the probability of something NOT happening is vastly easier than calculating every way it COULD happen.
    $P(\text{NOT A}) = 1 - P(A)$
📝 Complement Rule Example

You flip a fair coin 5 times. What is the probability of getting at least one Heads?

Solution Step-by-Step:

Trying to calculate exactly 1 Head, exactly 2 Heads, exactly 3 Heads... and adding them all up is extremely tedious and prone to error. Use the complement rule!

1. The only outcome that does NOT satisfy "at least one Head" is getting absolutely ZERO Heads (meaning getting 5 Tails in a row).

2. Probability of getting a Tail on one flip is $1/2$. Because flips are independent, $P(5 \text{ Tails}) = (1/2)^5 = 1/32$.

3. Calculate Complement: $P(\text{At least 1 Head}) = 1 - P(\text{0 Heads}) = 1 - 1/32 = \frac{31}{32}$

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Official Paper: 2012 - Q77

In a group of students, exactly 2/5 are male and exactly 1/3 study mathematics. The probability $p$ that a male student chosen at random studies math has what range?
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Official Paper: 2023 - Q51

Two standard six-sided dice are rolled. What is the probability that the product of the two numbers obtained is the square of a prime?
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Official Paper: 2015 - Q57

The arithmetic mean of $a, b, c$ is 8. Find the arithmetic mean of $a+1, b+2, c+6, 3$.
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Official Paper: 2025 - Q50

What does the Cartesian product of a set A and a set B correspond to?

5. Independent vs. Dependent Events (With vs Without Replacement)

When calculating the probability of drawing items sequentially, you must pay extreme attention to the wording of the question regarding replacement.

📝 Dependent Events Example (Without Replacement)

A standard deck contains 52 cards (26 red, 26 black). You draw two cards randomly without replacement. What is the probability that both cards are red?

Solution Step-by-Step:

1. The probability the first card is red is simple: $26/52 = 1/2$.

2. Because you did NOT replace the first red card, the sample space has permanently changed. There are now only 25 red cards remaining out of 51 total cards.

3. The probability the second card is red (given the first was red) is $25/51$.

4. Multiply (Product Rule): $\frac{26}{52} \times \frac{25}{51} = \frac{1}{2} \times \frac{25}{51} = \frac{25}{102}$

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Official Paper: 2011 - Q76

Box A has 4 stars, 2 hearts. Box B has 2 stars, 1 heart. David moves 1 random shape from A to B. He then draws from B. What is the probability it is a star?
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Official Paper: 2022 - Q57

The mean of five non-zero positive integers is 20. The median is 24. What is the maximum possible value for the largest number?

6. Combinatorics: Permutations & Combinations

When the sample space is huge, we cannot count outcomes manually. We use combinatorics. The fundamental question to ask yourself immediately upon reading a question is: "Does the order matter?"

Permutations (Order MATTERS)

Used when arranging objects in a strict sequence (e.g., assigning 1st, 2nd, and 3rd place in a race; creating a password; lining up books on a shelf). Selecting object A then B is treated mathematically as a completely different outcome than selecting B then A.

$P(n, k) = \frac{n!}{(n-k)!}$
Combinations (Order DOES NOT Matter)

Used when selecting a group or committee from a larger pool where roles are identical (e.g., picking 3 pizza toppings from a menu of 10; selecting 4 students to form a study group). Selecting A then B is exactly the same as selecting B then A. We divide by $k!$ to erase the duplicate internal orderings.

$C(n, k) = \binom{n}{k} = \frac{n!}{k!(n-k)!}$
📝 Combinations Example

A hospital ward has 8 available nurses. The head doctor needs to randomly select exactly 3 nurses to assist in an emergency surgery. How many different groups of 3 nurses can be formed?

