Creating a Coding Book in IBM SPSS StatisticsThiyagu K
The Codebook is a document containing information about each of the variables in your dataset, such as:
The name assigned to the variable
What the variable represents (i.e., its label)
How the variable was measured (e.g. nominal, ordinal, scale)
How the variable was actually recorded in the raw data (i.e. numeric, string; how many characters wide it is; how many decimal places it has)
For scale variables: The variable's units of measurement
For categorical variables: If coded numerically, the numeric codes and what they represent
This presentation explains the procedure of creating a codebook in IBM SPSS Statistics.
Intro to SQL by Google's Software EngineerProduct School
Intro to SQL, by Roman Polonsky, software engineer on Google's Global Tools Team.
SQL provides powerful but reasonably simple tools for data analysis and handling. This workshop will take absolute beginners through the basics of SQL. You’ll learn SQL queries needed to collect data from a database, even if it lives in different places and analyze it to find the answers you’re looking for.
Take away from this workshop the understanding of essential SQL skills that allow developers to write queries against single and multiple tables, manipulate data in tables, and create database objects.
Creating a Coding Book in IBM SPSS StatisticsThiyagu K
The Codebook is a document containing information about each of the variables in your dataset, such as:
The name assigned to the variable
What the variable represents (i.e., its label)
How the variable was measured (e.g. nominal, ordinal, scale)
How the variable was actually recorded in the raw data (i.e. numeric, string; how many characters wide it is; how many decimal places it has)
For scale variables: The variable's units of measurement
For categorical variables: If coded numerically, the numeric codes and what they represent
This presentation explains the procedure of creating a codebook in IBM SPSS Statistics.
Intro to SQL by Google's Software EngineerProduct School
Intro to SQL, by Roman Polonsky, software engineer on Google's Global Tools Team.
SQL provides powerful but reasonably simple tools for data analysis and handling. This workshop will take absolute beginners through the basics of SQL. You’ll learn SQL queries needed to collect data from a database, even if it lives in different places and analyze it to find the answers you’re looking for.
Take away from this workshop the understanding of essential SQL skills that allow developers to write queries against single and multiple tables, manipulate data in tables, and create database objects.
This presentation explains the different options involves in the variable view interface of IBM SPSS Statistics. This slide also describes the different types of data and their meaning in a clear manner.
At the end of this Lesson (Part 1) the students should be able to know the following
Introduction
Data Entry
Variable and Value Label
Entering Data
File management
Descriptive statistics
Editing and modifying the data
Elementary Data Analysis with MS Excel_Day-4Redwan Ferdous
This event took place on 12th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-4, the MS Excel Data Tab, View and Review tab as well as Developer Tab of Horizontal top ribbon was discussed. As well as different Quick analysis tools, What-if Analysis, Data Table, Scenario Manager, Pareto Chart was also discussed.
From this power point you can get the details about Advanced Filter, Use of Macros with Advanced Filter, Data Validation, Creation of data validation Drop-Down List, Handling of External Data, Goal Seek, What-if analysis,
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
This presentation explains the different options involves in the variable view interface of IBM SPSS Statistics. This slide also describes the different types of data and their meaning in a clear manner.
At the end of this Lesson (Part 1) the students should be able to know the following
Introduction
Data Entry
Variable and Value Label
Entering Data
File management
Descriptive statistics
Editing and modifying the data
Elementary Data Analysis with MS Excel_Day-4Redwan Ferdous
This event took place on 12th September 2020. This was arranged by EMK Center (Makerlab). The title was 'Elementary Data Analysis with MS Excel', where very basic data analysis with MS excel was discussed.
In Day-4, the MS Excel Data Tab, View and Review tab as well as Developer Tab of Horizontal top ribbon was discussed. As well as different Quick analysis tools, What-if Analysis, Data Table, Scenario Manager, Pareto Chart was also discussed.
From this power point you can get the details about Advanced Filter, Use of Macros with Advanced Filter, Data Validation, Creation of data validation Drop-Down List, Handling of External Data, Goal Seek, What-if analysis,
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
Structured Query Language (SQL) _ Edu4Sure Training.pptxEdu4Sure
The PPT content is for reference only. The training will be hands-on & practical.
