Meaning from Data: Statistics Made Clear

Course No. 1487
Professor Michael Starbird, Ph.D.
The University of Texas at Austin
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Course No. 1487
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Course Overview

Who was the greatest baseball hitter of all time? How likely is it that a poll is correct? Is it smart to buy last year's highest-performing stock? Which hospital has the best outcome for a given procedure? When is it a good idea to buy a product's extended warranty?

These questions all involve the interpretation of statistics, as do a surprising number of other mysteries, including: Is the "hot hand" among sports players real? How can you tell if Shakespeare is the probable author of a newly discovered poem? What is a guilt-free way to get someone to admit to cheating? And, how does a tax assessor calculate the market value of a house?

Meaning from Data: Statistics Made Clear is your introduction to a vitally important subject in today's data-driven society. In 24 half-hour lectures, you will explore the principles and methods that underlie the study of statistics. You have probably heard such terms as mean, median, percentile, quartile, statistically significant, and bell curve, and you may have a rough idea of what they mean. This course sharpens your understanding of these and scores of other statistical concepts and shows how, properly used, they can extract meaning from data.

Become Statistically Savvy

These challenging yet accessible lectures assume no background in mathematics beyond basic algebra. While most introductory college statistics courses stress technical problem solving and plugging data into formulae, this course focuses on the logical foundations and underlying strategies of statistical reasoning, illustrated with plenty of examples. Professor Michael Starbird walks you through the most important equations, but his emphasis is on the role of statistics in daily life, giving you a broad overview of how statistical tools are employed in risk assessment, college admissions, drug testing, fraud investigation, and a host of other applications.

Statistical Adventures

Professor Starbird is a master at conveying concepts through examples. Some of these include:

  • When is a Lottery not a Lottery? When it is not truly random. The 1969 Vietnam War draft lottery assigned young draft-age men a ranking for induction based on their birthdays, which were placed in capsules and drawn from a container, supposedly at random. But by computing the statistical correlation for the order-of-draw, it's clear that a nonrandom variable was at play. The most likely explanation is that the capsules with the dates were not thoroughly mixed.
  • The Birthday Challenge: What is the probability that out of 50 random people, two of them share the same birthday? The chances are much higher than most people think.
  • The Chicken Soup Method: How can 1,000 randomly chosen people serve as a predictor for the behavior of hundreds of millions of voters? This is the essence of a political poll, and its effectiveness should be no more surprising than the fact that that a single taste of chicken soup is enough to predict the overall saltiness of the batch, whether the batch is in a cup or a giant vat.
  • Beware of Fallacious Reasoning: At the O. J. Simpson murder trial, Simpson's lawyer Johnnie Cochran countered evidence that Simpson had beat his wife with a statistic that only 1 in 1,000 wife beaters go on to kill their wives. Therefore, Cochran argued, there was only a 1 in 1,000 chance that Simpson went on to commit the murder. Professor Starbird discusses the fallacies in this argument, including the fact that a wife was actually murdered in this case, so the relevant question should be: What is the probability that she had previously been beaten?
  • Who Really Won the 1860 Presidential Election? Establishing the will of the people in an election can be tricky, especially when three or more candidates are involved. Professor Starbird shows how the results of the four-way presidential race of 1860 can be interpreted as giving victory to each of three candidates, depending on the voting scheme employed. Abraham Lincoln won according to the rules in place, but given other equally valid rules, the victor—and history—would have been very different.

Statistics Is Everywhere

Statistical information is truly everywhere. You can't look at a newspaper without seeing statistics on virtually every page. You can't talk about the weather forecast without invoking statistics. Statistics obviously arises in business and social science but even enters the arts in analyzing manuscripts. And you'd better not go to a casino without understanding statistics. "It's really harder to find somewhere where statistics isn't important than to find the places where it is," says Professor Starbird.

