The motion picture industry is a competitive business. More than 50 studios prod
ID: 3208265 • Letter: T
Question
The motion picture industry is a competitive business. More than 50 studios produce a total of 300 to 400 new motion pictures each year, and the financial success of each motion picture varies considerably. Gross sales for the opening weekend, the total gross sales, the number of theaters the movie was shown in, and the number of weeks the motion picture was open are common variables used to measure the success of a motion picture. Data collected for a sample of 100 motion pictures produced in 20XX are contained in the file named Movies, linked at the bottom of the page. Use all 100 data points.
Managerial Report
Prepare a report (see below) using the numerical methods of descriptive statistics presented in this module to learn how each of the variables contributes to the success of a motion picture. Be sure to include the following three (3) items in your report.
Be sure to include the following three (3) items in your report:
1) Descriptive statistics (mean, median, range, and standard deviation) for each of the four variables along with an explanation of what the descriptive statistics tell us about the counties.
2) Use the z-score to determine which counties, if any, should be considered outliers in each of the four variables. If there are any outliers in any category, please list them and state for which category they are an outlier. Describe which method you used to make your determination.
3) Descriptive statistics (correlation coefficient) showing the relationship between median household income (in dollars), and each of the other three variables. Thus, that makes a total of three correlation coefficients. Evaluate the relationships between median household income (in dollars) and each of the other three variables. Use tables, charts, graphs, or visual dashboards to support your conclusions.
Rank Movie Title Opening Gross Total Gross Theaters Weeks 1 Harry Potter and the Deathly Hallows Part 2 169,189,427 381,011,219 4,375 19 2 Transformers: Dark of the Moon 97,852,865 352,390,543 4,088 15 3 The Twilight Saga: Breaking Dawn Part 1 138,122,261 281,287,133 4,066 14 4 The Hangover Part II 85,946,294 254,464,305 3,675 16 5 Pirates of the Caribbean: On Stranger Tides 90,151,958 241,071,802 4,164 19 6 Fast Five 86,198,765 209,837,675 3,793 15 7 Mission: Impossible - Ghost Protocol 12,785,204 209,397,903 3,555 17 8 Cars 2 66,135,507 191,452,396 4,115 25 9 Sherlock Holmes: A Game of Shadows 39,637,079 186,848,418 3,703 16 10 Thor 65,723,338 181,030,624 3,963 16 11 Rise of the Planet of the Apes 54,806,191 176,760,185 3,691 19 12 Captain America: The First Avenger 65,058,524 176,654,505 3,715 16 13 The Help 26,044,590 169,708,112 3,014 30 14 Bridesmaids 26,247,410 169,106,725 2,958 20 15 Kung Fu Panda 2 47,656,302 165,249,063 3,952 18 16 Puss in Boots 34,077,439 149,260,504 3,963 18 17 X-Men: First Class 55,101,604 146,408,305 3,692 17 18 Rio 39,225,962 143,619,809 3,842 21 19 The Smurfs 35,611,637 142,614,158 3,427 20 20 Alvin and the Chipmunks: Chipwrecked 23,244,744 133,110,742 3,734 25 21 Super 8 35,451,168 127,004,179 3,424 16 22 Rango 38,079,323 123,477,607 3,923 18 23 Horrible Bosses 28,302,165 117,538,559 3,134 16 24 Green Lantern 53,174,303 116,601,172 3,816 15 25 Hop 37,543,710 108,085,305 3,616 11 26 Paranormal Activity 3 52,568,183 104,028,807 3,329 11 27 Just Go With It 30,514,732 103,028,109 3,548 14 28 The Girl with the Dragon Tattoo (2011) 12,768,604 102,515,793 2,950 13 29 Bad Teacher 31,603,106 100,292,856 3,049 16 30 Cowboys & Aliens 36,431,290 100,240,551 3,754 14 31 Gnomeo and Juliet 25,356,909 99,967,670 3,037 19 32 The