The Business Statistics and Analysis Capstone is an opportunity to apply various skills developed across the four courses in the specialization to a real life data. The Capstone, in collaboration with an industry partner uses publicly available ‘Housing Data’ to pose various questions typically a client would pose to a data analyst. Your job is to do the relevant statistical analysis and report your findings in response to the questions in a way that anyone can understand. Please remember that this is a Capstone, and has a degree of difficulty/ambiguity higher than the previous four courses. The aim being to mimic a real life application as close as possible.
Q&A with Garfield Fisher
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En provenance du cours de Rice University
Business Statistics and Analysis Capstone
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À partir de la leçon
Business Statistics and Analysis Capstone: An Introduction
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Sharad BorleAssociate Professor of Management
Jones Graduate School of Business
Let's say I have a bit of a unique perspective on that.
Having 30 years experience, I can see that data sets are becoming larger
and not necessarily more complicated, but definitely larger.
And also to text analytics, data that doesn't necessarily fit a simple format;
that's definitely becoming more common.
But the industry has remained consistent
and it's been remained consistent in that it's data collection,
data analysis and data reporting, regardless of whether you're using Excel
or other statistical software packages, that is what's consistent.
And being able to ask the right question,
perform the right analysis, and deliver the right results is equally important,
but also there is one thing that I think is happening and it will continue to happen,
is storytelling.
And that is being able to take the results, tell a story
that your CEO or your decision-makers are able to understand.
Business statistics is a little bit different than, what I would say,
IT people would do with data.
Business statistics looks deeper into the questions and looks at the appropriate analysis
that can be perform with the data.
Business statistics goes well beyond simply doing frequencies or tabulations
and creating pie charts and bar charts.
It actually asks questions.
And the point of asking the question is to find the right data to answer that question.
So I'd say understanding business statistics versus just simply understanding
how to tabulate data is critically important.
That separates the employee, or the consultant,
from a pack of 90 percent of everyone who can use Excel
and do simple statistics to 10 percent of the workforce
who really know how to understand the analysis and communicate results.
Excel is one of those software packages
that I feel is completely underutilized when it comes to advanced analysis.
There's so - there's so much power to Excel beyond data cleaning,
beyond running frequencies and doing pie charts.
Excel has built in it tools that allow you to do difference testing, such as T-tests,
correlation tests and advanced regression analysis for prediction.
I feel that the majority of people
that I have met who use Excel for their financials simply do formulas.
And they're very great formulas and complicated formulas,
but it really scratches the surface of what Excel is capable of doing.
And then you partner Excel with some advanced statistical software like SPSS, SAS and R
and you truly have all the skills
that are necessary to be a very productive member
of a data science team in any organization,
whether it's public sector, private sector,
or going out much like myself and becoming a consult.
So, I would say that the skills that are required in today's workforce
is a range of skills often referred to as data science.
There's the IT skills and that's being able to build systems that collect the data,
store the data, warehouse the data.
Then there's the analytic skills or statistical skills.
And then beyond the statistical skills there's data visualization,
that's the reporting, the pie charts, the dashboards.
And more recently, there is the data journalism or being able to tell the story.
So for instance, you have a pie chart, you have a bar chart.
They do tell stories if you're looking closely enough,
if you're looking into what analysis went into that particular chart.
For instance, you might do a T-test, which then a bar chart is very appropriate.
But that T-test then gives you levels of significance
and you can draw conclusions from that.
And so simply looking at a bar chart
and saying there's one group that performed higher than another group,
simply by looking at the chart, is probably ill-advised.
You need to go and look at the chart,
look at the statistic that was performed and then tell the story.
And I'd say moving forward telling the story
is probably the most important part of data analysis.
Because if you cannot tell the story about what that chart is communicating
and what analysis went into it, your audience isn't going to get the full picture.
I've noticed over the last several years that the demand has increased.
It's very difficult to find people who have the ability to not only collect the data,
analyze the data, but communicate the data,
but have that full picture.
Recently, I read where there's at least 400,000 jobs going unfilled in the U.S. alone
for data management positions.
Data management would include things like using Excel,
storing your data in formats that can be easily shared,
but also being able to communicate to someone who can do the analysis,
what analysis needs to be done.
I've also read another report where there's over a million jobs
for people who have what would be referred to more as the hard skills.
And again, the skills that you'd be learning in this - in this course,
skills like performing descriptive analysis, advanced analysis and particularly,
regression analysis and prediction.
That is where I see the market going.
It's being able to use data that we've gathered for the last 20, 30, 40 years
and using that data to predict the next two, three, five or 10 years.
And anyone who learns those skills, regardless of the software,
certainly will be in a very good position to be able to take advantage
of the demand that exists right now for that particular type of job.
And I would also say that there's no - it's not necessary
that any one focus on one particular type of job,
whether that is in public sector or a private sector or consulting.
I would say no matter what you decide to do,
having those skills is certainly an opportunity to basically write your own ticket
for the job that you want for the rest of your life.
And I certainly have been able to take advantage of that.
I started early, at the age of 19.
I had one of my first consulting jobs
and realized from that point I'd never wanna work again ,
so I continued to be a consultant.
So there's just a little plug there.
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