#comp3

[neverluckalwaysme]

#comp3

[carlarzall]

comp3

✦✦✦ Thank you for viewing, comments/replies are LOVED!  ✦✦✦

Another contest entry thing

✦✦✦ Commission + Other links;; https://linktr.ee/carlarzall Disc server;; https://discord.gg/TGpPUE9mfG  ✦✦✦ Stop! You may not use this art unless explicitly said it was for you. Don't use as your pfp, RP, claim as your own, etc. Don't copy/trace/ref unless you ask please.

[aristsagainstarttheft]

Pose theft issues- Common Geometric Shapes are NOT copyrightable.

I want to make note that Pose Theft Accusations  Are wrong in general and this document I found via American law at least, via.GOV ( which is Official) says Pose theft accusations is wrong in themselves. and therefore  I am innocent, as many others are as well.

No, I do not have a hate boner, I have a hate boner for being wrongfully accused of tracing.

https://www.copyright.gov/comp3/redlines/chap900.pdf

-- According to this documentation, if someone makes a similar pose to you shape-wise, it is not copyrightable via American law. (Please note that this is American Law.) Simple geometric shapes are not copyrightable. So, in my case with the centaur, mine was different enough not to be seen as art theft. No, I am not admitting to doing so.

I looked all over through the law to find this information out because of this, I want an apology for those who are accused if applicable. or them to be left alone, which ever or.

______________________________ FROM THE DOCUMENT_______________________

C O M P E N D I U M O F U . S . C O P Y R I G H T O F F I C E P R A C T I C E S , Third Edition Chapter 900 : 13 01/28/2021 In all cases, a visual art work must contain a sufficient amount of creative expression. Merely bringing together only a few standard forms or shapes with minor linear or spatial variations does not satisfy this requirement. The Office will not register works that consist entirely of uncopyrightable elements (such as those discussed in Chapter 300, Section 313 and Section 906 below) unless those elements have been selected, coordinated, and/or arranged in a sufficiently creative manner. In no event can registration rest solely upon the mere communication in two- or three-dimensional form of an idea, method of operation, process, or system. In each case, the author’s creative expression must stand alone as an independent work apart from the idea which informs it. 17 U.S.C. § 102(b).; Mazer, 347 U.S. at 217 (“[A] copyright gives no exclusive right to the art disclosed; protection is given only to the expression of the idea – not the idea itself.”). For more information on copyrightable authorship, see Chapter 300 (Copyrightable Authorship: What Can beBe Registered). 906 Uncopyrightable Material Section 102(a) of the Copyright Act states that copyright protection only extends to “original works of authorship.” 17 U.S.C. § 102(a). Works that have not been fixed in a tangible medium of expression, works that have not been created by a human being, and works that are not eligible for copyright protection in the United States do not satisfy this requirement. Likewise, the copyright law does not protect works that do not constitute copyrightable subject matter or works that do not contain a sufficient amount of original authorship. The U.S. Copyright Office will register a visual art work that includes uncopyrightable material if the work as a whole is sufficiently creative and original. Some of the uncopyrightable elements that are commonly found in visual art works are discussed in Sections 906.1 through 906.8906.10 below. For a general discussion of uncopyrightable material, see Chapter 300, Section 313. 906.1 Common Geometric Shapes The Copyright Act does not protect common geometric shapes, either in two- dimensional or three-dimensional form. There are numerous common geometric shapes, including, without limitation, straight or curved lines, circles, ovals, spheres, triangles, cones, squares, squares, cubes, rectangles, diamonds, trapezoids, parallelograms, pentagons, hexagons, heptagons, octagons, and decagons. Generally, the U.S. Copyright Office will not register a work that merely consists of common geometric shapes unless the author’s use of those shapes results in a work that, as a whole, is sufficiently creative. Examples: • Geoffrey George creates a drawing depicting a standard pentagon with no additional design elements. The registration specialist

[aitoolswhitehattoolbox]

Lead of Technical Safety & LP COMP3 Shared Resources

Job descriptionWe have a current opportunity for a Lead of Technical Safety & LP COMP3 Shared Resources on a contract basis. The position will be based in Doha. For further information about this position please apply.-Bachelor’s Degree in Chemical Engineering, Safety Engineering or equivalent.-With minimum 10 years of experience in industrial safety and loss prevention in the oil and gas…