Training: SQL (Structured Query Language)
For any Training & Certificate, please email us at partner@edu4sure.com
or Call/ whatsapp at +91-9555115533
Or visit www.testformula.com (Our LMS to access Self-paced vidoes) or visit www.edu4sure.com
Database Slides for DIT students
Slide 3: A Database is defined as a structured set of data. So, in SQL the very first step to store the data in a well-structured manner is to create a database. The CREATE DATABASE statement is used to create a new database in SQL.
Slide 4: Example CREATE DATABASE my_database ;
Slide 5: *create a table in SQL*
The CREATE TABLE statement is used to create a table in SQL.
A table comprises of rows and columns
So, while creating tables we have to provide all the information to SQL about the names of the columns, type of data to be stored in columns, size of the data etc.
Syntax:
CREATE TABLE table_name ( column1 data_type(size), column2 data_type(size),
column3 data_type(size), .... );
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
14. Rationale to study SQL
• Learning SQL to Query Biological Databases
• Are you getting too much data, or missing crucial
data when querying via a Web interface? Many
biological databases can be queried directly via
SQL, thus bypassing the limitations of the
database's interface. SQL is at the heart of
biological databases as diverse as Ensembl,
ArrayExpress and the Mouse Genome Database.
• Focus on understanding relational databases by
studying a repository of biological data and learn
how to query it using SQL.
15. SQL consists of only 4 statements, sometimes
referred to as CRUD:
–Create - INSERT - to store new data
–Read - SELECT - to retrieve data
–Update - UPDATE - to change or modify
data.
–Delete - DELETE - delete or remove data
Structured Query Language
16. Definitions
Definitions
• Database: Collection of tables
• Table
– Collection of records that share a common
fundamental characteristic
• E.g., patients and locations can each be stored in
their own table
• Record
– Basic unit of information in a relation
information
– A record is composed of fields
– E.g., 1 record per person
• Query
– Set of instructions to a database “engine” to
retrieve, sort and format returning data.
• “find me all patients in my database”
17. Table Characteristics
• Two-dimensional structure with rows and
columns
• Rows (tuples) represent single entity
• Columns represent attributes
• Row/column intersection represents single value
• Tables must have an attribute to uniquely identify
each row
• Column values all have same data format
• Each column has range of values called attribute
domain
• Order of the rows and columns is immaterial to
the DBMS
18. Numeric Data Types
MySQL uses all the standard ANSI SQL numeric data types, so if you're coming to MySQL from a different
database system, these definitions will look familiar to you. The following list shows the common numeric data
types and their descriptions:
INT - A normal-sized integer that can be signed or unsigned. If signed, the allowable range is from -2147483648 to
2147483647. If unsigned, the allowable range is from 0 to 4294967295. You can specify a width of up to 11 digits.
TINYINT - A very small integer that can be signed or unsigned. If signed, the allowable range is from -128 to 127.
If unsigned, the allowable range is from 0 to 255. You can specify a width of up to 4 digits.
SMALLINT - A small integer that can be signed or unsigned. If signed, the allowable range is from -32768 to
32767. If unsigned, the allowable range is from 0 to 65535. You can specify a width of up to 5 digits.
MEDIUMINT - A medium-sized integer that can be signed or unsigned. If signed, the allowable range is from -
8388608 to 8388607. If unsigned, the allowable range is from 0 to 16777215. You can specify a width of up to 9
digits.
BIGINT - A large integer that can be signed or unsigned. If signed, the allowable range is from -
9223372036854775808 to 9223372036854775807. If unsigned, the allowable range is from 0 to
18446744073709551615. You can specify a width of up to 20 digits.
FLOAT(M,D) - A floating-point number that cannot be unsigned. You can define the display length (M) and the
number of decimals (D). This is not required and will default to 10,2, where 2 is the number of decimals and 10 is
the total number of digits (including decimals). Decimal precision can go to 24 places for a FLOAT.
DOUBLE(M,D) - A double precision floating-point number that cannot be unsigned. You can define the display
length (M) and the number of decimals (D). This is not required and will default to 16,4, where 4 is the number of
decimals. Decimal precision can go to 53 places for a DOUBLE. REAL is a synonym for DOUBLE.