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24 lectures
 |  Average 30 minutes each
  • 1
    Describing Data and Inferring Meaning
    The statistical study of data deals with two fundamental questions: How can we describe and understand a situation when we have all the pertinent data about it? How can we infer features of all the data when we know only some of the data? x
  • 2
    Data and Distributions—Getting the Picture
    The first three rules of statistics should be: Draw a picture, draw a picture, draw a picture. A visual representation of data reveals patterns and relationships, for example, the distribution of one variable, or an association between two variables. x
  • 3
    Inference—How Close? How Confident?
    The logic of statistical inference is to compare data that we collect to expectations about what the data would be if the world were random in some particular respect. Randomness and probability are the cornerstones of all methods for testing hypotheses. x
  • 4
    Describing Dispersion or Measuring Spread
    This lecture defines and explores standard deviation, which measures how widely data are spread from the mean. The various methods of measuring data dispersion have different properties that determine the best method to use. x
  • 5
    Models of Distributions—Shapely Families
    Any shaped curve can model a data set. This lecture looks at skewed and bimodal shapes, and describes other characteristically shaped classes of distributions, including exponential and Poisson. Each shape arises naturally in specific settings. x
  • 6
    The Bell Curve
    The most famous shape of distributions is the bell-shaped curve, also called a normal curve or a Gaussian distribution. This lecture explores its properties and why it arises so frequently—as in the central limit theorem, one of the core insights on which statistical inference is based. x
  • 7
    Correlation and Regression—Moving Together
    One way we attempt to understand the world is to identify cases of cause and effect. In statistics, the challenge is to describe and measure the relationship between two variables, for example, incoming SAT scores and college grade point averages. x
  • 8
    Probability—Workhorse for Inference
    Probability accomplishes the seemingly impossible feat of putting a useful, numerical value on the likelihood of random events. Our intuition about what to expect from randomness is often far from accurate. This lecture looks at several examples that place intuition and reality far apart. x
  • 9
    Samples—The Few, The Chosen
    Sampling is a technique for inferring features of a whole population from information about some of its members. A familiar example is a political poll. Interesting issues and problems arise in taking and using samples. Examples of potential pitfalls are explored. x
  • 10
    Hypothesis Testing—Innocent Until
    This lecture introduces a fundamental strategy of statistical inference called hypothesis testing. The method involves assessing whether observed data are consistent with a claim about the population in order to determine whether the claim might be false. Drug testing is a common application. x
  • 11
    Confidence Intervals—How Close? How Sure?
    Headlines at election time frequently trumpet statistics such as: "Candidate A will receive 59 percent of the vote, with a margin of error of plus or minus 3 percent." This lecture investigates what this "margin of error" statement means and why it is incomplete as written. x
  • 12
    Design of Experiments—Thinking Ahead
    When gathering data from which deductions can be drawn confidently, it's important to think ahead. Double-blind experiments and other strategies can help meet the goal of good experimental design. x
  • 13
    Law—You’re the Jury
