Questions tagged [teaching]

For questions about the teaching of probability and statistics, at any level.

Filter by
Sorted by
Tagged with
1
vote
0answers
26 views

When do we REALLY need to distinguish interval from ratio measurement levels?

This question is specifically aimed toward the practice of statistics and data science and toward statistics educators (particularly introductory level statistics). In brief, ¿when do we really need ...
1
vote
0answers
32 views

Suggestions for an online course in graduate Statistical Inference?

I am looking for an online course (MIT OpenCourseWare style) in graduate-advanced statistical inference. I am now reading Casella and Berger (2008) "Statistical Inference", and I was ...
7
votes
5answers
1k views

How to learn statistics for medical research?

I'm a last year medical student, as we say "Intern doctor". In the future I want to do research on the issue that I want to get in. Therefore I want to learn mathematics, statistics, R ...
1
vote
0answers
13 views

Normally distributed: examples like LTCM

I am looking for examples of organizations suffering dire consequences (losing money) because they have assumed that something was normally distributed hence underestimating the risk of tail events. ...
3
votes
1answer
113 views

Non-self-referential interpretation of confidence intervals?

Interpreting what a (say) 95% confidence interval actually means is obviously tricky, especially when you are trying to teach it to students just beginning to learn stats. One of the biggest ...
4
votes
1answer
68 views

Resources or textbooks about teaching statistics (pedagogy)

I want to become a better teacher and, therefore, I am looking for resources or textbooks about how to teach statistics and quantitative methods to students or learners (focusing on hints on how to ...
23
votes
7answers
2k views

Explain in layperson's terms why predictive models aren't causally interpretable

Imagine that you are asked to infer some causal effect -- a change in an outcome $y$ in response to some variable $x$. But, the person asking for this directs you to use a predictive model to do so. ...
1
vote
1answer
70 views

Central Limit Theorem - intuitive explanation without deep math [duplicate]

The Central Limit Theorem says that the distribution of the sample mean is approximately normal. Is there any intuitive explanation for why this should be so? I know it can be proven with deep math, ...
1
vote
2answers
119 views

In Bayes Theorem why do we say :given that" when "out of" is more understandable. (Why is Conditional on referred to as "Given") [closed]

I understood the answer to my problem here when I substituted the "given that" symbol with the phrase "out of" I got this idea from 3Blue1Brown where Grant points out that people ...
3
votes
4answers
141 views

What are some references to teach statistics to business students?

I am going to teach a Statistics course next year and I should cover the basics of probabilities and statistics to undergrad students in business. They don't have any background in probability, so, at ...
3
votes
2answers
221 views

Why is the formula for the density of a transformed random variable expressed in terms of the derivative of the inverse?

In this very nice answer, the intuitive explanation of the formula for the density of a transformed random variable, $Y = g(X)$, leads naturally to an expression like $$f_Y(y) = \frac{f_X(g^{-1}(y))}{...
0
votes
0answers
27 views

Online stats teaching question

In the spirit of some exercises of Gelman's book on teaching statistics, I want to incorporate some more interactive elements to the zoom classes I teach. One exercise I want to implement is the ...
18
votes
1answer
448 views

Why do we use term “population” instead of “Data-generating process”?

I have always been confused about the use of the term “population” in statistics. In my first statistics course I was taught that we need a sample, because surveying the whole population is too costly....
2
votes
2answers
121 views

What concept comes before VAE and after GMM?

Suppose I am designing a course on generative models and I have just finished discussing GMM. My goal is to teach VAE. However, VAE's technicality is very high. Does there exist some model in between ...
3
votes
0answers
42 views

LCA - how to include predictors (conceptual difference between one-step and bias-corrected three-step approach?)

I am trying to teach LCA as part of a modelling course, but I haven't quite made sense of how to deal with testing whether certain (demographic variables) predict class membership. Question: (Why) ...
1
vote
0answers
10 views

Why does the Standard deviation formula when using coded data not account for the addition or subtraction of coded part

When we code data from x to x-b the standard deviation formula is: Sd(x)=sd(x-b)= (sum of(x-b)^2)/n - (sum of (x-b)/n)^2 Why do they not use (sum of (x-b)/n +b )^2 for the second part since this is ...
0
votes
0answers
26 views

Giving a job lecture on "minimax statistical estimation". What kind of questions to expect?

