@ -6,32 +6,31 @@
* Title slide :slide:
#+BEGIN_SRC emacs-lisp-slide
(org-show-animate '("Quantitative Methods, Part-II" "Vikas Rawal" "Prachi Bansal" "" "" ""))
(org-show-animate '("Quantitative Methods, Part-II" "Descriptive Statistics" " Vikas Rawal" "Prachi Bansal" "" "" ""))
#+END_SRC
* Day 1
** Title slide
* Title slide
#+BEGIN_SRC emacs-lisp-slide
(org-show-animate '("Why do financial journalists need to know quantitative methods?" "" "" ""))
#+END_SRC
** What do we aim to achieve in this course? :slide:
*** * Make friends with numbers
*** * Learn how to read numbers, how to present them, and how to write about them
*** * Learn how to use computers to work with numbers
** Two Types of Statistics :slide:
** * Descriptive Statistics
*** * Use summaries of data for the entire population to describe a population
*** * Use summaries of sample data to describe a sample
** * Inferential Statistics
*** * Use sample data to describe a population
** Descriptive Statistics :slide:
* What do we aim to achieve in this course? :slide:
*** Make friends with numbers
*** Learn how to read numbers, how to present them, and how to write about them
*** Learn how to use computers to work with numbers
* Two Types of Statistics :slide:
** Descriptive Statistics
*** Use summaries of data for the entire population to describe a population
*** Use summaries of sample data to describe a sample
** Inferential Statistics
*** Use sample data to describe a population
* Descriptive Statistics :slide:
+ Frequency
+ Measures of central tendency
+ Summary positions
+ Measures of dispersion
** * Frequency :slide:
** Frequency :slide:
#+NAME : worker-code0
#+begin_src R :results value :export results :colnames yes :hline
@ -93,7 +92,7 @@
| M | 7 |
| F | 9 |
** * Measures of Central Tendency :slide:
** Measures of Central Tendency :slide:
#+NAME : mid-code
#+begin_src R :results value :export results :colnames yes :hline
@ -118,7 +117,7 @@
| M | 172428.6 | 50000 |
| F | 46333.3 | 45000 |
** * Measures of Position :slide:
** Measures of Position :slide:
+ First quartile
+ Second quartile (median)
@ -128,9 +127,9 @@
+ Quintiles
+ Percentiles
** * Measures of Dispersion :slide:
** Measures of Dispersion :slide:
*** * Range and other measures based on positions :slide:
*** Range and other measures based on positions :slide:
$range=max-min$
@ -147,7 +146,7 @@ $range=max-min$
range=max(salary)-min(salary))]
#+end_src
*** * Range and other measures based on positions :slide:
*** Range and other measures based on positions :slide:
+ Distance between any two positions (Deciles, Quintiles, Percentiles) can be used as a measure of dispersion.
@ -179,7 +178,7 @@ $inter.quartile.range=Q3-Q1$
*** * Variance, Standard Deviation and Coefficient of Variation
*** Variance, Standard Deviation and Coefficient of Variation
$variance=\frac{1}{n} \times \sum(x_{i}-x)^{2}$
@ -214,59 +213,59 @@ $cov=\frac{standard.deviation}{mean}$
| F | 54500000 | 7382.4 | 0.16 |
**
*
** * Common uses of statistical graphics :slide:
** Common uses of statistical graphics :slide:
+ To show trends over time
+ To show mid-point variations across categories
+ To show composition
+ (less commonly, though more usefully) to show/analyse dispersion
** * Mis-representation :slide:
** Mis-representation :slide:
#+CAPTION : "and sometimes the fact that numbers have a magnitude as well as an order is simply forgotten"
[[file:graphics/tufte-insanity.png ]]
** * Mis-representation :slide:
** Mis-representation :slide:
#+CAPTION : Another example borrowed from Tufte
[[file:graphics/tufte-fuel.png ]]
** * Mis-representation :slide:
** Mis-representation :slide:
#+CAPTION : Tufte's graph on fuel economy of cars
#+attr_html : :width 400px
[[file:graphics/tufte-fuel2.png ]]
** * Mis-representation :slide:
** Mis-representation :slide:
#+CAPTION : Nobel prizes awarded in science (National Science Foundation, 1974)
#+attr_html : :width 300px
[[file:graphics/nobel-wrong.png ]]
** * Mis-representation :slide:
** Mis-representation :slide:
#+CAPTION : Nobel prizes awarded in science (corrected by Tufte)
