#codebook

[newsboys-of-1899]

Excerpts from the only known surviving copy of the code book used for communications between Joseph Pulitzer and his staff at the New York World. The book is held at the Columbia University Rare Books Library.

Source

[amalgamortuum]

Code and cipher tables of Mary, Queen of Scots, circa 1596. A prime example of a classic nomenclator, this system lists names, words, and common letter combinations alongside their equivalent code symbol(s), in addition to a supplementary cipher alphabet to cover any words or names not listed in the code section. Nomenclators were employed by European royalty to conceal diplomatic as well as personal correspondences during the 15th century onward. They saw widespread use until the 1850s when they were superseded by the invention of the telegraph and Morse code.

The box in the upper left corner of the table contains a cipher alphabet where each plaintext letter has four symbol equivalents. The top half of the upper right box contains substitution symbols for common digraphs (including the letter W, which was historically a digraph), each of which has two equivalent symbols; the lower half lists signs to represent common English word endings.

Below this is a list of 31 null characters — these are meaningless signs intended to confuse decryption attempts — followed by a list of 16 symbols, 12 of which represent the months of the year, and four more representing the words “Ponds,” “Angels,” “Crownes [sic],” and “Ducats.”

The next line details the use of four specialized signs:

The first sign (resembling a cursive digit 1 or lowercase /) is used to represent a doubling of any preceding character (used to double a letter, for example)

The second sign (a small square) is used as a full stop or period

The third sign (resembling a cursive capital V) is used as parentheses

The fourth sign (resembling a lowercase j without the dot) makes any preceding character null

The rest of the table lists symbol equivalents of the names of key individuals and locations as well as common words and short phrases. The first three columns encrypt the names of individuals and places (many titles are abbreviated, such as k. for king, Q. for queen, E. for earl, and lo. for lord). The fourth through seventh columns list encryptions for common words as well as a few more names.

[dataanalysiswithpriya]

                  CODEBOOK – MARS CRATER DATASET

Name: PRIYA HEGDE

Course Name: Data Analysis and Interpretation                                                                                                                                  

Data Set Overview:

The Mars Global Crater Database used in this study is taken from Robbins (2011). According to this dataset, Mars contains 378,540 craters with diameters ≥ 1 km

The purpose of this study is to analyse the crater size, depth, morphology, and the surface history of the planet. The database includes a unique identification number for every crater entry.

Variables:

Variable Name

Types of variables

Description

Why included

CRATER_ID

String

Unique crater identifier

Track individual craters

LATITUDE_CIRCLE_IMAGE

Decimal degrees (°N)

Latitude of crater centre (circle-fit)

Map location and geospatial patterns

LONGITUDE_CIRCLE_IMAGE

Decimal degrees (°E)

Longitude of crater centre (circle-fit)

Map location and spatial clustering

DIAM_CIRCLE_IMAGE

Kilometres (km)

Crater diameter from circle-fit

Main research variable (crater size)

DEPTH_RIMFLOOR_TOPOG

Kilometres (km)

Rim-to-floor depth (average of selected points)

Second main variable (crater depth/erosion indicator)

NUMBER_LAYERS

Integer (0,1, 2...)

Maximum number of ejecta layers identified

Indicator of ejecta complexity / impact energy

MORPHOLOGY_EJECTA_1

Categorical (e.g., SLERC, DLERS)

Primary ejecta morphology (inner-most)

Understand ejecta type vs size

MORPHOLOGY_EJECTA_2

Categorical (HuSL, SmSL, etc.)

Morphology of ejecta layers

Secondary morphology descriptor

MORPHOLOGY_EJECTA_3

Categorical

Outer ejecta texture/shape (butterfly, pincushion)

Special ejecta patterns, unusual impacts

Research Question & Hypothesis:

 Research question:

Is crater diameter on Mars associated with crater depth?

Is crater diameter on Mars associated ejecta complexity?

 Hypothesis: Larger craters (higher DIAM_CIRCLE_IMAGE) will have greater depth (DEPTH_RIMFLOOR_TOPOG) and more ejecta layers (NUMBER_LAYERS) and more complex ejecta morphology (MORPHOLOGY_EJECTA_1).

References Identified:

Robbins, S. J. (2011). Planetary Surface Properties from a Global Martian Crater Database.

Garvin, J. (2003). Global Geometric Properties of Mars Impact Craters.

Melosh, H. (1989). Impact Cratering: A Geologic Process.

Watters, T. (2015). Impact Craters and Surface Ages on Mars.

KEY POINTS:

Robbins (2011) developed a comprehensive global database of Martian craters, including detailed measurements of crater diameter, depth, and ejecta characteristics.

Garvin (2003) and Watters (2015) demonstrated a positive correlation between crater diameter and depth, although depth variability arises from erosional and depositional processes.

Melosh (1989) provided the theoretical framework linking impact energy to crater size and ejecta morphology complexity.

