(Part 2) Best business education & reference books according to redditors
We found 730 Reddit comments discussing the best business education & reference books. We ranked the 291 resulting products by number of redditors who mentioned them. Here are the products ranked 21-40. You can also go back to the previous section.
31. Probability and Statistics for Engineering and the Sciences
4 mentions
Used Book in Good Condition
33. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
3 mentions
We're in the midst of an opioid epidemic to which the state has responded almost entirely with force--it is the prohibition of drugs which leads to their negative consequences.
http://press.uchicago.edu/ucp/books/book/chicago/D/bo23530208.html
https://www.amazon.com/Drug-War-Crimes-Consequences-Prohibition/dp/0945999909/ref=sr_1_1?ie=UTF8&qid=1498778246&sr=8-1&keywords=jeffrey+miron
While you likely won't have any issues with learning the content, teaching physics is a very, very different beast than teaching mathematics. There are similarities, for sure. Lots of them. But there are also vast differences.
If you're serious about teaching physics, especially at the AP level, look into these resources:
Feel free to PM me if you have any questions. I have lots more to say on the subject :P
So I hope everyone has seen the manga version of C21: https://twitter.com/EDerenoncourt/status/1170343228819853313
But there's also manga linear algebra: https://nostarch.com/linearalgebra
and manga Bayesian Statistics: https://twitter.com/tkasasagi/status/1154975832361717765
EDIT: it never stops https://www.amazon.com/Manga-Guide-Regression-Analysis/dp/1593277288
> What the fuck does that even mean?
Maybe Trump's advisors are sitting him down and going over the fundamentals with him.
>it's also a learning/growing experience
Unfortunately this shibboleth has become a major selling point for higher education since the influx of Baby Boomers in the 1960s.
It reminds me of what Greenspan called "Irrational Exuberance" in regard to the 90s stock market and tech bubble.
Other non-qualitative measures like "teaches critical thinking" are also trotted out as justifications for the traditional BA degree.
While Academically Adrift showed that humanities majors do gain more from college than your average Business major (something like 1/3 of all bachelor's degrees conferred), I have to wonder, "At what cost?"
From what I've read, there are a few major steps we could take toward improving the current system, in giving measurable results:
My grandparents—in their rural farm town—took Latin and Calculus. Graduating high school back then was likely of the same rigor as fluff degrees from many state universities today (speaking as someone with a History degree). Not more than 10% of the population graduated from college before 1965.
Aside from being a social signal, that the individual with the BA likely has a bit of drive, some intelligence, and obedience to authority, they're not even a good indices of basic writing or mathematical skills anymore. There is no shortage of humanities majors, like myself, with piss poor mathematical skills; the same goes for STEM graduates who write like high school students.
This also puts colleges' feet to the fire to actually teach and achieve results.
IQ and personality tests were widely used before Griggs v. Duke Power Co. and told employers more than your average college degree does today.
These steps would make the playing-field more equal, and eliminate the need to squander 4+ years during what is likely the most valuable decade of one's life. It also doesn't cost $40,000+.
Aside from all that, the most consequential action that would be taken is the elimination of government-backed student loans. Colleges have no reason to contain costs, as young people will go anyway, soaking up the marketing and lore the institutions rely upon—the dangling carrot being access to jobs that are "socially respectable" and act as signaling devices.
You've got a lot of options, so I'm going to throw out a few I recommend, no particular order:
Disclaimer: I have not gone to B-School yet, but my experience with analysts that come from technical backgrounds is that Excel is a fairly easy tool to pickup. I wouldn't stress too much about learning before you get in.
Hope it helps.
> Wenn es da nicht bestimmte politische und mediale Verflechtungen geben täte.
Lobbyismus fasst auch in Deutschland immer mehr Fuß, ich frage mich wann es die ersten Lobbyverbände gibt für die Bürger (wie in den USA - So etwas sollte eigentlich obsolet sein, in einer Demokratie).
Letztendlich ist es ein Problem unserer Demokratie, dass sich Politiker so stark von der Wirtschaft beeinflussen lassen. Der Blick in die USA zeigt nur wo die Reise hingeht, wenn wir nichts dagegen unternehmen. Denn dort herrschen schon seit Jahren fürchterliche Zustände, auch geschuldet durch Citizens United.
Ein gutes Buch, mit erschreckenden Beispielen, dazu ist Corporations Are Not People.
Power Pivot and Power BI: The Excel User's Guide to DAX, Power Query, Power BI and Power Pivot in Excel 2010-2016.
The Definitive Guide to Dax aka the Purple Book.
Analyzing Data with Power BI and Power Pivot for Excel aka the Orange Book.
And lastly, one I don't actually have as yet, but am itching to get:
Beginning DAX with Power BI: The SQL Pro's Guide to Better Business Intelligence
https://www.amazon.com/Measured-Lies-Bell-Curve-Examined/dp/0312172281
https://www.amazon.com/Intelligence-Genes-Success-Scientists-Statistics/dp/0387949860
https://www.amazon.com/Inequality-Design-Cracking-Bell-Curve/dp/0691028982
https://www.amazon.com/Bell-Curve-Debate-Russell-Jacoby/dp/0812925874
https://www.amazon.com/Bell-Curve-Wars-Intelligence-Republic/dp/0465006930
https://www.amazon.com/Manga-Guide-Regression-Analysis/dp/1593277288
Some are downright riveting...
