Poli 5D Social Science Data Analytics More on Stata Shane Xinyang - - PowerPoint PPT Presentation

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Poli 5D Social Science Data Analytics More on Stata Shane Xinyang - - PowerPoint PPT Presentation

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Poli 5D Social Science Data Analytics More on Stata Shane Xinyang Xuan ShaneXuan.com February 1, 2017 ShaneXuan.com 1 / 12 Contact Information Shane Xinyang Xuan xxuan@ucsd.edu The teaching sta ff is a team! Professor Roberts M 1600-1800

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SLIDE 1

Poli 5D Social Science Data Analytics

More on Stata Shane Xinyang Xuan ShaneXuan.com February 1, 2017

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SLIDE 2

Contact Information

Shane Xinyang Xuan xxuan@ucsd.edu The teaching staff is a team! Professor Roberts M 1600-1800 (SSB 299) Jason Bigenho Th 1000-1200 (Econ 116) Shane Xuan M 1100-1150 (SSB 332) TH 1200-1250 (SSB 332) Supplemental Materials UCLA STATA starter kit http://www.ats.ucla.edu/stat/stata/sk/ Princeton data analysis http://dss.princeton.edu/training/

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Road map

Some quick notes before we start today’s section: – Make sure that you pass around the attendance sheet – Open a .do file – Import your data (“h1 fams data.xlsx”) – I will be using my slides, and you will need to type the code in your .do file

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Announcement

I have changed my office hours to

I Monday 11-11:50 am I Thursday 12-12:50 pm

in order to accommodate as many students as possible.

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SLIDE 5

Data management

I You should have the data imported before the section starts:

– cd “/Users/Shane/Dropbox/Poli5D/psets/” – import excel “h1 fams data.xlsx”, sheet(“Families”) firstrow clear

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SLIDE 6

Data management

I You should have the data imported before the section starts:

– cd “/Users/Shane/Dropbox/Poli5D/psets/” – import excel “h1 fams data.xlsx”, sheet(“Families”) firstrow clear

I We want to generate a new variable (age dad2)

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SLIDE 7

Data management

I You should have the data imported before the section starts:

– cd “/Users/Shane/Dropbox/Poli5D/psets/” – import excel “h1 fams data.xlsx”, sheet(“Families”) firstrow clear

I We want to generate a new variable (age dad2)

generate age dad2 = age dad + 1

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SLIDE 8

Data management

I You should have the data imported before the section starts:

– cd “/Users/Shane/Dropbox/Poli5D/psets/” – import excel “h1 fams data.xlsx”, sheet(“Families”) firstrow clear

I We want to generate a new variable (age dad2)

generate age dad2 = age dad + 1

I We want to replace a value in variable race mom

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SLIDE 9

Data management

I You should have the data imported before the section starts:

– cd “/Users/Shane/Dropbox/Poli5D/psets/” – import excel “h1 fams data.xlsx”, sheet(“Families”) firstrow clear

I We want to generate a new variable (age dad2)

generate age dad2 = age dad + 1

I We want to replace a value in variable race mom

replace race mom = “Black” if race mom == “Blck”

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Label your variables

I Create a mapping (mom older names)

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SLIDE 11

Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

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SLIDE 12

Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

I Associate the mapping with a variable

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SLIDE 13

Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

I Associate the mapping with a variable

label values mom older mom older names

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SLIDE 14

Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

I Associate the mapping with a variable

label values mom older mom older names

I Assign label

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SLIDE 15

Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

I Associate the mapping with a variable

label values mom older mom older names

I Assign label

label variable mom older ”Whether mom is older”

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Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

I Associate the mapping with a variable

label values mom older mom older names

I Assign label

label variable mom older ”Whether mom is older”

I Tabulate your results

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Label your variables

I Create a mapping (mom older names)

label define mom older names 1 ”Yes” 0 ”No”

I Associate the mapping with a variable

label values mom older mom older names

I Assign label

label variable mom older ”Whether mom is older”

I Tabulate your results

tab mom older

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SLIDE 18

Deal with missingness

I Generate missing

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Deal with missingness

I Generate missing

generate dadmiss = missing(age dad)

