Post By

Ryan Brownlee

– Founder of AspiringMD

Is statistics on the MCAT? Yes, but you do not need advanced statistics. Learn which statistics concepts the MCAT tests, how often they appear, and what to study.

Yes, statistics is on the MCAT, but you do not need to know anything close to an entire college statistics course for the exam. The MCAT focuses much more heavily on your ability to interpret data and understand what statistical results mean than on performing complicated statistical calculations by hand.

According to the AAMC, Data-Based and Statistical Reasoning is one of the four Scientific Inquiry and Reasoning Skills tested throughout the Chemical and Physical Foundations, Biological and Biochemical Foundations, and Psychological, Social, and Biological Foundations sections. The AAMC estimates that this skill accounts for approximately 10% of the questions in each of those three sections.

That number can sound intimidating until you understand what the AAMC actually includes under “Data-Based and Statistical Reasoning.” These are not all questions asking you to calculate standard deviations or perform hypothesis tests. The category also includes interpreting graphs and tables, recognizing patterns, comparing variables, evaluating experimental results, understanding uncertainty, and deciding which conclusions are supported by the available data.

For most premeds, the better question is therefore not simply, “Is statistics on the MCAT?” It is “How much statistics do I actually need to know for the MCAT?” Fortunately, the answer is much more manageable than taking an entire statistics textbook and adding it to your study schedule.

How Much Statistics Is on the MCAT?

The AAMC classifies approximately 10% of the questions in each of the three science sections as Skill 4: Data-Based and Statistical Reasoning.

Since the Chemical/Physical, Bio/Biochem, and Psych/Soc sections each contain 59 questions, you could loosely think of that as around six Data-Based and Statistical Reasoning questions per science section, although the exact number can vary from one exam to another.

Across those three sections, that would be approximately 18 questions associated with Skill 4.

However, I would be careful about interpreting that as 18 statistics questions.

The AAMC’s Skill 4 category is much broader than traditional statistics. A question in this category could show you a graph from a biology experiment and ask which conclusion is supported by the data. Another could show two variables and ask you to interpret their relationship, while another might require you to understand what a confidence interval or statistically significant result means.

This distinction is important because I would not spend 10% of my MCAT content-review time memorizing statistics formulas. I would spend time learning the relatively small group of statistics concepts the AAMC expects you to recognize and then spend considerably more time practicing how to interpret experimental data.

If you want to see exactly how the AAMC categorizes the material on the exam, I keep the official content outline available through my AAMC MCAT Topic List PDF guide. I recommend using the actual AAMC outline during content review because it helps prevent you from spending hours studying material that goes substantially beyond the scope of the MCAT.

What Statistics Do You Need to Know for the MCAT?

The official AAMC description of Data-Based and Statistical Reasoning specifically mentions several statistical concepts that students should understand.

For the MCAT, I would make sure you are comfortable with:

You should understand these concepts well enough to use them, rather than simply memorizing their definitions.

For example, knowing that standard deviation measures dispersion is a good start. Being prepared for the MCAT means looking at two experimental groups and recognizing that the group with the larger standard deviation has more variability in its observations.

The same principle applies to statistical significance. Memorizing a cutoff without understanding what significance means is much less useful than being able to read an experiment, recognize what was compared, interpret the reported statistical information, and determine what conclusion the researchers can reasonably make.

Do You Need to Calculate Standard Deviation on the MCAT?

You should know what standard deviation means and how to interpret it, but I would not spend significant study time practicing lengthy hand calculations of standard deviation.

Standard deviation tells you how spread out observations are around the mean. A small standard deviation means values tend to cluster relatively close to the mean, while a larger standard deviation means the observations are more spread out.

Imagine two groups in an experiment both have a mean measurement of 50.

Group A has:

Mean = 50, SD = 2

Group B has:

Mean = 50, SD = 15

The groups have exactly the same mean, but the individual observations in Group A are much more tightly clustered around 50. Group B has considerably greater variability.

That type of interpretation is much closer to how I would expect you to use standard deviation on the MCAT than being handed 15 numbers and asked to calculate the standard deviation from scratch.

You should also recognize the general idea behind a normal distribution and understand how values relate to the mean and standard deviation. I would know the common 68-95-99.7 rule: approximately 68% of observations in a normal distribution fall within one standard deviation of the mean, about 95% fall within two, and about 99.7% fall within three.

You do not need to turn your MCAT preparation into an advanced biostatistics course, but understanding what those distributions mean can make data interpretation much easier.