Many are just pamphlets, cheat sheets, or quick introductions - most don't go beyond introductions or very specific features they're trying to push. Some are tied to new books being published, like this and this.
So, your mileage may vary - they're not really technical books in the typical sense though. I'm also not sure why they say 'millions' when it's very obviously 404 downloads (based on the link /u/tommis posted). It seems misleading at the very least.
Mathematician and former Wall Street quant Cathy O'Neill wrote what I bet will be the defining book concerning the huge and unique risks of unwittingly enshrining bias into the production and consumption of sociological (and commercial) data science. Weapons Of Math Destruction is awesome and I recommend it to anyone who takes media coverage of mathematical models seriously.
https://www.amazon.com/dp/B019B6VCLO/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1
McKeachie's Teaching Tips.
​
https://www.amazon.com/McKeachies-Teaching-Tips-Wilbert-McKeachie/dp/1133936792
​
Whenever I'm stuck for what to do in class, whenever I have a lot on my plate and need an activity that's student-led, whenever I'm frustrated about how a class is going, I open McKeachie's to a random page. There's almost always some good wisdom or a solution!
What consequences are you giving? Do they make sense? Would working on the major problem behavior of the worst offenders help? Sometimes it's one kid influencing others to be naughty.
I recommend Collaborative Problem Solving with the worst kids. Here are the forms.
Secondly, I recommend reading Teach Like a Champion.
Lastly, I recommend Teaching with Love and Logic.
Alright some advice I can give you is to avoid CCS (Community College Sickness); that is where you work while going to Community College. You might walk in to a job that pays you half way decent but they will expect you to work a lot of hours. I made the mistake of thinking I could take 5 classes and work 40+ hours a week. Professors don’t care if you are working or not they will still give you assignments. One example of this I had to deal with is my professor assigned us a book to read and gave us a week to read it. I have literally no time to read it. I remember waking up with my face in the book. Even still, it’ll suck up all your free time to do things outside of classes, visiting people, exploring, and it’ll kill your motivation when you get home. After all you just worked a double shift on Saturday you just want to relax for it bit.
Socializing is hard, most people at community college are just looking to go to class and get the hell out of there. You may make some friends in class but the problem is many live in towns outside of yours. You might have to drive 10, 20 or even 30 minutes away to hang out with them. And girls, forget about it. You may meet a couple but if you are at home (I know this was the case where I was at) they don’t want to go back to your place and hang with your mother and brother mere feet away. As much as you say you won’t want the dorm life you’ll regret the experience, I know I sure did. When friends would come home they would regale me with stories of the fun things they did from drinking, parties, events the school hosted and trips to do things outside of the campus.
The boredom is another thing. My town had nothing going on for young adults. It’s Friday night you have time off from work and school, but fuck man there is nothing to do anywhere close by. You might end out hanging out with from friends one weekend, and the next and the next. It’s fucking boring especially if the people you hang out with don’t like the same shit you do. Now about the classes, you are going to be dealing with some immature asshole. Unfortunately these people aren’t the college student type; they don’t give a shit about education. They are just here because it’s the only thing they have going for them. All the scumbags in high school you know, and I’m not talking about asshole jokes or preppy kids, I’m talking about the low of the low will end up there if they don’t have anything else going on for them.
The upside is if you show an interest in something a professor will notice and encourage you to pursue it. Not every professor will do this, but the good ones will. These people are your best friends and will help you try and move on. Also the 30+ year olds are the best people to get to know. They have more of a sense about what the world is they aren’t going to sugar coat anything for you. I’ve learned a lot of important lessons for these guys; they ranged from police officers who worked in some of the roughest areas in my state, chefs getting a business degree, elementary school bus drivers and people who are looking for a new career after their first didn’t pan out. These people are you best fucking friends; let me say that again BEST FUCKING FRIENDS. They are serious about their education and if you are serious about it also they will help you in the classes they are in.
The most important advice I can give to you is get your associates, while it’s not as big as a safe net as a bachelors it’s still better then college credits and a high school diploma. If you still don’t know what to do after you get your AS I would suggest moving to a young city, Austin comes to mind. The most important thing you can do even if you hate people is being around people your own age who are driven in what they want to do.
Also Rate your Professor is your friend, correction, your GOD!
Edited for spelling and grammar, ended up adding more.
I also suggest you read these two books. It helped me a fair amount.
http://www.amazon.com/DIY-Edupunks-Edupreneurs-Transformation-Education/dp/1603582347
http://www.amazon.com/Academically-Adrift-Limited-Learning-Campuses/dp/0226028569/ref=pd_sim_b_4
Read this before you buy anything! I had Mazzullo last semester for STAT400. We did not need a WebAssign code, and it was honestly never mentioned in class, so I have no idea what it's even good for if you have her. This is listed as recommended, not required, for all sections, so you most likely don't need it. Only buy WebAssign if your professor is grading homework for credit through it!