Collectively, these studies support the hypothesis that larger craters exhibit greater depth and more complex ejecta structures.

[mariakosinsights]

Codebook Week 1

[xmunet-blog]

Drug Abuse Research

I am interested in people health. After looking through the codebook for the NESARC study, I have decided that I am particularly interested in Drug Abuse. 

I will choose the dataset of NESARC surely. The original research topic is drug abuse.

I will pickup below two sections in my personal codebook

SECTION 3C: DRUG ABUSE/DEPENDENCE (MEDICINE EXPERIENCES) SECTION 3E: FAMILY HISTORY (II) OF DRUG ABUSE

While drug abuse is a good starting point, I need to determine what it is about drug abuse that I am interested in. As I know , one of friends that I have known through the years that hooked on drugs heavily. She is tend to take drugs even it is not necessary and suggest others to do so even the effect is unclear. Meanwhile her mother show same behavior. It seems that the behavior is related with family aggregation.

I decide that I am most interested in exploring the association between family history and drug abuse. 

So the 2nd research topic is to find out the association between family aggregation and age of drug abuse.

The variables I used:

Age of drug abuse ----

1378-1379 S3CD1Q13A AGE AT ONSET OF SEDATIVE ABUSE 1380-1381 S3CD2Q13A AGE AT ONSET OF TRANQUILIZER ABUSE

1382-1383 S3CD3Q13A AGE AT ONSET OF OPIOID ABUSE 1384-1385 S3CD4Q13A AGE AT ONSET OF AMPHETAMINE ABUSE 1386-1387 S3CD5Q13A AGE AT ONSET OF CANNABIS ABUSE 1388-1389 S3CD6Q13A AGE AT ONSET OF COCAINE ABUSE 1390-1391 S3CD7Q13A AGE AT ONSET OF HALLUCINOGEN ABUSE 1392-1393 S3CD8Q13A AGE AT ONSET OF INHALANT ABUSE 1394-1395 S3CD9Q13A AGE AT ONSET OF HEROIN ABUSE

1396-1397 S3CD10Q13A AGE AT ONSET OF OTHER DRUG ABUSE

Family aggregation on problems with drugs -----

2429-2429 S3EQ1 BLOOD/NATURAL FATHER EVER HAD PROBLEMS WITH DRUGS

2430-2430 S3EQ2 BLOOD/NATURAL MOTHER EVER HAD PROBLEMS WITH DRUGS

2433-2433 S3EQ3C ANY FULL BROTHERS EVER HAD PROBLEMS WITH DRUGS

2436-2436 S3EQ4C ANY FULL SISTERS EVER HAD PROBLEMS WITH DRUGS

Literatural review: I am checking relevent information and stuies in ” https://scholar.google.com” by searching item ”family histoy of drug abuse”.

reference: “Family History of Alcohol and Drug Abuse, Childhood Trauma, and Age of First Drug Injection ″ by  Chris Taplin,Sahoo Saddichha,Kathy Li &Michael R. Krausz https://www.tandfonline.com/doi/full/10.3109/10826084.2014.901383

″ Familial Transmission of Substance Use Disorders ″ by  Kathleen R. Merikangas, PhD; Marilyn Stolar, MA; Denise E. Stevens, PhD; et al https://jamanetwork.com/journals/jamapsychiatry/fullarticle/204407

After literatural review, I found there is increasing evidence that substance use disorders are familial and that genetic factors explain a substantial degree of their familial aggregation.According to the article ” Familial Transmission of Substance Use Disorders” , it presnts that elevation in risk of this magnitude places a family history of drug disorder as one of the most potent risk factors for the development of drug disorders.

Based on above information , I am considering research the topic with the variables (Father, monther, brothers, sisters have drug problem and age of drug abuse) to approve my hypotheis – the association between drug abuse and family aggregation.

[bettylouiseme]

#THE CODE BOOK MURDERS by Leslie Nagel

PEACE

The 4th edition in Oakwood mysteries open with a disaster that puts into the action and immediately catches your attention. Charley Carpenter finds a backpack that contains a journal that is in code and Oakwood Book Club in action. The notebook decoded shows a link to a famous murder, Regan Fletcher. Her boyfriend was convicted of her murder. Who really kill Ryan? There are more than…

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[selangorc]

- CODEBOOK

SECOND STEP

The second step after preparing the coding strategy is preparing the codebook.

This step is done by converting each data from each variables into an IBM SPSS-understandable format.

To prepare the codebook, click Analyze > Reports > Codebook.

Then, the dialog box below will be displayed

* Select and move all the variables into the Codebook Variables by highlighting the variables and clicking the arrow button between the two boxes. 

- Next, click on the Output tab and untick all of the Variable Information except for Label, Value labels and Missing values

- Following that, click the Statistics tab and select all the boxes > OK 

- Afterwards, the result of the Codebook will be displayed in the SPSS Output as shown below:

[gellobot]

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