    Opening the second part of the course, which deals with applying statistics, this lecture focuses on two examples of courtroom drama: a hit-and-run accident and a gender-discrimination case. In both, the analysis of statistics aids in reaching a fair verdict. x
  • 14
    Democracy and Arrow’s Impossibility Theorem
    An election assembles individual opinions into one societal decision. This lecture considers a surprising reality about elections: The outcome may have less to do with voters' preferences than with the voting method used, especially when three or more candidates are involved. x
  • 15
    Election Problems and Engine Failure
    The challenge of choosing an election winner can be thought of as taking voters' rank orderings of candidates and returning a societal rank ordering. A mathematically similar situation occurs when trying to determine what type of engine lasts longest among competing versions. x
  • 16
    Sports—Who’s Best of All Time?
    Analyzing statistical data in sports is a sport of its own. This lecture asks, "Who is the best hitter in baseball history?" The question presents statistical challenges in comparing performances in different eras. Another mystery is also probed: "Is the 'hot hand' phenomenon real, or is it random?" x
  • 17
    Risk—War and Insurance
    A discussion of strategies for estimating the number of Mark V tanks produced by the Germans in World War II brings up the idea of expected value, a central concept in the risky business of buying and selling insurance. x
  • 18
    Real Estate—Accounting for Value
    Tax authorities often need to set valuations for every house in a tax district. The challenge is to use the data about recently sold houses to assess the values of all the houses. This classic example of statistical inference introduces the idea of multiple linear regression. x
  • 19
    Misleading, Distorting, and Lying
    Statistics can be used to deceive as well as enlighten. This lecture explores deceptive practices such as concealing lurking variables, using biased samples, focusing on rare events, reporting handpicked data, extrapolating trends unrealistically, and confusing correlation with causation. x
  • 20
    Social Science—Parsing Personalities
    This lecture addresses two topics that come up when applying statistics to social sciences: factor analysis, which seeks to identify underlying factors that explain correlation among a larger group of measured quantities, and possible limitations of hypothesis testing. x
  • 21
    Quack Medicine, Good Hospitals, and Dieting
    Medical treatments are commonly based on statistical studies. Aspects to consider in contemplating treatment include the characteristics of the study group and the difference between correlation and causation. Another statistical concept, regression to the mean, explains why quack medicines can appear to work. x
  • 22
    Economics—“One” Way to Find Fraud
    Economics relies on a wealth of statistical data, including income levels, the balance of trade, the deficit, the stock market, and the consumer price index. A surprising result of such data is that the leading digits of numbers do not occur with equal frequency, and that provides a statistical method for detecting fraud. x
  • 23
    Science—Mendel’s Too-Good Peas
    Statistics is essential in sciences from weather forecasting to quantum physics. This lecture discusses the statistics-based research of Johannes Kepler, Edwin Hubble, and Gregor Mendel. In Mendel's case, statisticians have looked at his studies of the genetics of pea plants and discovered data that are too good to be true. x
  • 24
    Statistics Everywhere
    The importance of statistics will only increase as greater computer speed and capacity make dealing with ever-larger data sets possible. It has limits that need to be respected, but its potential for helping us find meaning in our data-driven world is enormous and growing. x

