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How to present a good look result?

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0

I would like to present a good look result for my own functions.

I create my own function to solve some chi-square test exercises, and the result looks like that:

Here is my own function:

chisq.poly = function(prob, freq, significance.level = 0.95) 

 #calculate chi-squared value
 expect_freq<-prob*sum(freq)
 dif_freq<-freq-expect_freq
 dif_freq_sq<-((freq-expect_freq)^2)/expect_freq
 chi_square<-sum(dif_freq_sq)
 chi_square_crit<-qchisq(significance.level, length(freq)-1, lower.tail=TRUE)

 #we put all necessary values into a dataframe (good for display) and then rename headers
 chi_table<-data.frame(prob,freq,expect_freq,dif_freq)
 colnames(chi_table)<-c("Probability","Frequency","Expected frequency","Difference")

 #Finally, we show the result of test
 hypothesis<-"H0: The experimental data is like the statemnent."
 result<-if (chi_square>chi_square_crit) "Reject the null hypothesis. The experimental data is not like the statemnent."
 
 else "cannot reject null hypothesis"

 warning_test<-if (abs(sum(expect_freq-freq))<sum(abs(expect_freq-freq))) "The expected frequency value may be less than 5, the result cannot be properly."
 
 else "Something good so far."

 O<-list(chi_table,chi_square,chi_square_crit,hypothesis,result,warning_test)

 names(O)<-c('Table','Chi_square','Critical Chi_square','Hypothesis','Result','Warning')

 return(O)

And I want to fix it like this or better:

r displayobject

share|improve this question

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Have a look at S3 classes and create a print function for your result as described here adv-r.had.co.nz/S3.html
  
  – drmariod
  Mar 26 at 6:43
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Instead of reinventing the wheel take a look at the broom library. In my opinion, your "good look result" is not very good looking, and -- perhaps more importantly -- not precise/correct from a statistical point of view. For example what does "The experimental data is not like the statement" even mean? Data are what they are! I guess you meant to say that the probability for observing data (frequencies) as extreme or more extreme (i.e. the p value) is small.
  
  – Maurits Evers
  Mar 26 at 7:25
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you @drmariod
  
  – Vĩnh Vũ Quang
  Mar 26 at 8:07
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you@MauritsEvers. My own function is about Goodness-of-Fit Test for polynomial distribution, and my bad vocabularies mislead you, sorry for this. I will try your suggestions, good guys :)
  
  – Vĩnh Vũ Quang
  Mar 26 at 8:14
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  stargazerit is also a good library for your purposes!
  
  – LocoGris
  Mar 26 at 9:41
  

  
  
  
  

 | 
show 1 more comment

0

I would like to present a good look result for my own functions.

I create my own function to solve some chi-square test exercises, and the result looks like that:

Here is my own function:

chisq.poly = function(prob, freq, significance.level = 0.95) 

 #calculate chi-squared value
 expect_freq<-prob*sum(freq)
 dif_freq<-freq-expect_freq
 dif_freq_sq<-((freq-expect_freq)^2)/expect_freq
 chi_square<-sum(dif_freq_sq)
 chi_square_crit<-qchisq(significance.level, length(freq)-1, lower.tail=TRUE)

 #we put all necessary values into a dataframe (good for display) and then rename headers
 chi_table<-data.frame(prob,freq,expect_freq,dif_freq)
 colnames(chi_table)<-c("Probability","Frequency","Expected frequency","Difference")

 #Finally, we show the result of test
 hypothesis<-"H0: The experimental data is like the statemnent."
 result<-if (chi_square>chi_square_crit) "Reject the null hypothesis. The experimental data is not like the statemnent."
 
 else "cannot reject null hypothesis"

 warning_test<-if (abs(sum(expect_freq-freq))<sum(abs(expect_freq-freq))) "The expected frequency value may be less than 5, the result cannot be properly."
 
 else "Something good so far."