The textbook (listed as required for all sections) is a custom version that just has the first half of the book (which is all that's used in STAT400). One of the later classes requires the whole book. This is the full book, and you can either rent it on Amazon ($30 right now) or "borrow" a digital copy from LibGen depending on your preferences.
Let me know if you have any other questions about the class.
Here's their book on Amazon if you want to analyze the study further.
Hi, I've taught physics and developed curriculum (for better or worse) for the last ten years. I work in an independent school so I may not be able to transfer all of my experiences to you if you work in public school, but the following steps have helped me immensely.
https://www.amazon.com/Probability-Statistics-Engineering-Sciences-Devore/dp/0538733527
I work on the west side of Chicago in a extremely violent neighborhood. Students at my school have seen some pretty crazy things, and that trauma brings some really challenging behaviors. The specials teachers I've seen be successful have a few things in common.
Kids know exactly what is expected of them throughout the entire class. The teachers have students practice this and model this for their class, narrating their behavior for everyone.
(Also, a fair consequence to being disruptive is "You can learn the rules by playing the game or by watching. Either is okay with me.")
Found one on amazon for $66 here. Other than that, pirate/torrent/whatever. Google it. Good luck
Oh! I got this! So, according to Make It Stick!, what you want to do is break the 2 hours into 30 minute chunks, and learn at least 2 things, swapping back and forth...or "interleaving", as the book called it.
Obviously, if you want to become good at 4 things in three months, learning four specific things would be the way to go. And if you want to get better at only 2 things, then just doing those two things would obviously be the way to go. What to learn is entirely your choice. But interleaving the things you're learning is how to do it.
I work with econ/stat people who are great at running and interpreting models and thinking about causality issues, but don't know much about programming. They've specialized, I get it, but in the future teams would benefit from everyone knowing some basics. It'll also make stats people more productive and help prevent errors. Also also, econ, other sciences, and the policy world really should embrace open source, open science, open access, etc.
But anyway, here's how to do it.
Below are a bunch of random resources. If you're looking for free courses, Software Carpentry has a bunch on the topics listed below and more. The terminal and Bash, Python, R, Matlab, Git, SQL, GNU Make, continuous integration, and data visualization. Data Carpentry has lessons for some of these topics, geared more toward social scientists. Apparently they're developing a course for doing econ with Bash(?). If you're into macro or computational stuff and want to learn Python, can't do wrong with QuantEcon.
I'll echo what the other guy said. If you have a Mac, cool. If not, consider dual booting with linux. It has a reputation for being difficult to use, but Ubuntu, Mint, and ElementaryOS are all very simple and work just like what you're used to in Proprietary World. It's possible to do the following with Windows, but requires a more setup work.
Learn to use the terminal (this is the point of using Mac or Linux, they come with a terminal and unix tools). Here's a decent book on the basics. Learn to navigate around your filesystem, run programs from the terminal, and use a bit of Bash. You can probably skip the chapters on actually programming with Bash. Bash as a programming language is cool, but not super necessary, and kinda quirky. It wouldn't be a waste of time though, since you can do certain things in Bash very quickly and easily. And you'll be a master haxxer.
Check out Data Science at the Command Line for a decent overview of stats programming in a linux environment. Goes over basic Python and R, and other tools to make life simple. There's also The Plain Person's Guide to Plain Text Social Science, geared toward people who do science but may not do programming atm. Covers more useful tools.
Learn Python or R or both. If Python, here. If R, here. If you're into ML, here for Python and possibly here for R but the code may be dated. Still, that book is The intro book for ML.
Learn Git. You should be in the habit of tracking changes you make to your code and the data/results it produces, especially if your data is being shared with anyone. If you use R, here's a great intro to Git and RStudio's fantastic Git integration.
Learn SQL. This one's harder to pick up on your own, at home, since you need a database set up to query. Look at the software/data carpentry courses.
Learn Docker. It makes your analyses/projects more shareable and--gasp--more reproducible (though I've gotten shit in the past for this, so let's compromise and say it helps but doesn't GUARANTEE reproducibility). This one is more optional than the others.
Once you have the basics down, you can do what interests you and learn best practices. Perhaps you want to know about Efficient R Programming (and general best practices). Or best practices in Python and more comprehensive coverage. Or how to make reports and papers with RMarkdown (want to make a paper that looks like it's published in AER? there's a template for that in Rmd).
It currently costs $97.70, so yep, the book is cheaper.
Rushton, fonte del primo articolo e autore del paper, è la cosa piu lontana da reppresentante della "scienza" sull'argomento. Le lacune del suo libro su cui il paper è basato sono molte, si passa da metodologia e raccolta di dati seguite con i piedi alla poca dimestichezza con i concetti trattati es. l'applicazione della teoria r/K nel teorizzare che la lunghezza media del pene in una popolazione ne determini l'intelligenza media (anche qui la raccolta dei dati è pessima).
