Eight months ago, Trey Causey wrote a post about modeling expected points in football, with an emphasis on uncertainty. With my twisted economist's mind, I mentioned that it seemed like dynamic programming could be used in this situation, and indeed it would feature in a future post of Trey ...

## Practical Pandas--Part 1

This is the first post in a series where I'll show how I use pandas on real-world datasets.

For this post, we'll look at data I collected with Cyclemeter on my daily bike ride to and from school last year. I had to manually start and stop the ...

## Tidy Data in Action

Hadley Whickham wrote a famous paper (for a certain definition of famous) about the importance of tidy data when doing data analysis. I want to talk a bit about that, using an example from a StackOverflow post, with a solution using pandas. The principles of tidy data aren't language ...

## Tacking the CPS (part 4)

As a reminder, the CPS interviews households 8 times over the course of 16 months. They're interviewed for 4 months, take 8 months off, and are interviewed four more times. So if your first interview was in month \(m\), you're also interviewed in months

$$m + 1, m + 2, m + 3, m + 12, m + 13, m + 14, m + 15$$ ...## Tackling the CPS (Part 3)

As a reminder, we have a dictionary that looks like

id length start end 0 HRHHID 15 1 15 1 HRMONTH 2 16 17 2 HRYEAR4 4 18 21 3 HURESPLI 2 22 23 4 HUFINAL 3 24 26 ... ... ... ...

giving the columns of the raw CPS data files. This post ...

## Quiz 10 Review

# Section A01

This quiz focused on exponential smoothing. Make sure that you know about moving averages and autocorrelation too.

### #1

You needed to find the biggest decline in the time series. You should never have to guess in stats, and I'm worried that some of you just looked at ...

## Quiz 9 Review

Don't forget your section number!

# Section A01

## #2

Remember that for the modified best conservative model, we still care about the significance of all the predictors other than the ones that must be included.

## #3

Quite a few people are still giving point estimates (just \(\hat{y}\)) when the ...

## Quiz 8 Review

## #1

The test statistic for \(H_0: \beta_1 = \beta_2 = 0\) is the \(F\) statistic. It's what we'll use for when we're testing multiple parameters at once.

Several people had \(\beta_1 = 0\)

**or**\(\beta_2 = 0\). This is wrong; it should be**and**not**or**. This is actually an important ...## Quiz 6 Review

Part

**b**asked for a CI for the slope \(\beta_1\). For this one you use the formula \(\hat{\beta_1} \pm t^{\ast}_{n-p-1} SE(\hat{\beta_1})\). \(n\) is the sample size and \(p\) is the number of predictors (1 in this case).You get the \(\hat{\beta_1}\) and \(SE(\hat{\beta_1})\) ...

## QUiz 5 Review

## Problem 1

Make sure to read the questions carefully, in particular

**the underlined or bold parts**. For this question we wanted the**statistical concept**that explains why interpreting a prediction for a car with 0 City MPG is mislaeding. I agree with many of you that a negative Highway MPG ...