Green Hornet 33,526,876 98,780,042 3,584 14 33 The Lion King (in 3D) 30,151,614 94,242,001 2,340 17 34 The Muppets 29,239,026 88,631,237 3,440 19 35 Real Steel 27,319,677 85,468,508 3,440 19 36 Crazy, Stupid, Love. 19,104,303 84,351,197 3,020 17 37 Battle: Los Angeles 35,573,187 83,552,429 3,417 12 38 Immortals 32,206,425 83,504,017 3,120 15 39 The Descendants 1,190,096 82,584,160 2,038 22 40 Zookeeper 20,065,617 80,360,843 3,482 16 41 War Horse 7,515,402 79,884,879 2,856 19 42 Limitless 18,907,302 79,249,455 2,838 16 43 Tower Heist 24,025,190 78,046,570 3,870 13 44 The Adventures of Tintin 9,720,993 77,591,831 3,087 13 45 Contagion 22,403,596 75,658,097 3,222 14 46 We Bought a Zoo 9,360,434 75,624,550 3,170 21 47 Moneyball 19,501,302 75,605,492 3,018 19 48 Jack and Jill 25,003,575 74,158,157 3,438 15 49 Hugo 11,364,505 73,864,507 2,608 20 50 Justin Bieber: Never Say Never 29,514,054 73,013,910 3,118 13 51 Dolphin Tale 19,152,401 72,286,779 3,515 18 52 No Strings Attached 19,652,921 70,662,220 3,050 11 53 Mr. Popper's Penguins 18,445,355 68,224,452 3,342 18 54 Happy Feet Two 21,237,068 64,006,466 3,611 16 55 Unknown 21,856,389 63,686,397 3,043 12 56 The Adjustment Bureau 21,157,730 62,495,645 2,847 12 57 Water for Elephants 16,842,353 58,709,717 2,820 16 58 The Lincoln Lawyer 13,206,453 58,009,200 2,707 18 59 Midnight in Paris 599,003 56,817,045 1,038 44 60 Friends with Benefits 18,622,150 55,802,754 2,926 9 61 I Am Number Four 19,449,893 55,100,437 3,156 15 62 Source Code 14,812,094 54,712,227 2,971 15 63 New Year's Eve 13,019,180 54,544,638 3,505 11 64 Insidious 13,271,464 54,009,150 2,419 23 65 Tyler Perry's Madea's Big Happy Family 25,068,677 53,345,287 2,288 13 66 Diary of a Wimpy Kid: Rodrick Rules 23,751,502 52,698,535 3,169 16 67 Footloose (2011) 15,556,113 51,802,742 3,555 13 68 The Dilemma 17,816,230 48,475,290 2,943 7 69 Arthur Christmas 12,068,931 46,462,469 3,376 7 70 Hall Pass 13,535,374 45,060,734 2,950 11 71 The Artist 204,878 44,671,682 1,756 30 72 Soul Surfer 10,601,862 43,853,424 2,240 15 73 Final Destination 5 18,031,396 42,587,643 3,155 9 74 The Ides of March 10,470,143 40,962,534 2,199 14 75 Hanna 12,370,549 40,259,119 2,545 13 76 Something Borrowed 13,945,368 39,046,489 2,904 12 77 Spy Kids: All the Time in the World 11,644,672 38,538,188 3,305 17 78 Scream 4 18,692,090 38,180,928 3,314 11 79 Big Mommas: Like Father, Like Son 16,300,803 37,915,414 2,821 14 80 Red Riding Hood 14,005,335 37,662,162 3,030 11 81 In Time 12,050,368 37,520,095 3,127 14 82 Paul 13,043,310 37,412,945 2,806 9 83 J. Edgar 11,217,324 37,306,030 1,985 15 84 The Roommate 15,002,635 37,300,107 2,534 7 85 Jumping the Broom 15,215,487 37,295,394 2,035 8 86 The Change-Up 13,531,115 37,081,475 2,913 8 87 30 Minutes or Less 13,330,118 37,053,924 2,888 7 88 Colombiana 10,408,176 36,665,854 2,614 10 89 Sucker Punch 19,058,199 36,392,502 3,033 9 90 Larry Crowne 13,096,065 35,608,245 2,976 7 91 A Very Harold & Kumar 3D Christmas 12,954,142 35,061,031 2,875 10 92 Drive (2011) 11,340,461 35,060,689 2,904 21 93 50/50 8,644,095 35,014,192 2,479 13 94 Courageous 9,112,839 34,522,221 1,214 17 95 The Rite 14,789,393 33,047,633 2,985 10 96 Arthur (2011) 12,222,756 33,035,397 3,276 9 97 Extremely Loud & Incredibly Close 72,348 31,847,881 2,630 14 98 The Debt 9,909,499 31,177,548 1,874 9 99 The Sitter 9,851,435 30,441,326 2,752 10 100 The Iron Lady 220,409 30,017,992 1,244 17Explanation / Answer
We shall solve this using the open source software R
The complete R snippet is as follows
# read the data into R dataframe
data.df<- read.csv("C:\Users\586645\Downloads\Chegg\movies.csv",header=TRUE)
str(data.df)
# descriptive stats
summary(data.df)