As part of a job application process, I am giving a short "mock lecture" for students on minimax estimation in statistics. I will introduce the basic concept and give an example. I am able ...
2
votes
0answers
30 views

Textbook default estimator of Bernoulli variance

Why do "most" (basically all) statistics text books use $\hat{\sigma}^2=\hat{p} (1-\hat{p})$ as an estimator for the variance of a Bernoulli process which we know is biased. Should the first ...
2
votes
2answers
48 views

Is this problem calculable only due to the parameter choices?

I am looking at a problem form Hogg, Tannis & Zimmerman (Ed. 10), and I am curious if the given problem is calculable (for an upper-level undergrad math/stats course) because of the choice of the ...
3
votes
1answer
318 views

Trick to remember when to reject null (p-values vs alpha)

I teach introductory statistics to undergraduates and they are often confused with hypothesis testing. In particular, while the rule is we reject the null hypothesis at significance level $\alpha$ ...
3
votes
0answers
117 views

Why don't textbooks on statistics start with an introduction to probability?

I recently read through Introduction to Probability, Statistics, and Random Processes by Hossein Pishro-Nik (free online version available here), and what I liked most about it is that it starts off ...
1
vote
0answers
56 views

Is there any university program that offers an intro statistical methods class that is bayesian -instead- of a frequentist one? [closed]

Is there any university program that offers an introductory statistical methods class that is bayesian -instead- of a frequentist one? Surely every intro to stats class in every program in the world, ...
1
vote
2answers
89 views

Does anyone in practice actually develop supervised model from scratch outside of classroom setting?

I have a question in regards to why bother with developing a model from scratch and perform hyperparameter tuning when you can just use transfer learning for supervised learning. The way that a ...
63
votes
32answers
3k views

What are the worst (commonly adopted) ideas/principles in statistics?

In my statistical teaching, I encounter some stubborn ideas/principles relating to statistics that have become popularised, yet seem to me to be misleading, or in some cases utterly without merit. I ...
3
votes
5answers
72 views

Pedagogical order of study for named distributions

I've seen myriads of named probability densities or distributions in multiple books and courses, usually both Binomial and Bernoulli are among the first discrete ones, while for continuous they use ...
4
votes
0answers
55 views

Reference for flawed randomized controlled trial

For a seminar, I am preparing an overview of advantages and shortcomings of randomized control trials (RCT; one shortcoming is, for example, often a limited external validity). To illustrate ...
0
votes
1answer
51 views

Web apps for visualization of probability distributions

I am looking for a tool to demonstrate how the shapes of some basic probability distributions (binomial, hypergeometric, Poisson, exponential and normal) change as a function of their parameters. I ...
2
votes
4answers
197 views

Intuition of terms P(θ) and P(y) in Bayes' Theorem [duplicate]

I am struggling with the intuition behind terms in the Bayes' Theorem. In the simple example of a deck of cards we have: $$ P(King | Red) = \frac{P(Red | King)P(King)}{P(Red)} $$ The terms in this ...
8
votes
2answers
132 views

Spurious relationships: flavours, terminology

The following types of relationships come to my mind when I think of the term "spurious" (as in "spurious regression" or "spurious correlation"): A statistical ...
9
votes
2answers
329 views

Quick test of quality of an econometrics textbook

When encountering an econometrics textbook for the first time, you might wish to assess its quality. What is the first thing you check? Is there a certain topic or a definition you examine, knowing ...
78
votes
12answers
8k views

Famous statistical wins and horror stories for teaching purposes

I am designing a one year program in data analysis with a local community college. The program aims to prepare students to handle basic tasks in data analysis, visualization and summarization, ...
3
votes
0answers
42 views

(Teaching) references for computational complexity

Background: I am going to teach computational complexity (time complexity) within an introductory course in machine learning. I would like to gently introduce the notion of computational complexity ...
1
vote
0answers
23 views

