UCDavis Cards Against Humanities Black Friday Experience Excel Worksheet

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apg1277654321

Business Finance

University of California Davis

Description

See the link and attachment for instruction https://cardsagainsthumanity.com/blackfriday/

Unformatted Attachment Preview

Example – Regression Analysis Using Excel Cards Against Humanity is a social party game. The owners have a tradition of doing a Black Friday Stunt. See here https://cardsagainsthumanity.com/blackfriday/ Video https://www.youtube.com/watch?v=xv_PGBZ3JrQ Does the company make money on selling boxes of bull feces? Lets investigate the following hypothesis using data. Hypothesis: Cards Against Humanity uses its Black Friday campaign each year to increase searches for its game. What did the company do 2014 to present? STEPS 1. Use Google Trends to see data charts about searches of Cards Against Humanity on Google. 2. Use the pull down menu to change from “Past 12 months” to “Past 5 Years” 3. Download the data pressing the downward arrow button (you may need to be logged into Google for download button option to appear) 4. Open in excel 5. Understand how the google trend index is calculated https://support.google.com/trends/answer/4365533?hl=en 6. You should now have an Excel file with “week” in one column and “Google Trend Index” in another 7. Add External Data: Create a new column with 1 indicating Black Friday week each year and 0 otherwise. 8. Next we will learn how to run a simple linear regression. Click the “Data” tab at the top of the excel screen, and then select “ Data Analysis” button. The Data Analysis ToolPak must be downloaded by clicking the File>Options>Add-Inns and selecting Analysis ToolPak 1 Click on Data Analysis to reveal the following window 2 3 9. Then. In Input Y Range, select the entire column that you created in Step 7. In input X range, select the entire column that has the Google Trend Index Data. 10. Once clicking OK, a new tab will open up with the regression results. 4 13. Note that Black Friday is likely to be significantly related to an increase in trending for Cards Against Humanity ( Vdo can teach you how to read the chart above : https://www.youtube.com/watch?v=Ut22-WLvEVw & https://www.youtube.com/watch?v=BtFvua7qV4 14. This is a simple example of integrating two data sources : Google Trends Data AND information about when Black Friday Occurs (Black Friday is next day to thanksgiving each year) 15. However, could there be other explanations about why Black Friday Stunt might be significant? It is the holiday season after all. So it might be significant where was a Black Friday Stunt or not, simply related to people buying things more in general during this season. 16. Consider getting more Google Trend Data on other board games like Apple to Apple or Exploding Kittens, games whose owners do Not do Black Friday stunts like CAH. Add these as control variable to your model. a. Add in columns that have the google trends indexes for other games adjacent to the google trends index column for CAH that already exists in the table b. Follow the same process as in Steps 8-10, but when selecting the Input X range, be sure to highlight all of the columns that google trends index data. 5 17. Does significance hold for the Black Friday Stunt? Obviously, this still doesn’t prove our hypothesis, because we are only showing correlations of Google Searches on CAH with the timing of Black Friday. But it is interesting to investigate! Example DataSheet multiTimeline.rar 6
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Explanation & Answer

Here you go! I have attached the answer in an excel document for you. Feel free to ask for any clarification or edits.

Category: All categories
Week

Cards Against Humanity: (United States)
6/28/2015
7/5/2015
7/12/2015
7/19/2015
7/26/2015
8/2/2015
8/9/2015
8/16/2015
8/23/2015
8/30/2015
9/6/2015
9/13/2015
9/20/2015
9/27/2015
10/4/2015
10/11/2015
10/18/2015
10/25/2015
11/1/2015
11/8/2015
11/15/2015
11/22/2015
11/29/2015
12/6/2015
12/13/2015
12/20/2015
12/27/2015
1/3/2016
1/10/2016
1/17/2016
1/24/2016
1/31/2016
2/7/2016
2/14/2016
2/21/2016
2/28/2016
3/6/2016
3/13/2016
3/20/2016
3/27/2016
4/3/2016
4/10/2016
4/17/2016
4/24/2016

CAH
25
23
22
24
26
25
23
21
21
20
24
18
17
21
18
21
19
26
23
26
30
100
68
52
57
88
91
35
30
29
23
22
18
18
19
21
19
17
16
16
13
14
14
16

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

5/1/2016
5/8/2016
5/15/2016
5/22/2016
5/29/2016
6/5/2016
6/12/2016
6/19/2016
6/26/2016
7/3/2016
7/10/2016
7/17/2016
7/24/2016
7/31/2016
8/7/2016
8/14/2016
8/21/2016
8/28/2016
9/4/2016
9/11/2016
9/18/2016
9/25/2016
10/2/2016
10/9/2016
10/16/2016
10/23/2016
10/30/2016
11/6/2016
11/13/2016
11/20/2016
11/27/2016
12/4/2016
12/11/2016
12/18/2016
12/25/2016
1/1/2017
1/8/2017
1/15/2017
1/22/2017
1/29/2017
2/5/2017
2/12/2017
2/19/2017
2/26/2017
3/5/2017
3/12/2017
3/19/2017

17
16
20
18
19
19
16
19
17
22
17
15
13
14
16
15
14
14
17
14
14
13
14
13
15
14
15
14
15
42
37
25
30
39
51
34
21
18
18
16
19
14
16
15
13
15
14

