1. ## Dynamic Programming

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 ...

2. ## 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 ...

3. ## 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 ...

4. ## 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

$$m + 1, m + 2, m + 3, m + 12, m + 13, m + 14, m + 15$$ ...
5. ## 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 ...

# 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 ...

# 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 ...

## #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 ...

9. ## 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 $$SE(\hat{\beta_1})$$ ...

## 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 ...

« Page 2 / 3 »