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Your professor

Michael Starbird

About Your Professor

Michael Starbird, Ph.D.
The University of Texas at Austin
Dr. Michael Starbird is Professor of Mathematics and University Distinguished Teaching Professor at The University of Texas at Austin, where he has been teaching since 1974. He received his B.A. from Pomona College in 1970 and his Ph.D. in Mathematics from the University of Wisconsin-Madison in 1974. Professor Starbird's textbook, The Heart of Mathematics: An Invitation to Effective Thinking, coauthored with Edward B. Burger,...
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Reviews

Meaning from Data: Statistics Made Clear is rated 4.0 out of 5 by 61.
Rated 4 out of 5 by from My review of "Meaning From Data: Statistics Made Clear" by Michael Starbird: Professor Starbird does a good job of not only covering the concepts of statistics, but also relating them to real-world applications, such as medicine, education, health, polls, and so on. When the viewers see how the field is used in other disciplines, it becomes more relatable and meaningful.
Date published: 2015-05-23
Rated 5 out of 5 by from Mathematics 0ver a 24 Hour Day Professor Starbird converts mathematics into a discipline that can be directly applied to our everyday lives. He uses statistics as one more dimension to our our external rational filters that increases our appreciation of world in which we live and how we might use statistics to increase our understanding of common events we previously did not question and usually took for granted.
Date published: 2015-01-31
Rated 2 out of 5 by from Statistics For this specific course the instructor should have been more specific about some essential key elements of this complicated field of statistics. He jumps from linear regression to Z values without explaining basic elements of what a bell shape is or why a sample is used to extrapolate data to make conclusions. No what i was expecting from this course.
Date published: 2014-12-29
Rated 5 out of 5 by from Ideal Introductory Course This is an excellent basic introduction to statistics. In-depth and relevant examples are presented by Dr. Starbird, who is clearly enthusiastic and knowledgeable about his subject. The course is light on math, which makes it a good overview prior to more intensive study. The focus is on fundamental concepts, strategies, and basic understanding, as well as potential shortcomings, of statistical approaches. Highly recommended.
Date published: 2014-12-10
Rated 3 out of 5 by from Sloppy presentation, cannot recommend Personable professor with friendly folksy style. A useful course if you want to learn about statistics, what they mean and how they're used: it is an illustrated introduction to the subject and its applications, suitable for high school as well as mature students. The first 12 lectures explain the concept and structure of statistics & data compilation, but I found the lecture on standard deviation very clumsy in presentation... this professor at times is hesitant and frequently stumbles over his words. The final 12 lectures present scenarios applying statistics, including a difficult-to-follow talk on distorting, misleading and lying statistics! The one remarkable aspect of this lecture series to me is how statistics can be used and interpreted, to produce many very different results from the same data. This is shown to be particularly the case with voting and elections, fascinating and somewhat alarming! Overall, I cannot recommend this course; I feel strongly that it could -- and assuredly should -- have been a lot better, in terms of presentation and clarity. It appears that all lectures were solo-takes whereas several ought to have been re-recorded because of the hesitancy and stumbling. I think a well-illustrated short book might be a finer investment.
Date published: 2013-12-31
Rated 4 out of 5 by from Great content but not deep enough This was a wonderful introduction to statistics. The professor has a great style of presentation and a wonderful sense of humor. He explains concepts well, especially the limitations of statistics. The strengths of the course were the clear explanations of the basics and how they apply to fields such as sports, voting, and the justice system. There is also a brilliant lecture on the misuse of statistics. My main concern was that some concepts should have been presented in greater detail (ANOVA, t-test, Fisher exact test, etc). Also the limitations of the normal distribution curve were not covered in sufficient detail. If your goal is a simple overview of statistics, then this course is very enjoyable and presents material that everyone should know. If, however, you need to use statistics at work or study, then you certainly need more detail than the course provides. I personally found this detail in the book 'Statistics in Plain English' by T Urdan which I also highly recommend. Overall, a very enjoyable course.
Date published: 2013-11-28