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

3/26/2017
4/2/2017
4/9/2017
4/16/2017
4/23/2017
4/30/2017
5/7/2017
5/14/2017
5/21/2017
5/28/2017
6/4/2017
6/11/2017
6/18/2017
6/25/2017
7/2/2017
7/9/2017
7/16/2017
7/23/2017
7/30/2017
8/6/2017
8/13/2017
8/20/2017
8/27/2017
9/3/2017
9/10/2017
9/17/2017
9/24/2017
10/1/2017
10/8/2017
10/15/2017
10/22/2017
10/29/2017
11/5/2017
11/12/2017
11/19/2017
11/26/2017
12/3/2017
12/10/2017
12/17/2017
12/24/2017
12/31/2017
1/7/2018
1/14/2018
1/21/2018
1/28/2018
2/4/2018
2/11/2018

17
12
12
11
13
13
13
13
15
14
11
11
11
12
18
18
12
13
13
12
12
10
12
11
10
10
9
10
12
11
13
11
13
53
40
26
25
28
36
47
37
17
14
11
10
10
9

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0

2/18/2018
2/25/2018
3/4/2018
3/11/2018
3/18/2018
3/25/2018
4/1/2018
4/8/2018
4/15/2018
4/22/2018
4/29/2018
5/6/2018
5/13/2018
5/20/2018
5/27/2018
6/3/2018
6/10/2018
6/17/2018
6/24/2018
7/1/2018
7/8/2018
7/15/2018
7/22/2018
7/29/2018
8/5/2018
8/12/2018
8/19/2018
8/26/2018
9/2/2018
9/9/2018
9/16/2018
9/23/2018
9/30/2018
10/7/2018
10/14/2018
10/21/2018
10/28/2018
11/4/2018
11/11/2018
11/18/2018
11/25/2018
12/2/2018
12/9/2018
12/16/2018
12/23/2018
12/30/2018
1/6/2019

10
10
10
11
10
10
10
8
8
8
7
9
11
10
11
10
9
12
12
10
10
11
10
10
9
11
13
11
9
7
7
9
7
8
9
10
11
10
13
47
21
18
16
23
33
26
13

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0

1/13/2019
1/20/2019
1/27/2019
2/3/2019
2/10/2019
2/17/2019
2/24/2019
3/3/2019
3/10/2019
3/17/2019
3/24/2019
3/31/2019
4/7/2019
4/14/2019
4/21/2019
4/28/2019
5/5/2019
5/12/2019
5/19/2019
5/26/2019
6/2/2019
6/9/2019
6/16/2019
6/23/2019
6/30/2019
7/7/2019
7/14/2019
7/21/2019
7/28/2019
8/4/2019
8/11/2019
8/18/2019
8/25/2019
9/1/2019
9/8/2019
9/15/2019
9/22/2019
9/29/2019
10/6/2019
10/13/2019
10/20/2019
10/27/2019
11/3/2019
11/10/2019
11/17/2019
11/24/2019
12/1/2019

12
10
9
9
9
9
8
8
8
7
7
8
9
10
8
7
7
8
8
10
9
9
8
9
10
8
9
9
8
8
8
7
8
9
8
7
7
6
8
8
9
10
9
11
11
26
15

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0

12/8/2019
12/15/2019
12/22/2019
12/29/2019
1/5/2020
1/12/2020
1/19/2020
1/26/2020
2/2/2020
2/9/2020
2/16/2020
2/23/2020
3/1/2020
3/8/2020
3/15/2020
3/22/2020
3/29/2020
4/5/2020
4/12/2020
4/19/2020
4/26/2020
5/3/2020
5/10/2020
5/17/2020
5/24/2020
5/31/2020
6/7/2020
6/14/2020
6/21/2020

15
19
27
23
10
10
8
8
8
7
8
7
6
7
12
16
49
30
22
18
15
12
11
11
10
7
8
8
9

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.377848017
R Square
0.142769124
Adjusted R Square
0.139459352
Standard Error
0.127404202
Observations
261
ANOVA
df
Regression
Residual
Total

Intercept
X Variable 1

1
259
260

SS
0.700170417
4.204044143
4.904214559

MS
F
Significance F
0.700170417 43.13564077
2.78127E-10
0.016231831

Coefficients
Standard Error
t Stat
P-value
-0.048588751
0.012984138 -3.742162367 0.000224729
0.004074116
0.000620319 6.567772893 2.78127E-10

Lower 95%
-0.074156667
0.002852605

Upper 95%
Lower 95.0% Upper 95.0%
-0.023020834 -0.074156667 -0.023020834
0.005295627 0.002852605 0.005295627

Category: All categories
Week

Exploding Kittens: (United States)
6/28/2015
7/5/2015
7/12/2015
7/19/2015
7/26/2015
8/2/2015
8/9/2015
8/16/2015
8/23/2015
8/30/2015
9/6/2015
9/13/2015
9/20/2015
9/27/2015
10/4/2015
10/11/2015
10/18/2015
10/25/2015
11/1/2015
11/8/2015
11/15/2015
11/22/2015
11/29/2015
12/6/2015
12/13/2015
12/20/2015
12/27/2015
1/3/2016
1/10/2016
1/17/2016
1/24/2016
1/31/2016
2/7/2016
2/14/2016
2/21/2016
2/28/2016
3/6/2016
3/13/2016
3/20/2016
3/27/2016
4/3/2016
4/10/2016
4/17/2016
4/24/2016

CAH
9
7
7
10
57
100
32
35
41
28
28
21
19
18
16
19
16
18
12
21
21
52
48
46
65
89
81
32
23
39
26
19
16
18
19
18
13
15
20
15
11
13
18
16

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

5/1/2016
5/8/2016
5/15/2016
5/22/2016
5/29/2016
6/5/2016
6/12/2016
6/19/2016
6/26/2016
7/3/2016
7/10/2016
7/17/2016
7/24/2016
7/31/2016
8/7/201...


Anonymous
Really helpful material, saved me a great deal of time.

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