Ways to make parametric statistics work with real time (often non-normal) data

BACKGROUND: I have been tasked with teaching basic data analysis methods with R to a group of people in a business setting. While my stance is that I am most difinitely not at the level where I ...
0
votes
0answers
49 views

Poisson process as a spatial process

Let's consider a Poisson process on the line with rate parameter $\lambda$. There are two ways to think about this: In any interval $[a,b)$ the expected number of events is distributed as a Poisson ...
4
votes
0answers
45 views

Reproducing a didactic example of Lindley (1993)

Lindley (1993) discusses the following mixed discrete and continuous prior for the tea tasting lady experiment, where $\pi$ is probability of a correct classification: $p(\pi=0.5) = 0.8$ (discrete ...
2
votes
1answer
604 views

chi squared goodness of fit test to check for normality

I have the following data: I would like to use the chi-squared goodness of fit test to test whether it comes from a normal distribution. How shall I go about it? In particular, I would like to know ...
8
votes
3answers
588 views

Teaching students about non-significant results and large effect size

This year I am going to teach statistics to sophomore year students of psychology. We'll be training such methods as one-way ANOVA. The example will be the time-reaction of a cognitive task among ...
2
votes
1answer
105 views

What does one expect from a great course of time series? [closed]

I usually teach finance (asset pricing and equilibrium models), quantitative economics (linear algebra and optimization), econometrics, computer science introduction to programming and machine ...
1
vote
1answer
137 views

“t-tests are too fundamental for academia” [closed]

I just heard a PhD student claim: The $t$-test is really fundamental and nobody in academy is gonna do it. He added that these tests serve more as a beginning exercise in order to get an idea of ...
0
votes
1answer
537 views

How do you calculate an exact two-tailed P-value using binomial distribution? [closed]

First, I will preface this question with my ulterior motive: I would like more evidence that the use of 19th and 20th century approximations play little to no pedagogic advantage in modern intro stats ...
2
votes
0answers
44 views

A book-chapter long nontechnical introduction / overview of neural networks

I will be teaching an introductory course in machine learning for students in management who have minimal quantitative skills. I am looking for a brief and gentle introduction to neural networks that ...
2
votes
1answer
1k views

Explain Root Mean Square Error to non-technical audience

My company is in the process of switching equipment from one vendor to another. We measured several metrics from the existing and new equipment and compared the time series. The ideal is to have no ...
1
vote
0answers
83 views

How do you explain 'explained variance'?

What is the best definition of 'explained variance' from a teaching perspective? I quite like this one: "Explained variance (also called explained variation) is used to measure the discrepancy ...
2
votes
1answer
51 views

Accounting Student taking Master in Stat, need your help regarding taking subjects

I had a Bachelor in Accounting and now I'm doing a Masters in Statistics. This is my first semester and I have to Choose at least 3 out of 6 offered subjects for this semester. These subjects Are: ...
12
votes
2answers
671 views

Are there any “esoteric” statistic tests with very low power?

Background In computer science, mathematics, and sometimes in other fields, “esoteric” examples cannot only be entertaining, but helpful to illustrate certain concepts, for example: Bogosort and ...
2
votes
2answers
152 views

How can we best explain causality for the uninitiated?

How can we best explain causality in layman's terms? There seem to be two main types of causality. One is probabilistic causation, the other is called determinism in philosophic circles or just ...
4
votes
3answers
116 views

Teaching a new, large topic: present in class or assign as homework first?

In spring 2019, I will be teaching a master's level course in applied statistics for students in economics and management. The main topics are linear regression, explanatory and confirmatory factor ...
2
votes
0answers
38 views

Master's-level Quantitative Methods / Statistics textbook for Management, Marketing, Economics students

What are some good textbooks for a master's (or upper undergraduate) level course in Quantitative methods / Statistics for students in Management, Marketing or Economics?
7
votes
1answer
624 views

Why start with measures of central tendency?

In teaching descriptive statistics, measures of central tendency come up early on, e.g. before measures of spread. For me it is natural enough to learn about central tendency, or location, of the data ...
1
vote
1answer
25 views

Parameter errors in linear least squares

I would like to help my (Chemistry) students understand the math behind linear regression.(1) The generally accepted approach for my discipline is to omit any use of calculus and introduce matrix ...