Many students struggle with statistics, but business students may struggle more than most based on our recent study of statistics students and tutors.
Why? And what tips do tutors have to help MBA students with statistics?
We asked statistics tutors who work with MBA students, and here are 10 of the best tips they shared to help MBA students with statistics:
Important statistical concepts for MBA students to understandMany MBA students come in with little experience in statistics and analytics. Becoming familiar with means, medians, standard deviation, normal distributions, and t-scores will allow them to apply data to business decisions, backing or challenging their hunches.
Statistics are purely numbers. Unless understood in the context in which the raw data was collected, the wrong conclusion can be drawn. A graph showing that an increase in pizza slices eaten the day of a test improves test scores may have a regression coefficient of nearly one. But this makes no sense considering the variables being studied - yet, statistically, the relationship is almost perfect.
It's important to understand that statistics is just another tool to use. It is the study of historical events and using that history to forecast future events using mathematical formulas. A student should learn to appreciate those formulas and use them. Just like we study history to see how historical events apply to current events, we study historical data to help us forecast the future.
I think statistical significance represents the most important concept for MBA students in statistics because it points businesses, consumers, companies, and innovators to relevant trends. When an event occurs a significant amount of time, companies pay attention and direct their resources there. Business leaders depend on statistical research to provide provable facts defending everything from budgets to marketing to product introductions.
Although there are many important concepts, such as sampling distributions, hypothesis testing, and analysis of variance, the most salient is regression analysis. Because it is widely used in many industries and disciplines, from academic research, Marketing and Life Sciences to the Social Sciences, regression analysis stands as one of the most fundamental statistical tools used to make informed business decisions. A former MBA student recently told me that during his interview process for a Manager of Business Analysis position, the hiring manager asked that he analyse a large data set using multiple regression and write a brief report of his findings.
Common struggles MBA students face with statisticsFirst, students allow the title, ‘Statistics’, to intimidate them. Getting too wrapped up in the name and the numbers and graphs can make your head spin. Think of statistics as merely a method to organise the occurrence of certain events relevant to a course of action meaningful to the observer. A business can use statistics to decide on billboard placement while an individual may use it to weigh the benefit of cable TV. This science offers specific ways to outline the importance of certain events.
Often MBA students struggle with the difference between sample statistics and population parameters. Suppose you want to know the average home price of certain types of homes in a particular area. If you have all the data (think Zillow), you might apply a filter and then just average the prices of all recently sold homes that meet your criteria. This is calculating a population average directly. If you don't have the data, you might instead take a sample, calculate a sample mean, and then infer the ‘population’ average using the Central Limit Theorem. Understanding how to make inferences from sample statistics to population parameters using the Central Limit Theorem is a major key to your success.
I find that one of the most common struggles MBA students have in regards to statistics is taking highly complex data and charts, and translating them into the simple components that make it up. So often they have immense calculating skills and great knowledge of ideas that go into interpreting data, but they struggle to apply it and break it down into simple terms. For instance, when interpreting graphics regarding multiple data points, it is easy to get lost in each data point and what they mean, rather than to take the data as a whole and interpret the trend. Establishing the over-riding trend of what the data is trying to get across allows you more power in conveying the message to your team and allows you to make more informed decisions, both on the test and in the real world.
A common struggle MBA students have, and a struggle I had when taking statistics in my MBA programme, is understanding which formula to use in each situation. Even using Excel for calculations on something as basic as standard deviation, there are two different functions, one formula for a sample and one formula for a population. The function to use depends on the situation. As one of the youngest branches of math (about 75 years old compared to at least 1,000 years for algebra or more than 2,400 for geometry) statistics can seem messy. It can have the feel that some of the rules (like a ‘large’ sample is 30 or more and a ‘small’ sample is less than 30) were devised by a couple grad students in a pub. Even so, statistics is a branch of math that MBA grads will find useful in their career.
Most MBA statistical courses are required and focus on memorising a set of formulas to solve problems. The issue for students is that they often do not learn the underlying reasoning and theory, relying too much on just the mechanics. Thus they finish the course without a solid understanding of how, when and why these analyses should be used. Since we live in a probabilistic world, especially when it comes to economic issues, a good grasp of these concepts and the ability to solve future problems using these concepts is almost mandatory in most business settings.
Wyzant is the largest network of experts, tutors and coaches for 1-on-1 learning. Business students may struggle more than most with statistics based on our recent study of statistics students and tutors.
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