[iabba]

#music For Immediate Press Release: W.A.B. "THEE OMEN" Album Release #streamit

“THEE OMEN”. Artist: W.A.B. Album: THEE OMEN Track Listing 1. It’s Over2. Comp3. Je NeSauis Qua4. My Friend5. Hazed6. Eye Me7. Devils8. Punish Me 9. Suspended10. Temporary Listen to the full album below streaming and support by purchasing @SHOP NUHBEGINC MULTIMEDIA – “Tune Into The Highest Frequency”. Providing multi-media production for your needs. -30- pr@nuhbeg.com414.751.0371

[urbanairbmx]

@tiogabmx Class! Comp3's for Big Vineee 👊🏼👌🏼 #trailsvinny #vincenthunter #comp3 #tioga #urbanairbmx #trailslayer #hogtrails (at UrbanAir) https://www.instagram.com/p/CVQd9wLMGDI/?utm_medium=tumblr

[zeetee]

The first thing that i do after i woke up is drink 1 glass of water because my throat feels so dry and someone said to me that drinking water in the morning is good for our body. We must be healthy everyday for us to be safe from any sickness especially that there is this virus spreading. So for the safety of everybody we must practice washing our hands, be hygienic all the time. And for instance lets just refrain from going out if not necessary to avoid contact from the persons around. If buying groceries outside just dont forget to wear face mask.

Moreover, during this quarantine period I had so many bonding time with my family. We work together in constructing our fence and it is almost done. This pandemic doesnt just give us the terrible feeling but also gives us splendidly having more time with our family in the positive side. But we must not forget to pray to our beloved and merciful God for all those who are positive in this covid-19 that they may conquer and survive this virus. And for all of us that we may find peace in our hearts and help each other despite this pandemic we are going through.

#comp3

[cactustactical-blog]

$14.99

SAFARILAND SPEEDLOADER, COMP 3, DAN WESSON, S&W AND TAURUS

The Safariland Comp III speedloaders spring driven action provides the fastest, most positive reloading available.

Injection-molded

Designed for maximum concealment

Spring-driven to offer the fastest weapon reloading device

Large-knob frame offers maximum grip clearance

Available in Black only

Fits: Dan Wesson - 38, 357 S&W - Models 10, 12, 13, 14, 15, 19, 64, 65, 66, 67, 68 Taurus - 66, 669, 689

http://www.cactustactical.com/SAFARILAND-SPEEDLOADER-COMP-3-DAN-WESSON-SAMPW-AND-TAURUS_p_771.html

[seungmin-jpeg]

About Kim Youngwon

Name: Kim Youngwon / Paul Kim

Birthday: 2000

Height: 171cm (5′7″) 

Nationality: Korean-American

Facts:

He’s from Virginia, USA

He does/did a ton of busking 

No Make Up cover

Perfect cover

Just The Way You Are cover

I’m In Love cover

Stalker cover

Some of his hobbies are playing basketball and of course busking

His nicknames are puppy and black bean pavilion (빵원이)

His favorite foods are kimchi stew and steak

He can play the guitar 

At the moment his favorite song is Take Me Down by Troye Sivan

Contestant on Under Nineteen on Vocal Team

Intro Video

Audition

Love Me Right Fancam

Sherlock Fancam

Honestly just has the best vocals (Comp1, Comp2, Comp3)

Social Media:

Soundcloud

Instagram 

[dejufuniverse]

voor de fans....er komen later dit jaar gloednieuwe afleveringen aan...

[anpigs]

9 Free YouTube Video Converter Applications To Compress, Convert And Download Videos

What is youtube mp3 conconventer download free

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Best YouTube Video Converter Amp3 lications

There are tons of different YouTube video converters out there, and it can be hard to know which one to use. Here are some of the best free YouTube video converters:

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How to use the best YouTube video converters

If you want to compress, convert, or download videos from YouTube, there are a few different applications that you can use. Here are some of the best free YouTube video converters:

1. CCVideoConverter is one of the most popular YouTube video converters on the market. It is easy to use and has a wide range of options for compression, conversion, and downloading videos.