In questo mio post trovi studi sull'opinione degli scienziati sull'argomento https://www.reddit.com/r/badscience/comments/7o5hxx/a_response_to_the_alternative_hypothesis_video/
Se ti interessa davvero l'argomento e vuoi dedicargli del tempo ti consiglio questi articoli e libri:
Studio APA
How heritability misleads about race
Intelligence, Genes, and Success: Scientists Respond to The Bell Curve
What went wrong? Reflections on science by observation and The Bell Curve
Intelligence: New Findings and Theoretical Developments
una recente meta-analysis
The Bell Curve Revisited: Testing Controversial Hypotheses with Molecular Genetic Data
Race and IQ in the postgenomic age: The microcephaly case
1 book by far is Andy Kirk’s. Data Visualisation: A Handbook for Data Driven Design https://www.amazon.com/dp/1526468921/ref=cm_sw_r_cp_api_i_rjx3DbDVRPFDN
It’s very broad and accessible yet substantial. That’s the book I recommend to anyone who need to read just one book.
2 is RJ Andrews book Info We Trust: How to Inspire the World with Data https://www.amazon.com/dp/1119483891/ref=cm_sw_r_cp_api_i_gmx3Db0FDG9DC.
This is a wonderful book that I read as an ode to visualization as a medium. It’s more artistic than Andy’s book both in its topic and its execution.
3 book depends on your specific interest. Dashboards/tableau? https://www.amazon.com/big-book-dashboard/s?k=big+book+of+dashboard.
Data art? https://www.amazon.com/dear-data-book/s?k=dear+data+book
Data journalism/ storytelling? Data-Driven Storytelling (AK Peters Visualization Series) https://www.amazon.com/dp/B07CCZPKV3/ref=cm_sw_r_cp_api_i_Msx3DbF1GZMG8
Science of visualization? https://www.amazon.com/Information-Visualization-Perception-Interactive-Technologies/dp/0123814642
Visualization from an academic point of view? https://www.amazon.com/Visualization-Analysis-Design-AK-Peters/dp/1466508914
D3js? https://www.amazon.com/Interactive-Data-Visualization-Web-Introduction/dp/1449339735
McKeachie's Teaching Tips is a long-running classic in higher ed, too. It would eat up most of your budget, though.
Data Science from Scratch
Python Machine Learning
DSFS covers basics of Python. If you're comfortable with that and want to dive into implementing algorithm (using Tensorflow2, for example), then PML is a great book for that.
These are listed in the order I'd recommend reading them. Also, I've purposely recommended older editions since they're much cheaper and still as good as newer ones. If you want the latest edition of some book, you can search for that and get it.
The Humongous Book of Basic Math and Pre-Algebra Problems https://www.amazon.com/dp/1615640835/ref=cm_sw_r_cp_api_pHZdzbHARBT0A
Intermediate Algebra https://www.amazon.com/dp/0072934735/ref=cm_sw_r_cp_api_UIZdzbVD73KC9
College Algebra https://www.amazon.com/dp/0618643109/ref=cm_sw_r_cp_api_hKZdzb3TPRPH9
Trigonometry (2nd Edition) https://www.amazon.com/dp/032135690X/ref=cm_sw_r_cp_api_eLZdzbXGVGY6P
Reading this whole book from beginning to end will cover calculus 1, 2, and 3.
Calculus: Early Transcendental Functions https://www.amazon.com/dp/0073229733/ref=cm_sw_r_cp_api_PLZdzbW28XVBW
You can do LinAlg concurrently with calculus.
Linear Algebra: A Modern Introduction (Available 2011 Titles Enhanced Web Assign) https://www.amazon.com/dp/0538735457/ref=cm_sw_r_cp_api_dNZdzb7TPVBJJ
You can do this after calculus. Or you can also get a book that's specific to statistics (be sure to get the one requiring calc, as some are made for non-science/eng students and are pretty basic) and then another book specific to probability. This one combines the two.
Probability and Statistics for Engineering and the Sciences https://www.amazon.com/dp/1305251806/ref=cm_sw_r_cp_api_QXZdzb1J095Y1
Differential Equations with Boundary-Value Problems, 8th Edition https://www.amazon.com/dp/1111827060/ref=cm_sw_r_cp_api_sSZdzbDKD0TQ9
After doing all of the above, you'd have the equivalent most engineering majors have to take. You can go further by exploring partial diff EQs, real analysis (which is usually required by math majors for more advanced topics), and an intro to higher math which usually includes logic, set theory, and abstract algebra.
If you want to get into higher math topics you can use this fantastic book on the topic:
This book is also available for free online, but since you won't have internet here's the hard copy.
Book of Proof https://www.amazon.com/dp/0989472108/ref=cm_sw_r_cp_api_MUZdzbP64AWEW
From there you can go on to number theory, combinatorics, graph theory, numerical analysis, higher geometries, algorithms, more in depth in modern algebra, topology and so on. Good luck!
750 or above is 99% percentile - it will require months of studying almost daily. If you have the will and dedication for it, it is possible. It's not going to be easy, but if you check success stories on GMATclub or other forums, you will find people who have done it.