Do You Need to Know Mean, Median, and Mode for the MCAT?

Yes. The AAMC specifically includes mean, median, and mode under the measures of central tendency you may be expected to understand.

The mean is simply the arithmetic average, while the median is the middle value after observations are placed in order. The mode is the value that occurs most frequently.

The more useful MCAT skill is understanding when these measures behave differently.

Imagine the annual incomes of five people are:

$40,000
$42,000
$45,000
$48,000
$2,000,000

The extremely high final income pulls the mean upward substantially, while the median remains $45,000.

If an MCAT passage describes a heavily skewed distribution with an extreme outlier, you should recognize why the median may better represent the typical observation than the mean. Questions like this require very little difficult mathematics, but they do require you to understand what the numbers actually represent.

Do You Need to Know P-Values for the MCAT?

You should understand the basic interpretation of statistical significance, and p-values are commonly encountered when reviewing scientific passages and MCAT preparation material.

A common threshold used in scientific research is p < 0.05, which is often used to designate statistical significance. For MCAT purposes, you should be comfortable recognizing whether reported results satisfy the significance threshold provided in a study and what that allows the researchers to conclude.

There is an important nuance here because students sometimes memorize “p < 0.05 means the experiment is correct,” which is not what a p-value tells you.

A statistically significant result does not automatically prove causation, prove that a hypothesis is true, or tell you that an effect is practically important. You still have to consider the study design, variables, sample, possible confounding factors, and exactly what was measured.

This is where statistics and MCAT scientific reasoning overlap. The exam is often less interested in whether you remember a statistical definition than whether you can avoid making a conclusion that goes beyond the evidence presented in a passage.

Do You Need to Know Confidence Intervals for the MCAT?

Yes, confidence intervals are explicitly mentioned by the AAMC as part of Data-Based and Statistical Reasoning.

For MCAT purposes, focus primarily on interpreting what a confidence interval tells you about an estimate and the uncertainty surrounding it. A narrower confidence interval generally represents a more precise estimate than a wider interval, assuming the intervals are being compared appropriately.

You may encounter a passage presenting means alongside confidence intervals or error bars and be asked whether the evidence supports a difference between groups.

Be careful about turning visual shortcuts into absolute rules, however. Students are sometimes taught that overlapping error bars automatically mean two groups are not significantly different and non-overlapping bars automatically mean they are significant. Whether that inference is valid depends on what the bars represent, such as standard deviation, standard error, or a confidence interval, and on the statistical test used.

On the MCAT, use the information the passage provides rather than inventing statistical conclusions that are not supported by it.

Is Probability on the MCAT?

Basic probability can appear on the MCAT, particularly when it overlaps with other subjects such as genetics, scientific reasoning, and interpreting experimental outcomes. You do not need the level of probability theory expected in an upper-level statistics course.

You should be comfortable thinking through simple probabilities, proportions, fractions, and percentages. Genetics is a good example because Punnett squares and inheritance patterns frequently require you to reason about the probability that an offspring inherits a particular genotype or phenotype.

The mathematical demands of the MCAT are usually more about recognizing relationships and calculating efficiently than performing advanced mathematics. You will not have a calculator, which is why being comfortable with fractions, ratios, percentages, scientific notation, estimation, and basic arithmetic is far more useful than learning advanced statistical equations.

Where Does Statistics Show Up on the MCAT?

One reason students underestimate statistics on the MCAT is that there is no section labeled Statistics.

Instead, statistical reasoning can appear throughout three sections of the exam.

Statistics in MCAT Bio/Biochem

Biology and biochemistry passages frequently describe experiments.

You might see researchers compare protein expression between groups, measure enzyme activity under several conditions, alter the expression of a gene, or administer a treatment and record physiological changes.

A graph or table may then summarize the results.

The question may not ask you anything that sounds like a statistics problem. Instead, it might ask which experimental group supports the researchers’ hypothesis, which variable was associated with the greatest response, or whether the results support a proposed biological mechanism.

This is still Data-Based and Statistical Reasoning.

The AAMC estimates that Skill 4 represents approximately 10% of Bio/Biochem questions, which is one reason I would spend a meaningful amount of your practice time learning how to interpret scientific figures rather than focusing entirely on memorizing biology facts.

Statistics in MCAT Chem/Phys

Chemical and Physical Foundations can also test Data-Based and Statistical Reasoning.