Solution Step-by-Step:

Does order matter? No. Being chosen 1st, 2nd, or 3rd doesn't change the fact that you are in the surgery group. Therefore, we use Combinations ($C$). Total pool $n=8$, chosen $k=3$.

$$C(8, 3) = \frac{8!}{3!(8-3)!} = \frac{8!}{3! \times 5!} = \frac{8 \times 7 \times 6}{3 \times 2 \times 1} = \frac{336}{6} = 56 \text{ groups}$$

High Yield IMAT Logic

Anagrams (Permutations with Repetition)

A very common, highly specific IMAT question asks how many distinct words (anagrams) can be formed by rearranging the letters of a given word. If all letters are totally unique (e.g., "CAT"), the answer is simply the factorial of the length: $n!$ ($3! = 3 \times 2 \times 1 = 6$). However, if some letters repeat, swapping two identical letters creates an indistinguishable word. You must divide the total permutations by the factorial of the frequency of each repeating letter to remove these phantom duplicates.

Example: How many distinct anagrams can be made from the word "MEDITALIANO"?

1. Count total letters ($n$): There are 11 letters total. So the numerator is $11!$.

2. Identify repeating letters: The letter 'I' appears 2 times (so divide by $2!$). The letter 'A' appears 2 times (divide by $2!$).

$\text{Total Anagrams} = \frac{11!}{2! \cdot 2!}$
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Official Paper: 2018 - Q57

A bag contains 3 red, 4 blue, and 5 green marbles. If one marble is drawn at random, what is the probability that it is not red?
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Official Paper: 2017 - Q59

Two fair six-sided dice are rolled. What is the probability that the sum of the scores is at least 10?

8. Binomial Probability (Repeated Trials)

If you conduct an experiment multiple times (e.g., flipping a coin 5 times, or having 4 children where each has a 25% chance of inheriting a disease), you must use the Binomial Probability formula. This calculates the probability of getting exactly $k$ successes in exactly $n$ independent trials.

$P(X = k) = \binom{n}{k} \cdot p^k \cdot (1-p)^{n-k}$

• $\binom{n}{k}$ calculates all the different possible orders the successes could happen.
• $p^k$ is the probability of the successes happening.
• $(1-p)^{n-k}$ is the probability of the failures happening.

📝 Binomial Genetics Example

Two parents are heterozygous carriers (Aa) for Cystic Fibrosis, a recessive disorder. They plan to have 3 children. What is the exact probability that exactly 2 of their 3 children will be born with the disease?

Solution Step-by-Step:

1. Identify variables: Total trials $n=3$. Desired successes (sick children) $k=2$. From a Punnett square of Aa x Aa, the probability of a child having the disease (aa) is $p = 1/4$. The probability of being healthy is $(1-p) = 3/4$.

2. Apply formula: $P(X=2) = \binom{3}{2} \cdot (1/4)^2 \cdot (3/4)^1$

3. Calculate: $\binom{3}{2} = 3$ (The sick children could be the 1st&2nd, 1st&3rd, or 2nd&3rd).

4. Final Math: $3 \times (\frac{1}{16}) \times (\frac{3}{4}) = \frac{9}{64}$

9. Conditional Probability & Bayes' Theorem

Conditional probability, denoted as $P(A|B)$, is the probability of event A occurring, given the strict condition that event B has already occurred. This effectively shrinks the mathematical sample space down to only the universe where B is true.

$P(A|B) = \frac{P(A \cap B)}{P(B)}$

"The probability of the overlap (A and B happening together) divided by the probability of the new restricted universe (B)."

Tree Diagrams for Sequential Events

P(B) P(B') Event B P(A|B) A ∩ B = P(B) × P(A|B)
Clinical Logic - Bayes' Theorem

Bayes' Theorem & The False Positive Paradox

Bayes' Theorem allows us to mathematically reverse conditional probabilities. This is the absolute mathematical foundation of medical diagnostics. It answers the terrifying patient question: "Doctor, if my screening test result came back positive, what is the actual probability that I truly have the disease?"

$P(\text{Disease} | \text{Positive}) = \frac{P(\text{Positive} | \text{Disease}) \cdot P(\text{Disease})}{P(\text{Positive Total})}$

IMAT Hack: The Hypothetical Population Tree

To solve Bayes' problems quickly without memorizing the complex expanded formula, use a Hypothetical Population of 10,000 people.