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What is youtube mp3 conconventer download free

If you have a YouTube account, you may be using the video sharing platform to upload and share videos with friends and family. You may also want to use YouTube to convert videos for offline viewing or for use on other devices.

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There are many different applications that you can use to compress, convert, and download videos. Some of the most popular applications include HqConverter, VideoPad, and MX Player.

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Free YouTube Video Converter Amp3 lications to Comp3 ress, Convert and Download Videos

Are you looking for a YouTube video converter that can compress, convert and download videos? If so, you're in luck! There are numerous free YouTube video converters available online.

Here are 5 of the best free YouTube video converters:

1. Convert YouTube to MP3 with YTD Video Converter This software is designed to convert YouTube videos into MP3 files. It includes a wide range of features, including options to adjust the quality of the converted files.

2. Download YouTube Videos with MP4 Downloader This free tool is designed to download YouTube videos in MP4 format. It includes a variety of features, including the ability to extract audio from videos.

3. Convert DVD Movies to MP4 with DVDVideoSoft MPEG-4 Converter This software is designed to convert DVDs into MP4 files. It includes a wide range of features, including the ability to customize the conversion process.

4. Convert Videos with VidMate 4 Free Video Converter Ultimate This software is designed to convert videos in a variety of formats. It includes features such as advanced encoding options and support for high-definition videos.

5. Compress and Convert Videos with WMP Video Conver

What are the benefits of using a video converter?

There are many benefits to using a video converter. Some of the benefits include:

-The ability to compress videos for faster streaming or download times. -The ability to convert videos between different formats. -The ability to download videos for offline viewing.

How to use the free YouTube video converters?

There are a number of free YouTube video converters available online. You can use these converters to compress, convert and download videos.

To use a YouTube video converter, first find the video you want to convert. Next, click the link to the converter website. On the website, you will be prompted to enter the URL of the video you want to convert. After entering the URL, you will be able to choose the compression format for the video. You can also choose to download the converted video.

[mexckk]

MEXC Global Will Merge the Shares of IOTX3S, COMP3S, KSM3S, TOMO3S & C983S Leveraged ETF Products

Since the net value of leveraged ETF products IOTX3S, COMP3S, KSM3S, TOMO3S & C983S are lower than 0.1 USDT respectively, they trigger the Share Merging Mechanism. As such, MEXC has merged the shares of IOTX3S, COMP3S, KSM3S, TOMO3S & C983S at 2021-11-04 05:00 AM (UTC).

The 10 share of IOTX3S, COMP3S, KSM3S, TOMO3S & C983S will be merged into 1 share respectively. Consequently, the net value per share of IOTX3S, COMP3S, KSM3S, TOMO3S & C983S will be up 10 times, while user's holding amount will be down to 1/10. In this connection, user's total asset will stay the same after the merging.

[aitoolswhitehattoolbox]

Process Specialist COMP3

Job descriptionWe have a current opportunity for a Process Specialist COMP3 on a contract basis. The position will be based in Doha. For further information about this position please apply.COMP3 project is part of a large-scale offshore Compression Development Program . This major project consists of new offshore facilities that comprise of five new riser platforms, one wellhead platform, 110km…

[urbanairbmx]

The comp3 stoke is v high! In stock now... urbanair.co.uk . . . #urbanairbmx #urbanaircrew #traillife #bmx #tiogabmx #comp3 #compIII #oldschool #midschool #stayfast https://www.instagram.com/p/BxkJkTXHrGk/?igshid=167mvto89ki4w

[jeffginnc]

Data Analysis Tools - week 2

LIBNAME mydata "/courses/d1406ae5ba27fe300 " access=readonly;

DATA new; set mydata.marscrater_pds;

attrib    Lat length=$12

                            Szz length=$8

                            NL  length=$3;

LABEL    Lat="Latitude (in degrees)"

                            Number_Layers="# Layers"

                            Szz="Crater Size (in km)"

                            NL="Num Layers";

If Latitude_Circle_Image <=-60 then Lat = "A <-60";

ELSE If Latitude_Circle_Image >-60 and Latitude_Circle_Image <=-30 then Lat = "B >-60 <=-30";

ELSE If Latitude_Circle_Image >-30 and Latitude_Circle_Image <=0 then Lat = "C >-30 <=0";