You may need to interpret a graph, calculate a slope, compare experimental conditions, recognize a relationship between variables, or determine whether a proposed model agrees with the data.

The statistics itself is generally basic, but the passage may combine the data with chemistry or physics concepts. This can make the question feel much harder than the underlying mathematical operation actually is.

If mathematics is one of your weaker MCAT areas, working on estimation, units, relationships between variables, and graph interpretation will usually provide more value than studying advanced statistics. The same principle applies to equations: I created a free MCAT Physics Equations Anki deck and guide to help students review formulas, but I recommend learning what each relationship actually means rather than memorizing equations in isolation.

Statistics in MCAT Psych/Soc

Psychology and sociology may be the section students associate most strongly with statistics because so many Psych/Soc passages describe human research.

You could encounter surveys, observational studies, experiments, demographic datasets, correlations, or comparisons between different populations.

Statistics in this section may involve central tendency, standard deviation, significance, confidence intervals, correlation, bias, variables, or conclusions researchers can reasonably draw from their findings.

Research methods and statistics are therefore worth reviewing during Psych/Soc preparation rather than treating the section as a giant vocabulary test.

When I studied for the MCAT, I used the detailed Khan Academy Psych/Soc notes for my initial content review and then the condensed version toward the end of my preparation. I have both available in my guide to the Khan Academy MCAT Psych/Soc 86-page and 300-page documents, which can be particularly useful if research methods and behavioral science terminology are weaker areas for you.

Is Statistics on CARS?

CARS is different.

The AAMC’s Scientific Inquiry and Reasoning Skill framework, including Skill 4 Data-Based and Statistical Reasoning, applies to the three science sections rather than CARS. CARS instead tests comprehension and reasoning through passages from the humanities and social sciences.

That means I would not study statistical concepts specifically for CARS.

You still need to reason carefully from evidence and avoid conclusions that extend beyond what an author actually says, but you are not expected to approach CARS passages as statistical research problems.

Do You Need to Take a Statistics Class Before the MCAT?

No, you do not need to take an entire college statistics class simply to prepare for the statistics tested on the MCAT.

A statistics course can certainly be useful, particularly because understanding research becomes increasingly important throughout medical school and medicine. Some undergraduate programs or medical schools may also have their own mathematics or statistics requirements, which is a separate issue from what the MCAT itself tests.

For the MCAT alone, however, the statistics content is narrow enough that you can learn it through targeted content review and practice.

If you already took statistics and remember the basic concepts, you probably need a refresher rather than an entire course. If you have never taken statistics, I would work through central tendency, dispersion, significance, confidence intervals, basic probability, correlation, error, and data interpretation, then move relatively quickly into MCAT-style practice questions.

One of the biggest mistakes you can make during MCAT preparation is studying a subject to the depth of a college course when the exam only expects introductory understanding. There is already an enormous amount of biology, biochemistry, chemistry, physics, psychology, and sociology to review, so your time needs to be allocated carefully.

Do You Need to Memorize Statistics Formulas for the MCAT?

There are relatively few statistics formulas I would prioritize memorizing compared with the equations you need for physics and chemistry.

You should certainly be able to calculate a mean:

Mean = Sum of all observations / Number of observations

You should also understand concepts such as range, percentages, ratios, and proportions well enough to calculate them quickly.

Beyond that, I would put much more emphasis on interpretation than memorizing formulas for variance, standard deviation, confidence intervals, t-tests, ANOVA, regression models, or other formal statistical tests.

If your study resource starts making you perform lengthy calculations of variance, manually calculate confidence intervals, or work through complicated hypothesis-testing equations, I would check those topics against the official AAMC content outline before spending a significant amount of time on them.

The MCAT is already difficult enough without accidentally studying material for a statistics final that you are not taking.

What Statistics Formulas Should You Know for the MCAT?

For a focused MCAT review, I would know or understand the following relationships:

Mean = Sum of observations ÷ Number of observations

Range = Maximum value − Minimum value

You should also know how percentages, fractions, proportions, ratios, and probability work because these concepts frequently appear when interpreting scientific data.

For standard deviation, interquartile range, confidence intervals, and statistical significance, interpretation is substantially more important than memorizing the full computational formulas.

This is one of those areas where understanding what a number means will usually help you more than memorizing the equation used by statistical software to calculate it.

Statistics vs. Research Methods on the MCAT

Statistics is often taught alongside research methods on the MCAT, but they are not exactly the same thing.