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SLIDE 20

Deal with missingness

I Generate missing

generate dadmiss = missing(age dad)

I Tabulate your results

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SLIDE 21

Deal with missingness

I Generate missing

generate dadmiss = missing(age dad)

I Tabulate your results

tab dadmiss

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SLIDE 22

Deal with missingness

I Generate missing

generate dadmiss = missing(age dad)

I Tabulate your results

tab dadmiss

I lookup functions

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SLIDE 23

Deal with missingness

I Generate missing

generate dadmiss = missing(age dad)

I Tabulate your results

tab dadmiss

I lookup functions

list if dadmiss == 1

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SLIDE 24

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

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SLIDE 25

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

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Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

I Create a mapping

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SLIDE 27

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

I Create a mapping

label define agenames 1 “young” 2 “middle” 3 “older”

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SLIDE 28

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

I Create a mapping

label define agenames 1 “young” 2 “middle” 3 “older”

I Apply the mapping

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SLIDE 29

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

I Create a mapping

label define agenames 1 “young” 2 “middle” 3 “older”

I Apply the mapping

label values age dad3 agenames

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SLIDE 30

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

I Create a mapping

label define agenames 1 “young” 2 “middle” 3 “older”

I Apply the mapping

label values age dad3 agenames

I Tabulate results, calculate by row

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SLIDE 31

Create some “bins”

Scenario: We want to recode interval variables into ordinal variables.

I recode functions

recode age dad (15/25=1) (26/35=2) (36/55=3), gen(age dad3)

I Create a mapping

label define agenames 1 “young” 2 “middle” 3 “older”

I Apply the mapping

label values age dad3 agenames

I Tabulate results, calculate by row

tab age dad3 welfare, row

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SLIDE 32

Visualization in Stata

I Histogram

– histogram age mom – histogram age mom, frequency – histogram age mom, percent

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Visualization in Stata

I Histogram

– histogram age mom – histogram age mom, frequency – histogram age mom, percent

I Scatterplot

– twoway (scatter age mom age dad, mlabel(idnum) mlabsize(tiny) msize(tiny))

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SLIDE 34

Visualization in Stata (2)

I Boxplot

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Visualization in Stata (2)

I Boxplot

– graph box age mom

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SLIDE 36

Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

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SLIDE 37

Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

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Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

I Code race mom into numeric variable ShaneXuan.com 10 / 12

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Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

I Code race mom into numeric variable

encode race mom, generate(race mom2)

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Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

I Code race mom into numeric variable

encode race mom, generate(race mom2)

I install -catplot- ShaneXuan.com 10 / 12

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SLIDE 41

Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

I Code race mom into numeric variable

encode race mom, generate(race mom2)

I install -catplot-

ssc inst catplot

ShaneXuan.com 10 / 12

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SLIDE 42

Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

I Code race mom into numeric variable

encode race mom, generate(race mom2)

I install -catplot-

ssc inst catplot

I Plot ShaneXuan.com 10 / 12

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SLIDE 43

Visualization in Stata (2)

I Boxplot

– graph box age mom – graph box age mom, scheme(s1manual)

I Barplot

I Code race mom into numeric variable

encode race mom, generate(race mom2)

I install -catplot-

ssc inst catplot

I Plot

catplot race mom2

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SLIDE 44

Visualization in Stata (3)

Histogram across units

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Visualization in Stata (3)

Histogram across units

I histogram age mom if race mom==“Black”

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SLIDE 46

Visualization in Stata (3)

Histogram across units

I histogram age mom if race mom==“Black” I histogram age mom if race mom==“White”

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Visualization in Stata (3)

Histogram across units

I histogram age mom if race mom==“Black” I histogram age mom if race mom==“White” I histogram age mom, by(race mom)

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SLIDE 48

Visualization in Stata (3)

Histogram across units

I histogram age mom if race mom==“Black” I histogram age mom if race mom==“White” I histogram age mom, by(race mom)

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SLIDE 49

Midterm Review

Please ask questions.

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