Rated 5 out of 5 by from Significant Insight, not a how-to If you want insight into how to extract meaning from statistical summaries then this course is for you. I wish everyone graduating from high school was required to take a course like this one. Few topics are as dry as statistics but Dr. Starbird makes it interesting and relevant. His delivery is very good, his sense of humor pleasing without being silly or annoying. The material is well chosen from real life examples of how to use and how to detect misuse of statistics. If some reviewers think that Dr. Starbird is boring or unprepared for teaching this course then they have probably never had a typical college class in statistics. My professors were mind-numbingly boring and never presented the concepts clearly, however well they did the math. I am surprised that some people bought this course expecting a tutorial how-to approach. Until the new calculus series came out none of the non-highschool courses are how-to's and the title is "Meaning from Data" not "How to Calculate Batting Averages". If that's what you want, buy this course and any of the many mathematical how-to texts out there. You will then have both a deep understanding and the ability to use statistics yourself. I have used statistics professionally and academically for decades and still this course gave me new insights into the use and abuse of statistics. Many concepts that were vague from academic studying and took years of experience to clarify are clearly revealed in this wonderful short course. By the way, it has an excellent companion in the probability course. The two subjects are so intertwined they really belong together but Dr. Starbird has done a good job of making two separate courses that complement without too much overlap. That takes deep knowledge of both subjects and good organization and planning.
Date published: 2013-06-15
Rated 3 out of 5 by from Nice General Discussion but No Problem Solving This is a great conversational description of the "idea" of statistics. The professor is a clear concise and experienced lecturer who will hold your attention. Some wonderful historical context about the conceptual development of statistics. However, if you are looking for detailed instruction on how to execute specific statistical calculations (correlations, deviations from means, etc.) against a given sample or set of samples, you need to look else where.
Date published: 2013-04-26
Rated 1 out of 5 by from A Joke Get this course only if you need a hipnotic regression therapy, because these lectures inevitably will put you into a trance. The lecture presentation is dreadful and extremely boring. To be honest, I expected this presentation to be aimed at an adult audience, but found out that it is aimed at three-year-olds instead. A very childish presentation and significantly lacking and poor material content. The Calculus course by the same professor is of similar sub-par quality.
Date published: 2013-01-26
Rated 3 out of 5 by from Statistics for those who don't want to do math! Well presented and interesting but lacking usable tools and content you can take away and apply. Are there people who want to know what statistics is about and what it can achieve without knowing how to do anything themselves? If so, then this course would be perfect for them. If you are looking for a statistics course to help you do statistics, then this isn't it. I found the professors probability lecture series much more useful than this one.
Date published: 2012-11-13
Rated 2 out of 5 by from Unwatchable I bought this course six years ago because I work with data and need to have a basic understanding of statistics. I've bought several courses and most of them have been excellent, but every time I tried to watch this I found myself going to sleep--literally. I tried watching it when I was well-rested, and even drank coffee to help. Granted, there's something inherent in a video of a professor talking about statistics in a fake classroom environment that is less than scintillating, no matter the quality of the production or instructor. And it's hard to criticize any one thing about it. But the bottom line is that the overall experience just fell flat. I subsequently bought a book and found it MUCH more engaging.
Date published: 2012-07-28
Rated 2 out of 5 by from Should have read the reviews I had ~6 semesters of statistics decades ago - thought this would provide the basics so I could try to understand again. The course was of limited use to me. About four of the lectures were useful - the ones on population and sample statistics. The rest were mildly interesting, but did not seem related to the title of the course. The lecture on hypothesis testing lacked enough rigor to be useful. In fact, one example incorrectly used the null hypothesis as what he wanted to show (that is what the alternate hypothesis is for). Finally, most of the course is at a high school level.
Date published: 2012-04-29
Rated 4 out of 5 by from A Nice Introduction to Statistics Prof. Starbird did a nice job with this course. His lectures were organized and his presentation was clear. I enjoyed the way he set up the course. The first half supplied some basic statistical concepts, and the second half supplied some real-life examples. I would agree with other reviewers that, at times, the course went a bit slow. In my case, I felt that had to do with some of the basic concepts already being familiar to me. For example, I would guess that most people buying a course from TTC would know what a Bell Curve is -- yet, Prof. Starbird dedicates a lecture to it. For some that is a good thing; for others it might be too much. Overall, this was a nice introduction to statistics. I would recommend the course to others who wish to know a bit about statistics.
Date published: 2012-04-22
Rated 4 out of 5 by from The Meaning of Statistics... This is a great entry-level course on what Statistics is, and what it can do for you. Dr. Starbird, as the title of the course says, shows us how to get meaning from data via Statistics. To do this, we get away from the math in this course, and look at questions more carefully and in different ways. (If you want a college-level class with many formulas, buy a textbook instead.) I especially enjoyed the lectures that focused on how a Statistical value can be misleading, or mean something other than what it seems. Dr. Starbird spends a great deal of time helping us see how to assign value and meaning to what Statistics tells us. Dr. Starbird's teaching skills and speaking style are very good, energetic, and interesting. His humor (and great examples) added a great deal to what could have been a dry course.