ELSE If Latitude_Circle_Image >0 and Latitude_Circle_Image <=30 then Lat = "D >0 <=30";

ELSE If Latitude_Circle_Image >30 and Latitude_Circle_Image <=60 then Lat = "E >30 <=60";

ELSE IF Latitude_Circle_Image >60 then Lat = "F >60";

If Diam_Circle_Image <=50 then Szz = "<=100";

ELSE IF Diam_Circle_Image > 50 and Diam_Circle_Image <=100 then Szz = ">100-200";

ELSE IF Diam_Circle_Image > 100 and Diam_Circle_Image <=300 then Szz = ">200-300";

ELSE IF Diam_Circle_Image > 150 and Diam_Circle_Image <=400 then Szz = ">300-400";

ELSE IF Diam_Circle_Image > 400 then Szz = ">400 km";

If Number_Layers <= 0 then NL = "0";

ELSE IF Number_Layers > 0 then NL = ">=1";

PROC SORT; by crater_id;

RUN;

DATA COMP1; SET NEW;

IF Szz = "<=100" OR Szz = ">100-200";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP2; SET NEW;

IF Szz = "<=100" OR Szz = ">200-300";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP3; SET NEW;

IF Szz = "<=100" OR Szz = ">300-400";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP4; SET NEW;

IF Szz = "<=100" OR Szz = ">400 km";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP5; SET NEW;

IF Szz = ">100-200" OR Szz = ">200-300";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP6; SET NEW;

IF Szz = ">100-200" OR Szz = ">300-400";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP7; SET NEW;

IF Szz = ">100-200" OR Szz = ">400 km";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP8; SET NEW;

IF Szz = ">200-300" OR Szz = ">300-400";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP9; SET NEW;

IF Szz = ">200-300" OR Szz = ">400 km";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

DATA COMP10; SET NEW;

IF Szz = ">300-400" OR Szz = ">400 km";

PROC SORT; BY CRATER_ID;

PROC FREQ; TABLES NL*Szz/CHISQ;

RUN;

For this assignment I divided the number of craters into 2 categories, o and >=1  just to provide a 2 category column. The crater size data had already been broken down into 5 columns. As you can see, the initial p value of .0001 shows a relationship between number of layers and crater size. As I performed the ad hoc paired testing, the p value must be below .005 for 10 comparisons to show the null hypothesis is false. I have attached the 2 comparisons (<100 to 100-200, and <100 to 200-300 that met that criteria. I attached one other (<100 to 300-400) that had a higher p value. All remaining comparisons had a p value higher than .005. This shows that the data for the most numerous small craters show there is a relationship between size and number of layers.

[zaworm]

Data Analysis Tools Week 2 Running a Chi-Square Test of Independence

1.Background

I have decided to look at Mars craters and ask the following question:

A. Are shallower depth craters associated with locations near the North and South poles of Mars?” The dataset was limited to craters that had a diameter of 100 km or less and a crater depth that was greater than 0 km.

I divided up the latitude of the planet into 5 bins based on the latitude degree increments/bins to see if there was a significant difference between the latitude of these groups and the depth of the crater.

I classified the crater as either being shallow or deep based on the crater depth.  The cutoff was chosen to be 180m.

2.Notes about the Results

2.1 The crater count based on the latitude is shown below:

2.2 The crater classification is based on the plot below, where the majority of the craters are classified as deep.

2.3 The overall mean deep craters are shown in the plot below.  There seems to be a correlation between latitude and depth of the crater, with a higher concentration of deep craters near the equator of the planet.  Lets perform a Chi-squared analysis to further investigate.

The Chi Squared test was run in Python and the full code is below in section 3.  The full results are shown in section 4.

For example the Chi squared test that was coded was written as follows:

The output showed that the p value was under 0.05 and the value was 0.0 indicating that a Post Hoc test was necessary.  The p value showed that the alternate hypothesis is to be accepted and there is a correlation between deep craters and the latitude.