For verbal, I suggest:
https://www.amazon.com/PowerScore-GMAT-Critical-Reasoning-Bible-ebook/dp/B00A413J4O
https://www.amazon.com/Sentence-Correction-Manhattan-Strategy-Guides/dp/1941234070/ref=dp_ob_title_bk
For Quant:
Teaching with Love and Logic by Jim Fay and David Funk was recommended to me. It's about classroom management, which you will need if you're doing alternative certification. IMO, everybody new to teaching needs classroom management help. It's just something that is hard to learn until you're in the trenches.
This book is pretty good:
https://www.amazon.com.au/Data-Science-Scratch-Joel-Grus/dp/1492041130/ref=sr_1_2?keywords=joel+grus&qid=1557969275&s=gateway&sr=8-2
Denne er veldig bra:
http://www.math.pku.edu.cn/teachers/xirb/Courses/biostatistics/Biostatistics2016/GraphicalPerception_Jasa1984.pdf
Det finnes også en bok av Tamara Munzner som går inn på mye av dette, men med videre forskning, artikkelen er fra 1984
Boken:
https://www.amazon.com/Visualization-Analysis-Design-AK-Peters/dp/1466508914
Andrew Ng's Machine Learning Online Course
Deep Learning with Python Book by Francois Chollet
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Bonus Gift:
Manga Guide to Regression Analysis
In the teaching program (I'm taking a course to become a certified university teacher), they recommend McKeachie's teaching tips (amazon link) and Dee Fink's guide to course design (pdf link). Both are useful, though you'll often find yourself thinking these guys keep stating the obvious.
There's also Potts' article: teaching pragmatics. Edit: didn't see you already mentioned Teaching linguistics, the edited collection the paper is published in.
Drug War Crimes: The Consequences of Prohibition by Jeffrey Miron
This is a good resource: https://www.amazon.com/Microsoft-Excel-Analysis-Business-Modeling/dp/1509304215/ref=sr_1_1?ie=UTF8&qid=1536926123&sr=8-1&keywords=excel+analysis
Honestly, ignore the "for engineering" part of "Statistics for Engineering." They're largely the same content.
How much calculus have you taken? Does the class use calculus?
First, the cartoon guide to statistics is surprisingly helpful for some people.
For a more traditional textbook, you might try Devore's main intro book.
Almost every student finds statistics confusing and it's either difficult to teach, or just difficult to learn. It's also a fractal discipline, since you can keep going deeper and deeper, but it's generally just going over the same few concepts with additional depth. If you end up in a class that's not well suited to your mathematical background it's especially frustrating.
Good luck.
Here is my copy and paste list:
Books
TIPERS
TIPERs are a fantastic resource for including conceptual thinking assignments. Answer keys are generally available if you talk to your school's Pearson Rep. IMO, the E/M book is the weakest, in part because it ignores that circuits are a thing. I would start with the first as it is a general overview, and go from there.
General Physics Education
Websites
Youtube
Let me know if you have questions about any of these, or about particular types of physics courses.
Can confirm that a few of these tips are indeed helpful. I have read about it on this book and I can recommend it to anyone that wants to study better.
https://www.amazon.com/Make-Stick-Peter-C-Brown-ebook/dp/B00JQ3FN7M
Weapons of Math Destruction. Read it.
You could look into the GMAT Prep book for writing. I bought the GMAT Prep books and I think the Foundations of Verbal would help you. Other ones that would be good for you are Sentence Correction and Integrated Reasoning and Essay. I've linked them below.
Foundations of Verbal
Sentence Correction
Integrated Reasoning and Essay
You can also search for free prep on Google. There are TONS of websites with practice problems and essay questions. All I had to do was sign up for free and I had access to loads of stuff. And there are a lot of forums with people in your situation or people that were in your situation that give insights to succeed.
Ross for probability. He wrote the undergrad book on probability. It is on it's 9th edition, so you can probably find an older edition for next to nothing.
Statistics for engineers and scientists by Devore would probably be a good book for learning stats as a physicist. I've taught out of it a few times and I like it as book. Again, you can find an international edition of this book for next to nothing.
Casella and Berger is a first year grad text/ upper level undergrad text. You need some mathematical maturity to do use it and it probably goes a lot deeper than you would want. I would not suggest it.
Fantastic book on the subject
http://www.amazon.com/Drug-War-Crimes-Consequences-Prohibition/dp/0945999909
Eventually take a look at this book to get a deeper view of the art and science of data visualization:
https://www.amazon.com/Visualization-Analysis-Design-AK-Peters/dp/1466508914?ie=UTF8&*Version*=1&*entries*=0
This is the bible of data visualization.
You might be interested in Randy Knight's book Five Easy Lessons. He included with his textbook (which I dislike) but he goes through every subject that an introductory physics textbook goes over listing common misconceptions and how to combat them and not reinforce them.