# lets convert the data into z score
data.df$Opening.Gross<- scale(data.df$Opening.Gross)
data.df$Total.Gross<- scale(data.df$Total.Gross)
data.df$Theaters<- scale(data.df$Theaters)
data.df$Weeks<- scale(data.df$Weeks)
The results are
> summary(data.df)
Rank Movie.Title Opening.Gross.V1
Min. : 1.00 30 Minutes or Less : 1 Min. :-1.025107
1st Qu.: 25.75 50/50 : 1 1st Qu.:-0.542902
Median : 50.50 A Very Harold & Kumar 3D Christmas : 1 Median :-0.311205
Mean : 50.50 Alvin and the Chipmunks: Chipwrecked: 1 Mean : 0.000000
3rd Qu.: 75.25 Arthur (2011) : 1 3rd Qu.: 0.164733
Max. :100.00 Arthur Christmas : 1 Max. : 5.326290
(Other) :94
Total.Gross.V1 Theaters.V1 Weeks.V1
Min. :-0.889070 Min. :-3.227260 Min. :-1.523517
1st Qu.:-0.743170 1st Qu.:-0.396955 1st Qu.:-0.603519
Median :-0.263181 Median : 0.006814 Median :-0.051520
Mean : 0.000000 Mean : 0.000000 Mean : 0.000000
3rd Qu.: 0.212377 3rd Qu.: 0.707439 3rd Qu.: 0.500479
Max. : 4.263889 Max. : 2.000207 Max. : 5.284470
> #outliers
> # we shall consider a record as outlier if it is outside -2 and 2
>
> subset(data.df,Opening.Gross >= 2 | Opening.Gross <= -2)
Rank Movie.Title Opening.Gross Total.Gross
1 1 Harry Potter and the Deathly Hallows Part 2 5.326290 4.263889
2 2 Transformers: Dark of the Moon 2.647159 3.843707
3 3 The Twilight Saga: Breaking Dawn Part 1 4.159525 2.799832
4 4 The Hangover Part II 2.199993 2.406044
5 5 Pirates of the Caribbean: On Stranger Tides 2.357942 2.209428
6 6 Fast Five 2.209475 1.750877
Theaters Weeks
1 2.0002073 0.68447875
2 1.5506169 -0.05151991
3 1.5161535 -0.23551957
4 0.9036454 0.13247976
5 1.6696722 0.68447875
6 1.0884944 -0.05151991
>
> subset(data.df,Total.Gross >= 2 | Total.Gross <= -2)
Rank Movie.Title Opening.Gross Total.Gross
1 1 Harry Potter and the Deathly Hallows Part 2 5.326290 4.263889
2 2 Transformers: Dark of the Moon 2.647159 3.843707
3 3 The Twilight Saga: Breaking Dawn Part 1 4.159525 2.799832
4 4 The Hangover Part II 2.199993 2.406044
5 5 Pirates of the Caribbean: On Stranger Tides 2.357942 2.209428
Theaters Weeks
1 2.0002073 0.68447875
2 1.5506169 -0.05151991
3 1.5161535 -0.23551957
4 0.9036454 0.13247976
5 1.6696722 0.68447875
>
> subset(data.df,Theaters >= 2 | Theaters <= -2)
Rank Movie.Title Opening.Gross Total.Gross
1 1 Harry Potter and the Deathly Hallows Part 2 5.3262904 4.2638894
59 59 Midnight in Paris -1.0053281 -0.4956309
71 71 The Artist -1.0201300 -0.6739380
94 94 Courageous -0.6855806 -0.8229430
100 100 The Iron Lady -1.0195467 -0.8890699
Theaters Weeks
1 2.000207 0.6844788
59 -3.227260 5.2844704
71 -2.102501 2.7084751
94 -2.951553 0.3164794
100 -2.904558 0.3164794
>
> subset(data.df,Weeks >= 2 | Weeks <= -2)
Rank Movie.Title Opening.Gross Total.Gross Theaters Weeks
13 13 The Help -0.04968812 1.1617317 -0.1318224 2.708475
59 59 Midnight in Paris -1.00532811 -0.4956309 -3.2272601 5.284470
71 71 The Artist -1.02012995 -0.6739380 -2.1025008 2.708475
> summary(data.df)
Rank Movie.Title Opening.Gross
Min. : 1.00 30 Minutes or Less : 1 Min. : 72348
1st Qu.: 25.75 50/50 : 1 1st Qu.: 12911908
Median : 50.50 A Very Harold & Kumar 3D Christmas : 1 Median : 19081251
Mean : 50.50 Alvin and the Chipmunks: Chipwrecked: 1 Mean : 27367623
3rd Qu.: 75.25 Arthur (2011) : 1 3rd Qu.: 31753936
Max. :100.00 Arthur Christmas : 1 Max. :169189427
(Other) :94
Total.Gross Theaters Weeks
Min. : 30017992 Min. :1038 Min. : 7.00
1st Qu.: 39955962 1st Qu.:2845 1st Qu.:12.00
Median : 72650344 Median :3102 Median :15.00
Mean : 90576889 Mean :3098 Mean :15.28
3rd Qu.:105042932 3rd Qu.:3550 3rd Qu.:18.00
Max. :381011219 Max. :4375 Max. :44.00
Household income variable is not given in the question . However , the correlation between 2 columns in R can be found as
cor(data.df$Opening.Gross,data.df$Total.Gross)
0.8877445