Response Variable Categorical 2 Levels: Crater Depth (shallow or deep)

************************************************ LAT_LOCATION_GROUP  -90_-50  -50_-20  -20_20  20_50  50_90 IS_CRATER_DEEP                                             SHALLOW                5507     6847    8449   5501   2821 DEEP                   4402    14528   20948   6966    551 LAT_LOCATION_GROUP   -90_-50   -50_-20   -20_20     20_50     50_90 IS_CRATER_DEEP                                                     SHALLOW             0.555757  0.320327  0.28741  0.441245  0.836595 DEEP                0.444243  0.679673  0.71259  0.558755  0.163405 chi-square value, p value, expected counts (5870.45780474349, 0.0, 4, array([[ 3771.55808939,  8135.74065604, 11189.06985102,  4745.18263199,        1283.44877156],      [ 6137.44191061, 13239.25934396, 18207.93014898,  7721.81736801,        2088.55122844]]))

An example Post Hoc test was coded as follows:

The output showed that the p value was 0.0 indicating the was under the Bonferroni adjustment and the null hypothesis was rejected indicating there is a correlation between latitude groups (-90 to -50 and -50 to -20):

************************************************ COMP1-10        -50_-20  -90_-50 IS_CRATER_DEEP                   SHALLOW            6847     5507 DEEP              14528     4402 COMP1-10         -50_-20   -90_-50 IS_CRATER_DEEP                     SHALLOW         0.320327  0.555757 DEEP            0.679673  0.444243 chi-square value, p value, expected counts (1569.4618848788969, 0.0, 1, array([[ 8440.95224396,  3913.04775604],     [12934.04775604,  5995.95224396]]))

A table summarizing the results of the 10 Chi Square results are shown below.  It shows that we can not accept the null hypothesis and there is a correlation between latitude and crater depth.  There is a stronger correlation when looking at the areas close to the poles vs the equator.

3.Raw Python Code:

The raw Python code is shown in the photos below.  I decided to use screenshots for easier readability as it includes syntax highlighting.

4.Code Output:

Below is the raw output from the code.  The interpretation and comments on the results are shown above in Section 2.

Mars Crater Study

Data Analysis Tools

Running a Chi-Square Test of Independence

-------------------------------------------

Info about this dataset

Total number of rows in the dataset: 384343

Total number of columns in the dataset: 10 Info about this subset and narrowed down  dataset

Total number of rows in the dataset: 76520

Total number of columns in the dataset: 5

-----------------------   LATTITUDE BIN SECTION   -----------------------------------------

Latitude bin counts: -90_-50     9909 -50_-20    21375 -20_20     29397 20_50      12467 50_90       3372 Name: LAT_LOCATION_GROUP, dtype: int64

-----------------------   DEPTH MANAGEMENT SECTION  ----------------------------------------- Here are the counts for deep and shallow craters craters:

DEEP       47395 SHALLOW    29125 Name: IS_CRATER_DEEP, dtype: int64

---------- Categorical Eplanatory Variable: Latitude group

Response Variable Categorical 2 Levels: Crater Depth (shallow or deep)

************************************************ LAT_LOCATION_GROUP  -90_-50  -50_-20  -20_20  20_50  50_90 IS_CRATER_DEEP                                             SHALLOW                5507     6847    8449   5501   2821 DEEP                   4402    14528   20948   6966    551 LAT_LOCATION_GROUP   -90_-50   -50_-20   -20_20     20_50     50_90 IS_CRATER_DEEP                                                     SHALLOW             0.555757  0.320327  0.28741  0.441245  0.836595 DEEP                0.444243  0.679673  0.71259  0.558755  0.163405 chi-square value, p value, expected counts (5870.45780474349, 0.0, 4, array([[ 3771.55808939,  8135.74065604, 11189.06985102,  4745.18263199,         1283.44877156],       [ 6137.44191061, 13239.25934396, 18207.93014898,  7721.81736801,         2088.55122844]]))

************************************************ COMP1-10        -50_-20  -90_-50 IS_CRATER_DEEP                   SHALLOW            6847     5507 DEEP              14528     4402 COMP1-10         -50_-20   -90_-50 IS_CRATER_DEEP                     SHALLOW         0.320327  0.555757 DEEP            0.679673  0.444243 chi-square value, p value, expected counts (1569.4618848788969, 0.0, 1, array([[ 8440.95224396,  3913.04775604],       [12934.04775604,  5995.95224396]]))