Date published: 2012-02-08
Rated 5 out of 5 by from Statistics for all. I have watched this course an average of 5-6 times plus or minus 1-2 lectures. This course should be rated statistically significant, definitely 3 standard deviations above the mean. With this course information, I can now extrapolate my success as a statistician. I have watched this course while taking a statistics class. It has helped me succeed beyond the fourth quartile. Thanks to Prof. Starbird for making such an interesting and life changing DVD.
Date published: 2011-12-18
Rated 4 out of 5 by from Meaning From Data After viewing all 24 lectures, i realized I missed points in many lectures, because the pace was so slow. The Professor seems to know his stuff, however, I feel the information could have been presented in a more lively way and the number of lectures could have been reduced without loosing much content. I still received some great ideas and I do recommend the course, however, be mindful that it is unduly long.
Date published: 2011-12-15
Rated 3 out of 5 by from Understated presentation This course covers an important topic but its pacing tries my patience at times. It seems as if above all, the goal was not to threaten anyone. I would rather have had the same material presented in a more concise form, say in 18 lectures rather than 24.
Date published: 2011-10-28
Rated 5 out of 5 by from Brings Statistics to Life Meaning from Data" is a descriptive statistics course--not a "hard-core" math course. It is ideal for one wanting to understand how statistics affects many life decisions about health, economics, legal decisions and more. For one (like myself) who has studied statistics, the course is a good refresher on selecting appropriate statistical tests for various situations. Dr. Starbird brings statistics to life!. Dr. Starbird is not a polished speaker and has hesitations in his presentations. However, he is articulate and literate. His presentation style is not distracting, but rather, quaint. He interjects examples that at first may seem irrelevant, but turn out to be appropriate. He is a gifted teacher and clearly wants his students to understand concepts, applications and conclusions.
Date published: 2011-09-29
Rated 4 out of 5 by from Solid Introduction to the field. I used this course to supplement some of my college coursework and feel the course gave a solid introduction into the field of statistics. Unfortunately, the course did drag on in some instances, and I found myself straining to pay attention. Still, a solid course if you are interested in learning more about probability and statistics.
Date published: 2011-09-18
Rated 4 out of 5 by from Concepts, Not Formulas One shouldn't watch the nonsense presented on the evening news without understanding how easily statistics can be easily misused by anyone with an agenda. This requires knowing the critical difference between mean and mode and when to trust/distrust one or the other. With all Great Courses products, the buyer is well advised to read the reviews, not just the course description. Many of us comment on what we thought we were buying, not what the course is intended to provide. I found this to be a very good introduction to the CONCEPTS of statistics. I honestly don't care about the proof of the mathematical equations and would have been dissatisfied if that had been a major part of the lectures. The goal of a course like this one is to show you that statistical analysis is both interesting and necessary to understand events.
Date published: 2011-03-08
Rated 5 out of 5 by from Understanding Statistics without math Course is powerful to explain the logic of data gathering and understanding the foundations of statistics. I really like the course without all the math. One must understand what statistics is attempting to explain. If you understand that, the math is easy. It is true there is little math in the course. This is a course in understanding data not doing simple math. Once you go through this course and you need to do the math, there are plenty of stat problems you can engage in by buying a cheap five dollar handbook. Great course, often math is taught and the professor misses the most important point--teach the concept first before doing the math. This is a logical approach...an understanding of the subject that remains with you long after the course.
Date published: 2011-01-15
Rated 2 out of 5 by from OK, but not Great As a doctoral student in another field, I felt I needed a primer in statistics. I felt like the professor's content was good, but was disappointed in his constant corrections he had to make. He should have either prepared more or had a prompter. I also felt that his examples could have been much better, more applicable. It was annoying waiting for graphics to pop up while he was straining to see his monitor. He is a good teacher and has a nice personality, but I've come to expect more from the Teaching Company. Thanks Teaching Company for doing what you do.
Date published: 2010-07-16
