Homework answers / question archive / Econ B2000, Statistics and Introduction to Econometrics The first questions do not require any work in R (although you might find it convenient, I’m not stopping you) – I will provide some summary data and you can construct hypothesis tests on your own

Econ B2000, Statistics and Introduction to Econometrics The first questions do not require any work in R (although you might find it convenient, I’m not stopping you) – I will provide some summary data and you can construct hypothesis tests on your own

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Econ B2000, Statistics and Introduction to Econometrics

The first questions do not require any work in R (although you might find it convenient, I’m not stopping you) – I will provide some summary data and you can construct hypothesis tests on your own. Subsequent questions require R coding.

1. (20 points) I’ve run crosstabs on a subset of the data (so you cannot replicate, just use these data as provided). These give verbose summary of vaxx choice by educational qualification and region. Form a hypothesis test of the form, “people with various educational qualifications in Region have different fraction vaxxed compared with other Region.” I expect that you will choose different ways to operationalize educational qualification (compare above some level with below that level, but what level?) and different regions (Census provides 4 – Northeast, Midwest, South, West, you might combine them). You can choose how to deal with NA responses to vaxx – perhaps count them as ‘no’? I expect that different people may choose different levels of significance. Please provide estimate, standard error, t-stat and a p-value for the hypothesis test and a confidence interval. Write a short paragraph explaining the test (carefully noting what is the null hypothesis) and explaining the results of that test.

> xtabs(~ EEDUC + RECVDVACC + REGION)

, , REGION = Northeast

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    0           25                  15

  some hs         1           95                  17

  HS diploma     25          924                 174

  some coll      20         1407                 201

  assoc deg      15          834                 104

  bach deg       34         2603                 147

  adv deg        19         2680                  88

 

, , REGION = South

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    0           92                  45

  some hs         4          192                 101

  HS diploma     31         1844                 585

  some coll      57         3498                 747

  assoc deg      28         1704                 360

  bach deg       59         5193                 498

  adv deg        62         5024                 284

 

, , REGION = Midwest

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    3           38                  17

  some hs         5           95                  49

  HS diploma     25         1217                 329

  some coll      32         2093                 454

  assoc deg      26         1227                 245

  bach deg       56         3228                 311

  adv deg        39         2680                 143

 

, , REGION = West

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    2          107                  28

  some hs         4          204                  75

  HS diploma     24         1532                 386

  some coll      55         3896                 716

  assoc deg      29         1870                 313

  bach deg       68         5397                 467

  adv deg        50         4676                 218

2. (20 points) I’ve run crosstabs again, this time on vaxx choice by educational qualification and gender identification. Form a hypothesis test of the form, “people with various educational qualifications who are one or more gender ID have different fraction vaxxed compared with another gender ID.” I expect that you will choose different ways to operationalize educational qualification (as noted in Question 1) and different genders (including the NA response, perhaps it makes sense to combine some). Choose a level of significance. Please provide estimate, standard error, t-stat and a p-value for the hypothesis test and a confidence interval. Write a short paragraph explaining the test (carefully noting what is the null hypothesis) and explaining the results of that test.

> xtabs(~EEDUC + RECVDVACC + GENID_DESCRIBE)

, , GENID_DESCRIBE = NA

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    1            9                   2

  some hs         9            9                   2

  HS diploma     66           63                  14

  some coll      84           84                  20

  assoc deg      62           43                   7

  bach deg      148          126                  20

  adv deg       123          120                  16

 

, , GENID_DESCRIBE = male

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    3          106                  29

  some hs         1          248                  91

  HS diploma     14         1992                 557

  some coll      21         4238                 783

  assoc deg       8         1902                 297

  bach deg       26         6773                 504

  adv deg        20         6271                 263

 

, , GENID_DESCRIBE = female

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    0          131                  57

  some hs         3          309                 144

  HS diploma     25         3372                 876

  some coll      54         6411                1292

  assoc deg      28         3613                 703

  bach deg       39         9354                 873

  adv deg        22         8524                 413

 

, , GENID_DESCRIBE = transgender

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    1            3                   6

  some hs         0            6                   1

  HS diploma      0           21                   4

  some coll       0           42                   5

  assoc deg       0           12                   3

  bach deg        1           42                   2

  adv deg         0           28                  10

 

, , GENID_DESCRIBE = other

 

              RECVDVACC

EEDUC         NA yes got vaxx no did not get vaxx

  less than hs    0           13                  11

  some hs         1           14                   4

  HS diploma      0           69                  23

  some coll       5          119                  18

  assoc deg       0           65                  12

  bach deg        3          126                  24

  adv deg         5          117                  31

3. (80 points) Now do your own analysis using “Household_Pulse_data.RData”. Choose an interesting topic to explore, different from previous questions. The data includes information on housing (rent or own; whether behind on rent or mortgage), food shortage, whether work remote or in person, whether kids are in school in person or remote or homeschooled, how anxious or worried, vaxx status and plans, along with demographics like race/ethnicity, gender, marital status, and household income (as a factor).

• Choose a subgroup of the sample to consider and provide summary statistics of that subgroup. Explain why this subgroup is interesting.
• Form a hypothesis test about an interesting variable, explore whether your chosen subgroup differs from the rest of sample. Please provide both a p-value for the hypothesis test and a confidence interval. Write a short paragraph explaining the test (carefully noting what is the null hypothesis) and explaining the results of that test.
• Using a k-nn classifier, can you find relevant information to predict an interesting outcome? How good is the classifier? Discuss.
• Can you explain some other interesting information about this data? Some interesting crosstabs? Maybe regressions? Impress me.