If you want to learn a lot about PowerPivot and (don't mind reading) I'd recommend anything written by Alberto Ferrari and Marco Russo. They write on PowerPivot / SSAS / Power BI for the Microsoft Press. One of their books was recommended by Michael Alexander who's a Microsoft MVP (I think for Access, but he also knows Excel very, very well.) Take a look at a few of the books below:
https://www.amazon.com/Definitive-Guide-DAX-intelligence-Microsoft/dp/073569835X/ref=asap_bc?ie=UTF8
https://www.amazon.com/Microsoft-Building-Models-PowerPivot-Business/dp/0735676348/ref=asap_bc?ie=UTF8
I only read a bit of their 2013 book, but it's very comprehensive and of high quality.
I also want to discuss a few other things mentioned here in the comments: PowerPivotPro by Rob Collie and SQLBi. Rob Collie is a former Microsoft engineer on Excel, is an expert on it, and still talks to many engineers on the Excel team. And SQL Bi is run by Marco Russo, who I mentioned above.
Sounds like you're a grad student then? It's really difficult to deal with not knowing the answer, but it's something we all have to deal with. I'm glad you're accepting of that. Can I give you some pointers from my grad school days that really helped me out?
It sounds like you're on the path to becoming a top-notch teacher. Keep that humility and always keep learning. Good luck!
Lynn and Vanhanen study has not been successfully replicated so far, their methodology has been criticized and they have also been accused of ignoring high IQ scores from Africa. There's a vast literature, u/humanprideworldwide has already mentioned [this good short reading] (https://www.reddit.com/r/badscience/comments/7o5hxx/a_response_to_the_alternative_hypothesis_video/) on this topic
More in depth readings :
I think a good starting point would be to read this APA paper on the state of intelligence research. It's fairly recent and it should answer most of your questions.
How heritability misleads about race by Ned Block, a more theoretical response to Murray and Hernsein's The Bell Curve.
Intelligence, Genes, and Success: Scientists Respond to The Bell Curve
What went wrong? Reflections on science by observation and The Bell Curve by Clark Glymour
Intelligence: New Findings and Theoretical Developments by Nisbett et al.
A study by Turkheimer et al. about the dependence of IQ heritability on socioeconomic status (ses). Another study by Kirkpatrick et al. on replication efforts.
A recent meta-analysis by Tucker-Drob & Bates for further edification.
The Bell Curve Revisited: Testing Controversial Hypotheses with Molecular Genetic Data by Dalton Conley and Benjamin Domingue.
Race and IQ in the postgenomic age: The microcephaly case by Sarah Richardson
Aaron Panofsky's chapter, From Behavior to Postgenomics, in Postgenomics: Perspectives on Biology After the Genome provides a succinct overview of recent developments on the "nature vs. nurture" debate over the genetic foundations of behavior.
First, thank you for the taking the time to respond to my question - I really appreciate it. Second, congratulations on receiving the MCSA: BI Reporting badge!
The reason I am struggling to prepare for this exam is because there is no real comprehensive prep course like there is for the CPA exam. There's no "Becker for MCSA: BI Reporting". Can you share how you went about preparing for these exams? I feel like I have learned a lot from edX but not enough to pass the exam and I cannot find any additional practice questions/tests to study - anywhere. Do you have any insight on this?
Yes, the edX Excel course was very good and has significantly improved my Excel skills. However I am still unsure what to expect as far as test questions are concerned. Are they similar to the ones on the edX course?
As far as DAX and M, I assume DAX will be more heavily tested on the Power BI exam then the Excel one. Would you say that's correct? At the moment, my DAX skills are limited because I haven't been able to sit down and really run through it yet - but I will do so. I am waiting for my DAX book to come in the mail. M doesn't seem that difficult but nonetheless I have to run through it.
Again, thank you for your insight - I really appreciate it!
I'm definitely really interested in that documentary, thanks for the recommendation. The book Weapons of Math Destruction paints a really great picture of how a data focused approach alone can reinforce racism (housing zones and eligibility for loans), create ineffective methods of "culling" poor performer teachers (arbitrary, opaque method for testing teachers resulting in firing) and maintain income inequality. So I'm in complete agreement with what you're saying in the way this approach can be abused.
The biggest reason I think we should emphasize this focus is because curation of information is going to be essential as time goes on and politics, business, daily life etc gets more complex. We're already exposed to so much information, think about now vs. 50 years ago, and cognitively it's very stressful. We don't know what to prioritize. A data driven approach (algorithms) to deciding what information we're exposed to (look at Facebook newsfeed), how our public policy is enacted, what careers we choose- are all imminent. So basically the way I see it is we can choose to understand those mechanisms or be victims the ones who control them. Whether the world is going to magically follow my unqualified advice is another matter...
I just see the dialogue that exists on mainstream media, and I'm just shocked at how simply these approaches could be resolved or at least greatly clarified by a very quick, simple number check. A lot of the data exists in the public database, even with uncertain values such as number of illegal immigrants we have a pretty reasonable idea... seems just infinitely better to say, "Okay, we can support approximately 15-20 million while sustaining native jobs and maintaining agricultural industries, looking at resources etc," then debate within that number range.
I understand that capitalism is a bit cold in the way it refers to humans... hell, economists like Nesbitt calculated the value of a human life... a bit messed up if you look at it philosophically. But I don't see better alternatives with the way our world is structured in order to maintain a certain quality of life and stability.