You should also understand concepts such as:

• Independent and dependent variables
• Experimental and control groups
• Confounding variables
• Correlation versus causation
• Randomization
• Bias
• Study design
• Reliability and validity
• Experimental controls
• Drawing conclusions from results

Some of these concepts fall more directly under the AAMC’s separate Scientific Inquiry Skill 3, Reasoning about the Design and Execution of Research, while others overlap with Skill 4.

The distinction is less important for your study schedule than recognizing that the MCAT expects you to understand how scientific evidence is produced and interpreted.

Imagine a study finds that people who exercise more frequently have lower blood pressure.

You should recognize that this demonstrates an association.

Whether you can conclude that exercise caused the lower blood pressure depends on the study design and potential alternative explanations. If the researchers simply surveyed people about their exercise habits, variables such as diet, age, medications, socioeconomic status, or preexisting health conditions might also differ between the groups.

That type of reasoning is extremely relevant to the MCAT even though you never had to calculate anything.

Correlation Does Not Automatically Mean Causation

This concept deserves particular attention because it appears throughout scientific and social science reasoning.

A positive correlation means two variables tend to move in the same direction. As one increases, the other tends to increase.

A negative correlation means the variables tend to move in opposite directions. As one increases, the other tends to decrease.

A correlation by itself does not demonstrate that one variable caused the other.

For example, imagine researchers find that people who sleep fewer hours tend to consume more caffeine.

You cannot automatically conclude that caffeine causes people to sleep less. It is also possible that people who sleep less consume more caffeine because they are tired, or that another variable influences both sleep and caffeine consumption.

When the MCAT asks what a study demonstrates, pay close attention to whether the researchers performed a controlled experiment or simply observed an association.

Random Error vs. Systematic Error on the MCAT

The AAMC specifically includes reasoning about random and systematic error in its description of Skill 4.

Random error causes unpredictable variation in measurements. If you repeatedly measure the same quantity and receive slightly different results because of unavoidable fluctuations, that is random error.

Systematic error consistently pushes measurements in a particular direction. A scale that always reports a person’s weight as five pounds too high would introduce systematic error.

An easy way to think about the difference is that random error tends to hurt precision, while systematic error can create a consistent bias.

Increasing sample size or repeating measurements can sometimes reduce the effect of random variation. Repeating an experiment with the same incorrectly calibrated instrument, however, will not magically remove its systematic bias.

The MCAT may give you an experimental setup and ask how a particular limitation affects the reliability or interpretation of the results, so understanding these ideas conceptually is more useful than memorizing definitions alone.

How Hard Is MCAT Statistics?

For most students, the statistics itself is not one of the most mathematically difficult parts of the MCAT.

The difficulty comes from using basic statistics inside an unfamiliar scientific passage.

You may understand perfectly well what a mean, standard deviation, and p-value are when they appear in a textbook. The MCAT can make the same concepts feel much harder by surrounding them with a passage about a protein you have never heard of, three experimental conditions, a complicated figure, error bars, and several paragraphs describing the researchers’ methods.

When this happens, try to separate the unfamiliar scientific language from the actual task.

Ask yourself:

1. What did the researchers change?
2. What did they measure?
3. What are the groups being compared?
4. What does the figure actually show?
5. Is the difference statistically meaningful according to the information provided?
6. What conclusion is supported by the data?
7. What conclusion would go beyond the evidence?

These questions can turn an intimidating research passage into a much more manageable problem.

How I Would Study Statistics for the MCAT

I would not devote weeks of isolated content review to MCAT statistics.

Instead, I would spend enough time learning the foundational concepts that you recognize them immediately, and then I would build the rest of the skill through practice passages.

When I studied for the MCAT, my biggest improvements did not come from endlessly rereading content. I spent a large portion of my later preparation working through practice material and then carefully reviewing why I had missed questions. If I discovered that I misunderstood an underlying concept, I went back and learned it. If the issue was that I misinterpreted a graph or drew a conclusion the passage did not support, however, simply reading another chapter would not have fixed the problem.

That distinction becomes especially important with statistics and experimental-design questions because you may repeatedly miss them even though you technically “know” the definitions.

When you begin taking practice exams, I recommend using an error log and separating mistakes such as content gaps, graph interpretation, experimental reasoning, math errors, and misreading the question. I explain the process I eventually settled on in my step-by-step guide to reviewing MCAT full-lengths, and I also made a free MCAT full-length review and error log spreadsheet if you want somewhere to track those patterns.

If you miss five statistics-related questions across several practice exams, seeing them together can tell you much more than treating each one as an isolated mistake.