#+attr_html : :width 300px
[[file:graphics/nobel-right.png ]]
** * Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
** Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
[[file:graphics/piketty1_o.png ]]
** * Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
** Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
[[file:graphics/piketty1_c.png ]]
** * Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
** Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
[[file:graphics/piketty2_o.png ]]
** * Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
** Mis-representation: illustrations from Thomas Piketty's work (source Noah Wright) :slide:
[[file:graphics/piketty2_c.png ]]
** * The problem multiplied with the coming in of spreadsheets :slide:
** The problem multiplied with the coming in of spreadsheets :slide:
#+ATTR_html : :width 300px
[[file:graphics/chart1.png ]]
@ -277,8 +276,8 @@ $cov=\frac{standard.deviation}{mean}$
#+ATTR_html : :width 300px
[[file:graphics/chart3.png ]]
** :slide:
** * Histogram :slide:
* :slide:
** Histogram :slide:
#+RESULTS : ccpc-wheat-hist1
#+attr_html : :width 800px
@ -292,7 +291,7 @@ $cov=\frac{standard.deviation}{mean}$
hist(b$yield,main="Histogram of wheat yields",ylim=c(0,4000))
#+END_SRC
** * Histogram with relative densities :slide:
** Histogram with relative densities :slide:
#+RESULTS : ccpc-wheat-hist2
#+attr_html : :width 600px
@ -306,13 +305,13 @@ $cov=\frac{standard.deviation}{mean}$
hist(b$yield,freq=F,main= "Histogram of wheat yields",ylim=c(0,0.00040))
#+END_SRC
** * Boxplot :slide:
** Boxplot :slide:
+ Invented by John Tukey in 1970
+ Many variations proposed since then, though the essential form and idea as remained intact.
** * Boxplot of wheat yields :slide:
** Boxplot of wheat yields :slide:
#+RESULTS : ccpc-wheat-box1
[[file:boxplotyield1.png ]]
@ -325,7 +324,7 @@ $cov=\frac{standard.deviation}{mean}$
boxplot(b$yield,main="Boxplot of wheat yields")
#+END_SRC
** * Violin plots :slide:
** Violin plots :slide:
#+RESULTS : ccpc-wheat-vio1
[[file:vioplotyield1.png ]]
@ -342,7 +341,7 @@ $cov=\frac{standard.deviation}{mean}$
** * Boxplots: Useful to identify extreme values :slide:
** Boxplots: Useful to identify extreme values :slide:
#+RESULTS : ccpc-wheat-box2
@ -355,7 +354,7 @@ $cov=\frac{standard.deviation}{mean}$
boxplot(b$yield,main="Magnified tail of the boxplot",ylim=c(7000,25000))
#+END_SRC
** * Boxplots: Useful for comparisons across categories :slide:
** Boxplots: Useful for comparisons across categories :slide:
#+RESULTS : ccpc-crop-box3
[[file:boxplotyield3.png ]]
@ -369,7 +368,7 @@ $cov=\frac{standard.deviation}{mean}$
boxplot(yield~Crop_code,data=b,main= "Boxplots of yields of various crops",las=3,ylim=c(0,8000),outline=F)
#+END_SRC
** * Violin plots :slide:
** Violin plots :slide:
#+RESULTS : ccpc-crop-vio
[[file:vioplotyield3.png ]]
@ -389,3 +388,37 @@ $cov=\frac{standard.deviation}{mean}$
* Paul Krugman on Fiscal Austerity
** What does this graph show? :slide:
#+attr_html : :width 1200px
[[file:krugman1.png ]]
Source: [[https://www.nytimes.com/2018/11/02/opinion/the-perversion-of-fiscal-policy-slightly-wonkish.html ]]
** What did Paul Krugman say? :slide:
"Here’
** How could we better show the relationship between unemployment and fiscal austerity :slide:
#+name : fixed-krugman-graph
#+attr_html : :width 1200px
[[file:krugman2.png ]]
#+NAME : graph2
#+BEGIN_SRC R :results output graphics :exports results :file krugman2.png :width 2000 :height 2000 :res 300
library(data.table)
library(ggplot2)
fread("~/ssercloud/acj2018/krugmandata.csv")->a
as.Date(a$date,format=c("%m/%d/ %y"))->a$date
factor(ifelse(a$date<"2010-01-01","2000-2009","2010-2018"))- >a$Period
melt(a,id=c("date","Period"),m=c("impact","unemployment"))->t
levels(t$variable)<-c("Fiscal stimulus","Unemployment rate")
ggplot(t,aes(x=date,y=value,group=variable,colour=Period))->p
p+geom_line(size=1.2)+facet_wrap(~variable,scales= "free_y",ncol=1)->p
p+scale_y_continuous("Per cent")+theme(legend.position="bottom")->p
p+scale_x_date("Year/Month",date_labels = "%Y")
#+END_SRC