 O<-list(chi_table,chi_square,chi_square_crit,hypothesis,result,warning_test)

 names(O)<-c('Table','Chi_square','Critical Chi_square','Hypothesis','Result','Warning')

 return(O)

And I want to fix it like this or better:

r displayobject

share|improve this question

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Have a look at S3 classes and create a print function for your result as described here adv-r.had.co.nz/S3.html
  
  – drmariod
  Mar 26 at 6:43
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Instead of reinventing the wheel take a look at the broom library. In my opinion, your "good look result" is not very good looking, and -- perhaps more importantly -- not precise/correct from a statistical point of view. For example what does "The experimental data is not like the statement" even mean? Data are what they are! I guess you meant to say that the probability for observing data (frequencies) as extreme or more extreme (i.e. the p value) is small.
  
  – Maurits Evers
  Mar 26 at 7:25
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you @drmariod
  
  – Vĩnh Vũ Quang
  Mar 26 at 8:07
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thank you@MauritsEvers. My own function is about Goodness-of-Fit Test for polynomial distribution, and my bad vocabularies mislead you, sorry for this. I will try your suggestions, good guys :)
  
  – Vĩnh Vũ Quang
  Mar 26 at 8:14
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  stargazerit is also a good library for your purposes!
  
  – LocoGris
  Mar 26 at 9:41
  

  
  
  
  

 | 
show 1 more comment

I would like to present a good look result for my own functions.

I create my own function to solve some chi-square test exercises, and the result looks like that:

Here is my own function:

chisq.poly = function(prob, freq, significance.level = 0.95) 

 #calculate chi-squared value
 expect_freq<-prob*sum(freq)
 dif_freq<-freq-expect_freq
 dif_freq_sq<-((freq-expect_freq)^2)/expect_freq
 chi_square<-sum(dif_freq_sq)
 chi_square_crit<-qchisq(significance.level, length(freq)-1, lower.tail=TRUE)

 #we put all necessary values into a dataframe (good for display) and then rename headers
 chi_table<-data.frame(prob,freq,expect_freq,dif_freq)
 colnames(chi_table)<-c("Probability","Frequency","Expected frequency","Difference")

 #Finally, we show the result of test
 hypothesis<-"H0: The experimental data is like the statemnent."
 result<-if (chi_square>chi_square_crit) "Reject the null hypothesis. The experimental data is not like the statemnent."
 
 else "cannot reject null hypothesis"

 warning_test<-if (abs(sum(expect_freq-freq))<sum(abs(expect_freq-freq))) "The expected frequency value may be less than 5, the result cannot be properly."
 
 else "Something good so far."

 O<-list(chi_table,chi_square,chi_square_crit,hypothesis,result,warning_test)

 names(O)<-c('Table','Chi_square','Critical Chi_square','Hypothesis','Result','Warning')

 return(O)

And I want to fix it like this or better:

r displayobject

share|improve this question

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges

chisq.poly = function(prob, freq, significance.level = 0.95) 

 #calculate chi-squared value
 expect_freq<-prob*sum(freq)
 dif_freq<-freq-expect_freq
 dif_freq_sq<-((freq-expect_freq)^2)/expect_freq
 chi_square<-sum(dif_freq_sq)
 chi_square_crit<-qchisq(significance.level, length(freq)-1, lower.tail=TRUE)

 #we put all necessary values into a dataframe (good for display) and then rename headers
 chi_table<-data.frame(prob,freq,expect_freq,dif_freq)
 colnames(chi_table)<-c("Probability","Frequency","Expected frequency","Difference")

 #Finally, we show the result of test
 hypothesis<-"H0: The experimental data is like the statemnent."
 result<-if (chi_square>chi_square_crit) "Reject the null hypothesis. The experimental data is not like the statemnent."
 
 else "cannot reject null hypothesis"

 warning_test<-if (abs(sum(expect_freq-freq))<sum(abs(expect_freq-freq))) "The expected frequency value may be less than 5, the result cannot be properly."
 
 else "Something good so far."

 O<-list(chi_table,chi_square,chi_square_crit,hypothesis,result,warning_test)

 names(O)<-c('Table','Chi_square','Critical Chi_square','Hypothesis','Result','Warning')

 return(O)

share|improve this question

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges

share|improve this question

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

edited Mar 26 at 6:31

Uwe Keim

28.1k3232 gold badges141141 silver badges225225 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges

asked Mar 26 at 6:30

Vĩnh Vũ QuangVĩnh Vũ Quang

1122 bronze badges