  • Assume a population of exactly 10,000 people.
  • Use the Prevalence $P(D)$ of the disease to split the 10,000 into Sick and Healthy branches. (e.g., 1% prevalence = 100 sick, 9,900 healthy).
  • Use the Sensitivity of the test on the Sick branch to find the True Positives. (e.g., 99% sensitive = 99 true positives).
  • Use the False Positive Rate on the Healthy branch to find the False Positives. (e.g., 5% false positive rate applied to 9,900 = 495 false positives).
  • Answer = (True Positives) / (Total Positives). Here, $99 / (99 + 495) = 99 / 594 \approx 16\%$. Even with a highly accurate 99% test, if the disease is extremely rare, a positive result often means you are still overwhelmingly likely to be healthy.
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Official Paper: 2024 - Q50

In a bag are 3 red balls and 7 green balls. Two extractions are made, with the first returned before the second. What is the probability of extracting 2 green balls?
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Official Paper: 2019 - Q54

The mean mass of three babies is 2.1 kg. The range is 0.7 kg. The lightest is 1.8 kg. What is the median?
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Official Paper: 2020 - Q57

The mean of 4 numbers is 5. When a fifth number is added, the mean becomes 6. What is the fifth number?

📊 Part 3: Statistics & Data Analysis

Before we can analyze large datasets, we must understand the mathematical logic governing ordered lists of numbers (Sequences) and their sums (Series).

10. Sequences & Sigma Notation

Arithmetic Sequence

Growth by constant Addition (Linear). The mathematical difference ($d$) between any two consecutive terms is constant.

$a_n = a_1 + (n-1)d$

Sum of first $n$ terms (Arithmetic Series):

$S_n = \frac{n(a_1 + a_n)}{2}$
Geometric Sequence

Growth by constant Multiplication (Exponential). The ratio ($r$) between consecutive terms is constant.

$a_n = a_1 \cdot r^{n-1}$

Sum of an infinite geometric series (only if $|r| < 1$):

$S_\infty = \frac{a_1}{1 - r}$

11. Measures of Central Tendency

"Where is the exact center of the data?" Statistics offers three distinct mathematical answers. Knowing which one to use depends entirely on the shape of the data distribution.

Mean ($\mu$)

The arithmetic average. It incorporates every precise mathematical value in the entire dataset. Because it uses magnitude, it is highly, dangerously sensitive to extreme outliers.

$\mu = \frac{\sum x_i}{n}$
Median

The exact physical middle value when data is ordered from smallest to largest. It completely ignores the magnitude of extreme values, making it highly robust to outliers (e.g., used for calculating average national housing prices).

50th Percentile
Mode

The single most frequently occurring value in the dataset. It is the only measure of central tendency that can be used for non-numerical, categorical data (e.g., identifying the most common blood type).

Can be Multimodal

Visualizing Right-Skewed Data

MODE (Peak) MEDIAN (50%) MEAN (Pulled by outliers) Long right tail (e.g. Income) Mean > Median > Mode

12. Measures of Dispersion (Spread)

Central tendency alone is dangerously incomplete. You must mathematically know how spread out or reliable the data is around that center.

Variance ($\sigma^2$)

$\sigma^2 = \frac{\sum (x_i - \mu)^2}{n}$

Logic: It calculates the average of the squared mathematical distances of each individual data point from the mean. We square the differences so negative distances don't simply cancel out positive ones, and importantly, squaring heavily penalizes massive outliers.

Standard Deviation ($\sigma$)

$\sigma = \sqrt{\text{Variance}}$

Logic: Variance mathematically gives results in "units squared" (e.g., dollars squared), which is uninterpretable in the real world. Taking the square root elegantly returns the measurement back to the original, understandable scale.

📝 Mastery Practice: IMAT Mathematics Quiz

Test your comprehensive understanding of advanced geometry, deep probability logic, combinatorics, and statistical interpretation. These questions are meticulously styled after the rigorous, integrated, multi-step logic required for the mathematical reasoning section of the IMAT.