Busn 5000 Cornwell UGA Midterm

The term data is (singlular/plural) _____

Plural

A data set is made up of _____ that contain information on a specific entity.

Records

Each record is made of _____ that contain measurements of known types.

Fields

A data table is made up of rows containing _____ and columns containing _____.

Observations,

Variables

We say that data are tidy if each variable corresponds to a _____, each row an _____, and each cell a _____.

Column, Observation, Single value

A quick-serve restaurant chain records sales, staffing and customer traffic every day for each store. You recognize this as a _____ data set where the unit of observation is the store-day.

Panel

We distinguish 4 stages of data analysis and refer to them compactly as _____ (in all caps).

ATAC

Name the stages.

Acquisition, Transformation, Analysis, Communication

The second stage involves, among other things, making sure the data are _____ (as the Posit folks would say).

Tidy

In the third stage, the workhorse will be the _____.

CEF

A variable will not have _____ if it does not measure what it is supposed to.

Validity

How to handle missing data depends on whether they are missing _____.

Endogenously

A national company has developed a new product and is offering it for sale at a discount to introduce it to the market. Randomly surveying customer who purchased the product in the initial discount period (would/would not) ______ generate a sample representing the population of typical customers.

Would not

It is advisable to _____ the acquisition, transformation and analysis tasks.

Separate

One reason reproducibility matters is to protect and support your _____ self.

Future

Another reason reproducibility matters to guard against _____ and _____.

Error, Fraud

One important component is describing the exact _____ of your raw input data.

Source

You should view a reproducible analysis as a _____ that you should be able to produce again and again.

Product

A _____ is a representation of the data structure comprising all of the attributes of the data and their types.

Data Schema

This representation of the data structure identifies the _____ to which each observation pertains.

Unit of record

This representation of the data also makes clear what are the _____ that identify an observation.

Key Variables

A terabyte is equal to a _____ bytes.

one trillion

R stores real numbers as a _____ data type and allocates _____ bytes of data to each number.

Numeric, 8

A megabyte can store _____ num values, while a terabye can store roughly a _____ times that.

131072, 1000000

The key idea behind _____ is that one draw from a population does not depend on another.

Random Sampling

Because we generally do not know the underlying data-generating process, we try to ______ it from the data we observe.

infer

The frequentist approach to probability defines the probability of some event (A) as the number of times it occurs out of an _____ number of random trials.

Infinite

This idea of relative frequency converging to the true probability is an example of the _____.

Law of Large Numbers

Because earnings distributions tend to be _____ right, the _______ distribution if often a good model for earnings data.

skewed, lognormal

The _____ is the thing we want to learn about. An _____ is the thing we compute to learn about it, which for a given set of data, gives us an _____ .

estimand, estimator, estimate

If E(estimator) equals the thing we want to learn about, we say that it is _____

Unbiased

Sample selection may be a source of _____ if the data we have does not represent the population we want to learn about.

bias

The natural log function is the inverse of the _____ function.

Exponential

The log of earnings is undefined if earnings equal _____.

0

Log transformations help us talk about _____ differences or changes.

Percentage

Comparing the earnings of women and men involves estimating the _____ expectation of _____ given _____.

Conditional, earnings, gender

The concept of a random variable's expected value is a _____ average of all the random variable's possible _____.

weighted, outcomes

Because we rarely know a random variable's distribution, we typically _____ its expected value using its _____ average.

Estimate, Sample

The expected value of an indicator variable that takes on the values 1 and 0 is equivalent to the _____ the random variable equals _____.

Probability, 1

The _____ says that the expected value of the CEF of, say, Y given X, is the expected value of Y.

LIE

The CEF gives the expected value of some random variable Y given the value of another random variable X. Applied to last week's work the gender pay gap, the Y was ______ and the X was ______ .

Earnings, gender

The formula E{[X−E(X)]^2}, calculates the ______ of a ______ .

Variance, Random variable

The expression E{[X−E(X)][Y−E(Y)] defines the ______ between ______ and ______ .

Covariance, x, y

To estimate E{[X−E(X)][Y−E(Y)] , we can just plug in the sample _____ for E(X) and E(Y) and replace the outer expectation with another sample _____ .

Mean, average

Covariance indicates the ______ of a relationship but not the ______ of a relationship.

direction, strength

The estimated correlation between earnings and age among 23-62 year-olds using the March 2009 CPS is ______ .

