DATA JOURNALISM

Dr. Bahareh Heravi @Bahareh360

Week 11Newsroom Statistics

What we have learned so farWhat Data Journalism is about���Finding Data���Data collection���Data scraping���Data mashing and summarisation���Data cleaning���Data aanalysis���Data visualisation with graphs, charts and infographics���Data visualisation with maps���FOI���Social Media as a source

   

NEWSROOM  STATISTICS  

We have learned before

Simple newsroom math

sum, average, median

Rate

Percent change

   

ANALYSING  RELATIONSHIPS  

Correlation analysis

Correlation concerns the strength of relationship between values of two variables.

���Are height and weight correlated?

Are engine size and max speed in cars correlated?

Correlation

Perfect  nega+ve   Perfect  posi+ve  

No  correla+on  

-­‐1  

0  

strong  strong  

weak  weak  

-­‐0.5   0.5  

1  

Source:  Sta+s+cs  without  tears,  Derek  Rowntree  

-­‐1  -­‐0.8  -­‐0.3  

0.3  

0  

0.8   1  

Student   Theory   Prac=cal  A   59   70  B   63   69  C   64   76  D   70   79  E   76   74  F   78   80  G   82   77  H   79   86  I   86   84  J   92   90  

50  

55  

60  

65  

70  

75  

80  

85  

90  

95  

50   55   60   65   70   75   80   85   90   95  

Theo

ry  

Prac=cal  

50  

55  

60  

65  

70  

75  

80  

85  

90  

95  

50   55   60   65   70   75   80   85   90   95  

Theo

ry  

Prac=cal  

Student   Theory   Prac=cal  G   82   77  H   79   86  I   86   84  

76  77  78  79  80  81  82  83  84  85  86  87  

78   79   80   81   82   83   84   85   86   87  

Theo

ry  

Prac=cal  

76  77  78  79  80  81  82  83  84  85  86  87  

78   79   80   81   82   83   84   85   86   87  

Theo

ry  

Prac=cal  

? !

   

SIGNIFICANCE  TEST  

Significance test

Significance test is to determine whether an observed relationship is real, or is it just one that we would anyway expect to see quite often by chance?

We start out assuming that there is no real

relationship between the two variables: null

hypothesis.

p valuep value: the probability that your relationship has happened by chance. The smaller the p value the more significant the relationship.

p value is calculated probability of an observed difference occurring by chance when really no difference/relationship actually exists (null hypothesis).

If p value was small enough(?*), we can reject the null hypothesis. ���

p value cut offs

p < 0.05 or 0.05 level significant*

p < 0.01 or 0.01 level highly significant**

���

WARNING

?

Correlation = Causation���

Other statistical analysis tools

R

PSPP

Excel solver ���

Hands-on

Correlation analysis and significant test for:

Penalty points in counties in Ireland and rate of road fatalities.

Use SPSS or PSPP

Go back to your penalty points and road fatalities story/data.

You have now completed all the data analysis and visualisation needed for our

penalty points story.������Well done!

Resources:    Sta+s+cs  without  tears:  A  primer  for  non-­‐mathema+cians,    Derek  Rowntree,    first  published  1981    Sta+s+cs  done  wrong,  Alex  Reinhart,  2015  hNp://www.sta+s+csdonewrong.com/          

 Ques=ons?  

 

Bahareh  R.  Heravi    

 

 

@Bahareh360