According to whom? An friend of mine wrote this book
Have you read it?
Unfortunately, according to evidence in "Academically Adrift", colleges are failing in teaching critical thinking skills, especially for those in Education, Social Work, and General Business majors. https://www.amazon.com/Academically-Adrift-Limited-Learning-Campuses/dp/0226028569
I'm going to give you some advice that I hope you take to heart. Your study process, meaning what you do with the material, is far more important than having "the best resource".
If all you are doing is using a resource, you will not learn the language very well at all. You have to cultivate a better process to work with the resources you have.
This sort of learning is hard because you have to face the fact of your learning and not how you wish it to be. Too many people use their resources to the point where they can almost recite it from heart but then when faced with a native speaker, they can't produce. It's because they mistake familiarity with the text for mastery of the concepts. Take a look at the progress that u/shiner_man made in just 90 days. He made his own flashcards, worked through his material repeatedly and in different ways. That's how you leanr a language. Of course you don't want resources that are crap, but at a certain point the way you work is far more important than having "the best" course.
Read these books:
Fluent Forever, Gabriel Wyner
Make it Stick, Peter C. Brown
Nice, thanks for the feedback! Does this look like the one that you used?
https://www.amazon.com/Sentence-Correction-Manhattan-Strategy-Guides/dp/1941234070/ref=sr_1_1?ie=UTF8&qid=1505748545&sr=8-1&keywords=manhattan+sc+gmat+book
I have a different suggestion - try learning Power BI instead. It is the "next step" from Excel and has a lot of deep analytic and data transformation / automation functionality via Power Query and DAX. Tableau is an excellent (and more mainstream) option as well. Also, you may as well start slowly working on Python.
I don't know how much you rely on primary texts for handling philosophy but you will likely find that many philosophical works are a bit much for high schoolers. I really like the style and level of the philosophy videos from this channel for introducing people to the major players in philosophy. I would imagine that this class is a good candidate for something akin to 'Problem Based Learning' but I am not a philosophy specialist so I might be off base there. In my intro philosophy and ethics classes we did a lot of group discussion that worked well because the professor knew how to be an effective moderator of topics that can cause emotions to run high, hell if I know how he did it though.
You will probably have some more issues with behavior management that are not normally present at the college level, even though these students are self selecting this class you should still have a consistent strategy to handle them (this works at the university level as well, so I think you should do this if you plan on teaching even at higher levels). I suggest finding a teaching strategy book and giving it a read through. You can find some that are very accessible, like Wong and Wong or Fay and funk. There are plenty of others, just find one that is decently reviewed and give it a quick read through. You don't have to agree with everything in it or put it all in place but find some things you like and think you can do and be consistent with it and it should work out.
If you want to be valuable to companies post graduation you should learn more about programming (design templates, how to write tests, how to go from a paper to code). I recommend this book as a good starting place. Once you're comfortable with how the different methods work, pick up this book.
This would be a good start.
Hi, There are so many resources out there I don't know where to start! I would work through some kind of beginner python book (recommendation below). Then maybe try Andrew Ng's Machine Learning Coursera course to get a taste of Machine Learning. Once you have completed both of those I would reassess what you would like to focus on. I will include some other books I would recommend below.
Beginner Python - https://www.amazon.co.uk/Python-Crash-Course-Hands-Project-Based/dp/1593276036/ref=sr_1_3?keywords=python+books&qid=1565035502&s=books&sr=1-3
Machine Learning Coursera - https://www.coursera.org/learn/machine-learning
Python Machine Learning - https://www.amazon.co.uk/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1491962291/ref=sr_1_7?crid=2QF98N9Q9GCJ9&keywords=hands+on+data+science&qid=1565035593&s=books&sprefix=hands+on+data+sc%2Cstripbooks%2C183&sr=1-7
https://www.amazon.co.uk/Data-Science-Scratch-Joel-Grus/dp/1492041130/ref=sr_1_1?crid=PJEJNNUBNQ8N&keywords=data+science+from+scratch&qid=1565035617&s=books&sprefix=data+science+from+s%2Cstripbooks%2C140&sr=1-1
Statistics (intro) - https://www.amazon.co.uk/Naked-Statistics-Stripping-Dread-Data/dp/039334777X/ref=sr_1_1?keywords=naked+statistics&qid=1565035650&s=books&sr=1-1
More stats (I haven't read this but gets recommended) - https://www.amazon.co.uk/Think-Stats-Allen-B-Downey/dp/1491907339/ref=sr_1_1?keywords=think+stats&qid=1565035674&s=books&sr=1-1
I just bought the book that the article was talking about. Send a message with your wallets people.
http://www.amazon.com/gp/product/032119991X/ref=oh_aui_detailpage_o00_s00?ie=UTF8&psc=1
McKeachie's Teaching Tips
Well that's what I'm asking for, are there any websites besides the publisher that sell them? I know amazon does, but take for instance the Mymathlab thing.
Nearly half of the people who bought it say that the code was invalid. I'm fine with just getting replacements through amazon's customer service, but it would take far too long and I wouldn't be able to start in my math class.