.13

If we want to estimate E(earnings|age=23), the simplest thing to do is plug in the sample ______ of earnings of 23-year-olds.

Mean

If we want to estimate E(earnings|age), the simplest thing to do is plug in the sample ______ earnings for each value of ______

mean, age

If we want to estimate how earnings change from one point in a career to the next, we can just _____ the sample ______ earnings for one age value from another.

subtract, mean

Based on Figure 6, earnings tend to ______ early in a career and plateau after age 40 or so.

rise

Modeling the pattern in Figure 6 with a linear function of age assumes that the difference in earnings from one age to the next is ______ .

Constant

Modeling the pattern in Figure 6 with a quadratic function of age captures the ______ shape of the relationship between earnings and age.

Concave

If you model the pattern in Figure 6 with a quadratic function of age, the difference in earnings from one age to the next varies with ______ .

age

Using the March 2009 CPS data, the quadratic model of E(earnings|age) predicts earnings increase up to roughly age _____ .

50

The quadratic model of E(earnings|age) fits the data well and is also justified by ______ theory

human capitol

The reason we want to move from earnings to wages is that the story is really about ______ .

Productivity

Earnings is a measure of both ______ and ______ , which masks productivity.

Wages, hours

Based on Table 2 in the deck, the gender gap in average wages in our sample of 23-62 year-olds is roughly $_____ per hour (round to the nearest whole number).

7

Our framework for using data to learn about the world is gathering ______ from the ______ of interest to infer features of the _____ process.

Random Samples, Population, data generating

In principle, any estimator can be decomposed into three parts:

Estimator=______+______+______

Estimand, bias, sampling error

If an estimator approaches the underlying estimand as sample size grows, we say the esimator has the property of ______ .

Consistency

If an estimator obeys the CLT, we can treat its sampling ______ as ______ for large sample sizes.

Distribution, Normal

Consistency means that as the sample size increases, both ______ and ______ approach zero.

bias, sampling error

A confidence interval tells how likely an estimate we calculate is close to its target in the ______ .

Population

Statistical hypothesis tests translate information contained in a confidence interval into _____ answers to particular questions.

yes/no

a t-test compares the _____ you obtain from the sample with the hypothesized value of the estimand divided by the _____ of the estimator.

Estimate, standard error

We reject the null hypothesis at the 5% level if the value of the t statistic is greater than _____ in absolute value.

1.96

Based on Figure 8 in the slide deck, it appears that the confidence intervals for average log wages overlap up to year _____ of a career.

5

To test whether the gender gap in average log wages is equal to zero, you divide the _____ in average log wages between women and men by the _____ of the difference.

difference, standard error

The absolute value of the t statistic for the null that there is no gender gap in log wages among 23-62 year-olds is _____ (round to two decimal places), which implies the null is _____ at the 5% level (or pretty much any other level for that matter).

40.95, rejected

If an estimator is consistent, any _____ and its sampling _____ vanish as sample size grows.

bias, error

If an estimator is consistent, we say it _____ the estimand.

identifies

When a CPS respondent refuses to report their earnings there is an _____ nonresponse.

item

Let's say that X∗ is the true X but is not directly observed because of measurment error. A simple model for this scenario is _____ = X∗ + _____.

x, e

If X∗ is _____ to the measurement error, we cannot learn anything about the distribution of X∗ from the distribution of _____

related, x

The classical measurement-error assumptions include that the expected value of the measurement error is _____ and the measurement error independent of the true _____.

0, x

One implication of classical measurement error is that corr(X,Y) _____ corr(X∗,Y), where Y is another random variable to which X might be related.

<

When X is binary, measurement error results in _____ and the _____ assumptions don't apply

misclassification, classical

When X is binary, learning about P(X∗=1) depends on the _____ positive and _____ negative rates.

False, False

Some students in Project STAR move away, resulting in _____, which is a form of _____ nonresponse.

attrition, unit

To understand the effects of sample selection on our ability to learn about E(Y|X), we need to know how selection depends on _____ and _____.

Y, X

If the selection mechanism is _____ of the X and Y, then we say missing data are missing _____.

independent, completely at random

If S represents the selection mechanism and E(Y|X,S)=E(Y|X), then we say the missing data are missing _____ or the mechanism is _____.

at random, exogenous

In the card data, 949 men do not have an IQ test score. This would violate _____ if the probability that a score is missing is higher for lower IQ men.

MCAR

One way to _____ missing values is to predict them using a statistical model.

Impute