A Simple MCAT Statistics Study Checklist

Before test day, I would make sure you can confidently explain the following without looking them up:

If you can understand those concepts and apply them to MCAT passages, I would move on to practice rather than trying to turn yourself into a statistician.

The Most Important Statistics Skill on the MCAT Is Data Interpretation

If I had to pick one skill from this entire article to emphasize, it would be reading scientific data efficiently.

The AAMC explicitly says that Data-Based and Statistical Reasoning includes analyzing figures, graphs, and tables, identifying patterns, explaining relationships between variables, answering research questions using data, and identifying conclusions supported by research results.

That means a student could memorize every statistics definition on an Anki deck and still struggle with Skill 4 questions if they cannot interpret a complicated figure.

Whenever you encounter a graph during practice, slow down enough to understand it before immediately reaching for the answer choices.

Look at:

• The x-axis
• The y-axis
• Units
• Experimental groups
• Control groups
• The legend
• Error bars
• Statistical significance markers
• Whether values increase, decrease, or remain unchanged
• Whether the question asks about absolute values or relative changes

You do not necessarily need to spend several minutes analyzing every figure before reading the question, but you should know where to look when the question sends you back to the data.

The AAMC’s own material is particularly valuable here because eventually you need to become comfortable with the way the test writers expect you to reason from their passages. During my own MCAT preparation, I transitioned heavily toward AAMC questions and full-lengths near the end of studying for exactly that reason. I explain the resources I used and how I structured my preparation in my complete guide to how I studied for the MCAT.

Don’t Overstudy Statistics for the MCAT

Statistics matters, but I would keep its importance in perspective.

The MCAT covers an enormous amount of content, and every hour you spend learning statistical material beyond the exam’s scope is an hour you are not spending reviewing biochemistry, amino acids, physics, organic chemistry, psychology, sociology, or practicing passages.

Use the AAMC content outline as your boundary.

If the AAMC specifically mentions a concept such as mean, median, mode, standard deviation, confidence intervals, statistical significance, or experimental error, learn it well enough to interpret it.

If your statistics resource starts teaching you complicated regression analysis, manually performing ANOVA, deriving probability distributions, or calculating advanced hypothesis tests, ask whether that depth is actually helping you answer MCAT questions.

For most students, it will not be the best use of limited study time.

So, Is Statistics on the MCAT?

Yes, statistics is definitely on the MCAT, but the exam tests statistical reasoning much more than advanced statistical mathematics.

The AAMC estimates that Data-Based and Statistical Reasoning represents approximately 10% of the questions in each of the three science sections. That category includes statistics, but it also includes reading graphs and tables, interpreting experimental results, identifying relationships between variables, understanding error and uncertainty, and deciding what conclusions the evidence supports.

You should know mean, median, mode, range, interquartile range, standard deviation, statistical significance, confidence intervals, correlation, and random versus systematic error. You should also be comfortable with basic probability, percentages, ratios, experimental variables, and research design.

What I would not do is take an entire advanced statistics course solely because you are worried about the MCAT.

Learn the statistics the AAMC specifically expects, make sure you understand what each concept means, and then practice applying those ideas to real MCAT passages. Once the definitions are familiar, the higher-yield skill becomes learning how to look at unfamiliar scientific data and quickly determine what it actually tells you.

Frequently Asked Questions About Statistics on the MCAT

Is there statistics on the MCAT?

Yes. Statistics and data interpretation appear throughout the three science sections of the MCAT. The AAMC classifies Data-Based and Statistical Reasoning as one of the four Scientific Inquiry and Reasoning Skills and estimates that it represents approximately 10% of questions in Chemical/Physical, Bio/Biochem, and Psych/Soc.

How much statistics is on the MCAT?

Approximately 10% of each science section is categorized as Data-Based and Statistical Reasoning, which works out to roughly six questions in each 59-question science section. However, not all of those questions are traditional statistics questions because the category also includes graphs, tables, experimental results, relationships between variables, and drawing conclusions from data.

What statistics do I need to know for the MCAT?

You should understand mean, median, mode, range, interquartile range, standard deviation, statistical significance, confidence intervals, correlation, random error, systematic error, and basic data interpretation. You should also understand research concepts such as independent and dependent variables, experimental controls, bias, and correlation versus causation.

Do I need to know p-values for the MCAT?