Rated 3 out of 5 by from Approach With Caution After hearing rave reviews of Dr. Starbird's courses, I finally decided to purchase one. Since I had taken a Statistics course in college, I decided to take this course, and see what changes had been made in the field in the last thirty years. Let me say that I am a music major, and although I did quite well in Geometry, I did not do well in other Math courses. On the positive side, Dr Starbird is a very interesting and engaging presentor. One gets the impression that he is right there in the room, and that one could ask him a question at any time. His knowledge in exceptional. Although the material gets quite technical, he still keeps interesting examples available. There are a few areas that I was a little surprised at in the course presentation. For example, in most statistics presentations and textbooks, the conecpts of 'mean, median and mode' are all presented together. Dr Starbird does not even mention the concept of mode(which is the most frequently occuring score in a given group of data points) This is somewhat curious to me, since all three numbers help to tell a bit different vantage point of any given set of data. In addition, I realize that the professor is attempting to keep the math part to a bare minimum, but how can one present statistics as a mathematical tool, it math isn't used? That is a bit like a German course just talking ABOUT the language, and not the German language itself. In other words, I sould like to see more math used in the presentations. I am sure that a gifted teacher like Dr Starbird would have little difficulty in bringing down these numerical examples to an understandable level. Perhaps due to these concerns, I did not really feel as if there was something that I "could take with me" from the course and think about in my daily life, as I usually walk away with from the other courses that I have taken. I am willing to give Dr. Starbird another try in another course; perhaps it is my lack of mathematical skill that is creating my difficulty. I also might suggest to someone that has a similiar background to mine to keep an open mind, and sue great care with this course.
Date published: 2010-05-06
Rated 2 out of 5 by from Not a college-level course Unfortunately this course tries to teach math without using math. Most of the mathematical concepts I learned in my college social statistics class are simply missing. So far my impression is that The Teaching Company's high school math courses actually teach how to do the math, while their "college" courses try to avoid it. When I buy a math course, I want to learn actual math.
Date published: 2010-03-24
Rated 5 out of 5 by from Excellent Overview Professor Starbird does a wonderful job of explaining the science of statistical analysis without getting into the underlying math. The first part of the course introduces the basic concepts used in statistics, each lecture building on the foundation laid down previously. In the second half of the course he discusses interesting questions that statistics can help solve. Who knew, for instance, that Mendel fudged his data when revolutionizing our understanding of genetics? Professor Starbird is an engaging lecturer with a fun sense of humor and an easy-going manner. He has a real knack for synthesizing complex ideas and then explaining them using common sense examples. This is an excellent course if you want to understand statistical analysis and don't need to know how to perform the calculations. All but one of the lecturers was clear and enjoyable; but watch out for the lecture on factor analysis. I still have no idea what he was talking about.
Date published: 2010-02-02
Rated 5 out of 5 by from Great Course Prof Starbird understand very well to explain a normally very dry topic with real life examples. It is fun for me to actually learn to NOT "fall asleep while looking at a sheet of numbers" (his quote at the very beginning of his course).
Date published: 2010-01-08
Rated 4 out of 5 by from Some lectures better than others... My husband thought Dr. Staribird did an excellent job with the muliple regression lecture - great explantion and visuals. He was not happy wtih the lecture on factor analysis - admittedly a very complex statistical concept that was not made very clear even with the examples. There were some lectures that seemed to have a lot more talking with few graphics in comparison and these lectures were not up to Dr. Starbird's previous performance levels. This was more of a review course for him but still very useful in everyday situations and his current work environment. He did enjoy the course but felt it could have used some additional real world examples to clarify of the concepts in the lectures from 12-18.
Date published: 2009-09-04
Rated 5 out of 5 by from Top Notch Professor Starbird is a terrific lecturer and this is probably my favorite course among the ones he offers. You will examine fundamental ideas related to statistics and have a good time doing it.
Date published: 2009-07-26
Rated 5 out of 5 by from A very nice introduction I lent this to a friend of mine who's studying to become a teacher. She's had a lot of experience tutoring mathematics and is very good at it. She knew the material, but was fascinated, and inspired, by how well it was presented in this course. My own response was the same. Well done.
Date published: 2009-06-14
Rated 4 out of 5 by from Good overview Prof Starbird uses a range of excellent examples of how statistics are applied to a variety of problems. I would have liked to have seen a fuller explanation of the Normal Distribution and the Chi Squared distributions, as these under pinned a lot of the practical examples. Overall a worthwhile course and well presented (Prof Starbird needs a set of new jokes though).
Date published: 2009-06-04
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