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Movie budget & Rating

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Ballasticmissile
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Posted on Tuesday, August 28, 2018 - 06:55 am:       

https://www.google.com/search?rlz=1C9BKJA_enDE766DE766&hl=en -US&ei=yS2FW-akH7C7ggfM06vABA&q=stock+market+&oq=stock+marke t+&gs_l=mobile-gws-wiz-serp.3..0i131i67j0i67l4.1663.1663..38 05...0.0..0.168.168.0j1......0....1.........0i71.lPpNdcxlF-Y
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Inquisitive
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Posted on Wednesday, August 15, 2018 - 09:06 pm:       


Kindal:

Inspected IMDB dataset that has 58788 movies from year 1893 to 2005. Strangely, with increase in budget of the movies, the rating are declining.

Pearson correlation coefficient: -0.01422905

Though, correlation doesn't lead to causation and requires further investigation, this is an unexpected result.



Has the budget been adjusted for inflation? If not, the result is obvious. Amongst the older movies, some of the bad ones won't even be listed on IMDb. So you'll notice a lot of high rating movies amongst the old ones. Because of this you'll get the feeling that lower budget => higher rating. Truth is that older movies have higher ratings. So budget is indirectly acting as a proxy for how new the movie is.
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Chanakya
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Posted on Wednesday, August 19, 2015 - 08:44 am:       


Kindal:

budget, length(numeric), genere & certification - mpaa (categorical variable) of the movie are independent variables , where as votes and rating are dependent variables.

I always run the summary of the dataset, understand the basic characteristics and then run the tests. Beauty with R is, one can write own packages to do these things or use the existing ones. :-)

Graphical representation of data is vital for data analysis and you should understand the variables better and gives a sense of how they are affecting each other. In this case you can do scatter plot for budget, length, votes and ratings. Using, categorical data in visualising is key skill and gives great insights.

Coming to performance, it's at the discretion of the analyst. I handled the data between 200-400k records on desktop without any issues. If data is huge, do random sampling (many functions exist) and extract 2000-3000 records. Analyse them and unless you are missing something critical, you can generalise these findings on the population.




thanQ for the explanation :-)
You have your way. I have my way. As for the right way, the correct way, and the only way, it does not exist.
~Friedrich Nietzsche
 

Chanakya
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Posted on Wednesday, August 19, 2015 - 08:44 am:       


~chirutha~:

Caste vs behaviour patterns, Political party vs Corruptions, Govt Departments vs fruitful schemes etc




Genuine Data unte why not :D
You have your way. I have my way. As for the right way, the correct way, and the only way, it does not exist.
~Friedrich Nietzsche
 

~chirutha~
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Posted on Wednesday, August 19, 2015 - 08:40 am:       


Kindal:


Idantha kadu kani, do an analysis on topics like Caste vs behaviour patterns, Political party vs Corruptions, Govt Departments vs fruitful schemes etc and come here :D
Be Kool
 

Kindal
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Username: Kindal

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Posted on Wednesday, August 19, 2015 - 08:07 am:       


Chanakya:



budget, length(numeric), genere & certification - mpaa (categorical variable) of the movie are independent variables , where as votes and rating are dependent variables.

I always run the summary of the dataset, understand the basic characteristics and then run the tests. Beauty with R is, one can write own packages to do these things or use the existing ones. :-)

Graphical representation of data is vital for data analysis and you should understand the variables better and gives a sense of how they are affecting each other. In this case you can do scatter plot for budget, length, votes and ratings. Using, categorical data in visualising is key skill and gives great insights.

Coming to performance, it's at the discretion of the analyst. I handled the data between 200-400k records on desktop without any issues. If data is huge, do random sampling (many functions exist) and extract 2000-3000 records. Analyse them and unless you are missing something critical, you can generalise these findings on the population.
!ntfi
 

Chanakya
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Username: Chanakya

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Posted on Wednesday, August 19, 2015 - 07:48 am:       


Kindal:

You are right. I misread it as -0.14 and thought at such high number of ratings (37161681) and 58788 # of movies, would explain some amount of this relationship. With pearson correlation coefficient of -0.014, the relationship is non-existent. Budget and rating are not related.

To some extent, increased budget leads increased votes or viceversa. Budget of the movie and # of votes has got nothing to do with the rating of the movie.




Okies!

Also how many variables did you use? I can see its huge data, i never thought or tested R performance angle in terms of processing huge data.

if you dont mind me questioning ( i know you wouldnt :-) ) - do you draw scatter plots between all variables (atleast which you think might be related) ?
You have your way. I have my way. As for the right way, the correct way, and the only way, it does not exist.
~Friedrich Nietzsche
 

Kindal
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Username: Kindal

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Posted on Wednesday, August 19, 2015 - 07:43 am:       


Chanakya:


anything different with Pearson coefficient than the one we get in R? here -0.014 should be read as "very weak relation" between budget & Rating?



You are right. I misread it as -0.14 and thought at such high number of ratings (37161681) and 58788 # of movies, would explain some amount of this relationship. With pearson correlation coefficient of -0.014, the relationship is non-existent. Budget and rating are not related.

To some extent, increased budget leads increased votes or viceversa. Budget of the movie and # of votes has got nothing to do with the rating of the movie.
!ntfi
 

Chanakya
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Username: Chanakya

Post Number: 1616
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Posted on Wednesday, August 19, 2015 - 07:27 am:       


Kindal:

Pearson correlation coefficient: -0.01422905




anything different with Pearson coefficient than the one we get in R? here -0.014 should be read as "very weak relation" between budget & Rating?
You have your way. I have my way. As for the right way, the correct way, and the only way, it does not exist.
~Friedrich Nietzsche
 

Kindal
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Username: Kindal

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Posted on Wednesday, August 19, 2015 - 07:21 am:       


Chanakya:

what about "number of votes" vs "movie rating" how are these affecting one another?



# of votes vs rating: 0.1037069 (Very weakly correlated or we can ignore this relationship)

# votes vs budget : 0.4412935 (Weakly or near to moderately correlated).

Seems, increased budget will increase number of people to rate the movies, and thus increased voting is resulting in reduced ratings for the movie.
!ntfi
 

Chanakya
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Username: Chanakya

Post Number: 1614
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Posted on Wednesday, August 19, 2015 - 07:01 am:       

what about "number of votes" vs "movie rating" how are these affecting one another?
You have your way. I have my way. As for the right way, the correct way, and the only way, it does not exist.
~Friedrich Nietzsche
 

Kindal
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Username: Kindal

Post Number: 2706
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Posted From: 14.139.128.20

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Posted on Tuesday, August 18, 2015 - 07:26 pm:       

Inspected IMDB dataset that has 58788 movies from year 1893 to 2005. Strangely, with increase in budget of the movies, the rating are declining.

Pearson correlation coefficient: -0.01422905

Though, correlation doesn't lead to causation and requires further investigation, this is an unexpected result.
!ntfi

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