You should understand the basic idea of statistical significance and be comfortable interpreting a p-value when one is provided in a research passage. A commonly used significance threshold is p < 0.05, although you should always use the significance criteria provided by the passage rather than assuming every study uses exactly the same threshold.

Is p < 0.05 always statistically significant on the MCAT?

A p-value below 0.05 is commonly treated as statistically significant when the study uses an alpha level of 0.05. However, you should pay attention to the threshold provided in the passage because significance depends on the predetermined alpha level rather than a universal rule that applies to every analysis.

Do you need to calculate standard deviation on the MCAT?

Understanding and interpreting standard deviation is much more important than manually calculating it from a large dataset. You should know that a larger standard deviation represents greater dispersion around the mean and a smaller standard deviation represents observations clustered more tightly around the mean.

Do you need to know the 68-95-99.7 rule for the MCAT?

It is useful to understand the basic relationship between a normal distribution and standard deviations. Approximately 68% of values lie within one standard deviation of the mean, approximately 95% within two, and approximately 99.7% within three.

Is probability on the MCAT?

Basic probability can appear on the MCAT, particularly in genetics and scientific reasoning. You should be comfortable with simple probabilities, fractions, percentages, ratios, and proportions, but advanced probability theory is unnecessary.

Do I need to take statistics before the MCAT?

You do not need to take an entire statistics course solely to prepare for the MCAT. A college statistics course can provide useful background, but the statistics tested on the MCAT can be learned through focused content review and passage-based practice.

Is statistics mostly in MCAT Psych/Soc?

Statistics is particularly noticeable in Psych/Soc because that section frequently discusses human research, surveys, correlations, demographics, and study design. However, Data-Based and Statistical Reasoning is tested in Chem/Phys and Bio/Biochem as well, and the AAMC assigns approximately the same 10% Skill 4 weighting to all three science sections.

Is statistics on MCAT Bio/Biochem?

Yes. Bio/Biochem passages frequently present experiments, graphs, protein or gene-expression data, treatment groups, and experimental results. You may need to interpret variability, determine which results support a hypothesis, or compare experimental groups.

Is statistics on MCAT Chem/Phys?

Yes. Chem/Phys can require you to interpret graphs, tables, slopes, relationships between variables, experimental measurements, and uncertainty. The AAMC categorizes approximately 10% of the section under Data-Based and Statistical Reasoning.

Is statistics on MCAT CARS?

Statistics is not a designated content area in CARS. CARS assesses comprehension and reasoning from humanities and social science passages rather than the AAMC’s four Scientific Inquiry and Reasoning Skills used in the three science sections.

Do I need to know confidence intervals for the MCAT?

Yes. The AAMC specifically lists interpreting confidence intervals as an example of Data-Based and Statistical Reasoning. Focus on understanding what a confidence interval communicates about an estimate and its uncertainty rather than learning complicated hand calculations.

Do I need to know t-tests or ANOVA for the MCAT?

You generally do not need to learn how to manually perform advanced statistical tests such as t-tests or ANOVA for the MCAT. Understanding the meaning of statistical significance and how to interpret research results is much more important than learning the mathematical procedures behind advanced statistical tests.

Do I need to memorize statistics formulas for the MCAT?

Very few statistics formulas deserve significant memorization time. You should be able to calculate simple measures such as a mean and range and be comfortable with percentages, ratios, and probabilities, but interpretation of concepts such as standard deviation, significance, and confidence intervals is much more important.

Are error bars on the MCAT?

They can be. MCAT graphs may include error bars, and you should first identify what those error bars represent before deciding what they tell you about variability or statistical significance. Do not automatically assume that overlapping or non-overlapping error bars prove whether two groups are statistically different unless the passage gives you enough information to make that conclusion.

Is correlation on the MCAT?

Yes. You should recognize positive and negative correlations and understand that correlation alone does not establish causation. The AAMC specifically includes using data to explain relationships between variables within its Data-Based and Statistical Reasoning framework.

Is a statistics class a prerequisite for the MCAT?

The MCAT itself does not require you to complete a statistics course before taking the exam. Whether you need a statistics course for your undergraduate degree or for individual medical schools is a separate question, so you should check the requirements of the schools where you eventually plan to apply.

What’s the best way to study statistics for the MCAT?

Start by learning the small group of statistics and research concepts identified by the AAMC, then move into passage-based practice. Once you understand mean, median, standard deviation, significance, confidence intervals, correlations, error, and research variables, reviewing graphs and experimental passages will usually be more valuable than continuing to read increasingly advanced statistics material.