************************************************ COMP2-10        -20_-20  -90_-50 IS_CRATER_DEEP                   SHALLOW            8449     5507 DEEP              20948     4402 COMP2-10        -20_-20   -90_-50 IS_CRATER_DEEP                   SHALLOW         0.28741  0.555757 DEEP            0.71259  0.444243 chi-square value, p value, expected counts (2329.314932557565, 0.0, 1, array([[10437.70752557,  3518.29247443],       [18959.29247443,  6390.70752557]]))

************************************************ COMP3-10        -90_-50  20_50 IS_CRATER_DEEP                 SHALLOW            5507   5501 DEEP               4402   6966 COMP3-10         -90_-50     20_50 IS_CRATER_DEEP                     SHALLOW         0.555757  0.441245 DEEP            0.444243  0.558755 chi-square value, p value, expected counts (289.20138905047946, 7.422790875630638e-65, 1, array([[4874.78870218, 6133.21129782],       [5034.21129782, 6333.78870218]]))

************************************************ COMP4-10        -90_-50  50_90 IS_CRATER_DEEP                 SHALLOW            5507   2821 DEEP               4402    551 COMP4-10         -90_-50     50_90 IS_CRATER_DEEP                     SHALLOW         0.555757  0.836595 DEEP            0.444243  0.163405 chi-square value, p value, expected counts (847.2982157758986, 2.811519087431208e-186, 1, array([[6213.54958211, 2114.45041789],       [3695.45041789, 1257.54958211]]))

************************************************ COMP5-10        -20_20  -50_-20 IS_CRATER_DEEP                 SHALLOW           8449     6847 DEEP             20948    14528 COMP5-10         -20_20   -50_-20 IS_CRATER_DEEP                   SHALLOW         0.28741  0.320327 DEEP            0.71259  0.679673 chi-square value, p value, expected counts (63.54773843933685, 1.5652720877138506e-15, 1, array([[ 8856.38761522,  6439.61238478],       [20540.61238478, 14935.38761522]]))

************************************************ COMP6-10        -50_-20  20_50 IS_CRATER_DEEP                 SHALLOW            6847   5501 DEEP              14528   6966 COMP6-10         -50_-20     20_50 IS_CRATER_DEEP                     SHALLOW         0.320327  0.441245 DEEP            0.679673  0.558755 chi-square value, p value, expected counts (496.2855186756665, 6.111846388145869e-110, 1, array([[ 7799.14012174,  4548.85987826],       [13575.85987826,  7918.14012174]]))

************************************************ COMP7-10        -50_-20  50_90 IS_CRATER_DEEP                 SHALLOW            6847   2821 DEEP              14528    551 COMP7-10         -50_-20     50_90 IS_CRATER_DEEP                     SHALLOW         0.320327  0.836595 DEEP            0.679673  0.163405 chi-square value, p value, expected counts (3258.881845816943, 0.0, 1, array([[ 8350.64856346,  1317.35143654],       [13024.35143654,  2054.64856346]]))

************************************************ COMP8-10        -20_20  20_50 IS_CRATER_DEEP               SHALLOW           8449   5501 DEEP             20948   6966 COMP8-10         -20_20     20_50 IS_CRATER_DEEP                   SHALLOW         0.28741  0.441245 DEEP            0.71259  0.558755 chi-square value, p value, expected counts (931.7404706337541, 1.2358200405213006e-204, 1, array([[ 9795.72305561,  4154.27694439],       [19601.27694439,  8312.72305561]]))

************************************************ COMP9-10        -20_20  50_90 IS_CRATER_DEEP               SHALLOW           8449   2821 DEEP             20948    551 COMP9-10         -20_20     50_90 IS_CRATER_DEEP                   SHALLOW         0.28741  0.836595 DEEP            0.71259  0.163405 chi-square value, p value, expected counts (4040.9902387527836, 0.0, 1, array([[10110.29295981,  1159.70704019],       [19286.70704019,  2212.29295981]]))

************************************************ COMP10-10       20_50  50_90 IS_CRATER_DEEP               SHALLOW          5501   2821 DEEP             6966    551 COMP10-10          20_50     50_90 IS_CRATER_DEEP                     SHALLOW         0.441245  0.836595 DEEP            0.558755  0.163405 chi-square value, p value, expected counts (1662.095048322109, 0.0, 1, array([[6550.31087821, 1771.68912179],       [5916.68912179, 1600.31087821]]))