Are the topics actually the same? I watched the first 2 videos and we didn't really discuessed those in my class (I'm taking Crunk).
I'm struggling with the textbook that was assiged to us and I'm looking for another resource that I could use.
This is the book we have:
Probability and Statistics for Engineering and the Sciences https://www.amazon.com/dp/1305251806/ref=cm_sw_r_cp_apa_i_zwgxCb29E996J
Definitely interested me with what you're saying. I'm unemployed but had some very basic analysis experience with Excel in my last role.
A few questions. Hope you don't mind answering. Didn't PM you in case others are interested in this.
I politely disagree! Check out Teaching with Love and Logic. OP, you too.
There is a great book by Wayne Winston which we pass around to all the new hires. It is excellent https://www.amazon.com/Microsoft-Excel-Analysis-Business-Modeling/dp/1509304215
Practice, practice, practice. The more DAX you wrote the more you will know...and the more you will know you don't know ;).
By the way, the book you need to read is The Definitive Guide to DAX, if you learn from this book you will know "everything". Another good source is sqlbi.com, you can find useful articles about the language.
https://www.amazon.com/Intelligence-Genes-Success-Scientists-Statistics/dp/0387949860
This book covers refutations of much of the maths, from actual statisticians.
>I'm not sure why people get up in arms over intelligence being one of the things. I mean, some people are genetically predisposed to not being very tall. Why is it so inconceivable that intelligence is connected to genes?
They're not getting up in arms about the idea that intellect is connected to genetics. It clearly is. They're getting up in arms over the poorly proven claim that there are genetic differences between the groups, and that black people are a homogenous group with a low IQ.
And as a result of that research he argued for starving black babies to death. If IQ is a result of disease or nutrition or education then that can be changed, but if it's a result of genetics, why not kill the inferior race, as he argues for with an end to social support?
>The fact remains, affirmative action is up for debate because no discussion should be off limits.
If you believe, as he does, that less black people should go to college because they're less intelligent, that is a very racially charged belief, true or false.
You are allowed to have that belief, but people are allowed to call you racist. The topic is not off limits, just the topic of black people being dumb so they shouldn't go to college tends to get you called racist.
Thanks for the delta.
You're sounding like some uneducated fuck that thinks everyone can just pull themselves up with their own bootstraps and those who are poor are just too lazy to do so. I bet you think we should privatize everything, because then if no one got anything for free they wouldn't feel entitled to it and that would encourage them to work for a brighter tomorrow...
Your idealized view of capitalistic optimism may work for you in what ever delusion you have in your head, where Reagan is a God and opportunity just trickles down from above... But in reality, the system is fucking broken. It has fucking failed. These kids never had a fair chance to begin with, the playing field was never level, they were doomed to fail from the start.
An unstable household, they probably never received the same quality nutrition you did growing up, the education system was a fucking joke, our country treats drug addiction as a criminal problem (not a mental health problem) and the criminal justice system is just completely and utterly fucked...
So yeah, these "violent criminals" may have made some poor choices, but they had pretty limited options from the get go. Can you just maybe entertain the thought, for just half a fucking second, that the system was fucked and not to their advantage at all. They were set up for failure from they even started.
You should really broaden your horizons a little bit. I'm not suggesting anything drastic, like taking a liberal studies class at your local college, but maybe read a book on the matter.
I would really recommend Jeffery A Miron's Drug War Crimes Seriously, its a really interesting book- it deals with the consequences of drug prohibition and the socio-economic ripples that it leaves on generations of the population.
Here you go.
Google is your friend.
https://www.amazon.com/Intelligence-Genes-Success-Scientists-Statistics/dp/0387949860
You've really said nothing of value here.
Both parties, especially Democrats—are responsible for declining state support, which is the largest factor in skyrocketing rising tuition. Additionally, states have had their own budget crises, especially after the 2008 market drop and housing bust—and the parties have only responded by exacerbating the problem in supporting unchecked government-backed student loans.
State governments are weighed down by Medicare funding (even more, thanks to the ACA), the increasing expenditures "needed" for declining K-12 schools year after year, and mounting pension crises at the county- and state-level.
Thus, states have no money to fund the largest demographic bubble since the Baby Boomers in Millennials, and the federal government has bridged the funding gap with student loans.
Students graduate into an economy with little value for their degrees, especially when many of them learn little, according to researchers in Academically Adrift.
I certainly think I would have better served by trade school than my 4-year humanities degree.
All I did was line the pockets of liberal college professors and a wealthy university, for knowledge I could have obtained with less propaganda from the local library, as it's clearly had little value to employers.
It took me three years to pay back student loans—money which would have been better off burned in a fireplace my senior year of high school.
The 4-year college degree is so anachronistic that it's almost comical. Until intelligence testing for employment, certificates, and exit-exams become a thing—where knowledge is verified and means something—we'll see college continue as a proxy IQ test and indoctrination center for the political left.
>Free Trade has lifted millions out of severe poverty all over the world.
I too love misattributing a trend to the wrong predictor variables.
May I suggest some remedial reading material?