DECIMAL(M,D) - An unpacked floating-point number that cannot be unsigned. In unpacked decimals, each
decimal corresponds to one byte. Defining the display length (M) and the number of decimals (D) is required.
NUMERIC is a synonym for DECIMAL.
19. String Data Type
• Although numeric and date types are fun, most data you'll store will be in string format. This list describes
the common string datatypes in MySQL.
• CHAR(M) - A fixed-length string between 1 and 255 characters in length (for example CHAR(5)), right-
padded with spaces to the specified length when stored. Defining a length is not required, but the default
is 1.
• VARCHAR(M) - A variable-length string between 1 and 255 characters in length; for example
VARCHAR(25). You must define a length when creating a VARCHAR field.
• BLOB or TEXT - A field with a maximum length of 65535 characters. BLOBs are "Binary Large Objects"
and are used to store large amounts of binary data, such as images or other types of files. Fields defined
as TEXT also hold large amounts of data; the difference between the two is that sorts and comparisons
on stored data are case sensitive on BLOBs and are not case sensitive in TEXT fields. You do not specify
a length with BLOB or TEXT.
• TINYBLOB or TINYTEXT - A BLOB or TEXT column with a maximum length of 255 characters. You do
not specify a length with TINYBLOB or TINYTEXT.
• MEDIUMBLOB or MEDIUMTEXT - A BLOB or TEXT column with a maximum length of 16777215
characters. You do not specify a length with MEDIUMBLOB or MEDIUMTEXT.
• LONGBLOB or LONGTEXT - A BLOB or TEXT column with a maximum length of 4294967295
characters. You do not specify a length with LONGBLOB or LONGTEXT.
• ENUM - An enumeration, which is a fancy term for list. When defining an ENUM, you are creating a list of
items from which the value must be selected (or it can be NULL). For example, if you wanted your field to
contain "A" or "B" or "C", you would define your ENUM as ENUM ('A', 'B', 'C') and only those values (or
NULL) could ever populate that field.
20. Built-in Data Types in SQL
• date: Dates, containing a (4 digit) year, month and
date
– Example: date ‘2005-7-27’
• time: Time of day, in hours, minutes and seconds.
– Example: time ‘09:00:30’ time ‘09:00:30.75’
• timestamp: date plus time of day
– Example: timestamp ‘2005-7-27 09:00:30.75’
• interval: period of time
– Example: interval ‘1’ day
– Subtracting a date/time/timestamp value from another gives
an interval value
– Interval values can be added to date/time/timestamp values
21. Build-in Data Types in SQL (Cont.)
• Can extract values of individual fields from
date/time/timestamp
– Example: extract (year from r.starttime)
• Can cast string types to
date/time/timestamp
– Example: cast <string-valued-expression>
as date
– Example: cast <string-valued-expression>
as time
22. User-Defined Types
• create type construct in SQL creates user-defined
type
create type Dollars as numeric (12,2) final
• create domain construct in SQL-92 creates user-
defined domain types
create domain person_name char(20) not null
• Types and domains are similar. Domains can have
constraints, such as not null, specified on them.
23. Large-Object Types
• Large objects (photos, videos, CAD files, etc.)
are stored as a large object:
– blob: binary large object -- object is a large
collection of uninterpreted binary data (whose
interpretation is left to an application outside of
the database system)
– clob: character large object -- object is a large
collection of character data
– When a query returns a large object, a pointer is
returned rather than the large object itself.
24. Creating a Table
• To create a table, use the CREATE TABLE command:
mysql> CREATE TABLE pet (
-> name VARCHAR(20),
-> owner VARCHAR(20),
-> species VARCHAR(20),
-> sex CHAR(1),
-> birth DATE, death DATE);
Query OK, 0 rows affected (0.04 sec)
25. Keys
• One or more attributes that
determine other attributes
– Key attribute
– Composite key
• Full functional dependence
• Entity integrity
– Uniqueness
– No ‘null’ value in key
28. Keys (con’t.)
• Primary key
– Candidate key to uniquely identify all other
attributes in a given row
• Foreign key
– Values must match primary key in another
table
29. Integrity Rules
• Entity integrity
– Ensures all entities are unique
– Each entity has unique key
• Referential integrity
– Foreign key must have null value or match
primary key values
– Makes it impossible to delete row whose
primary key has mandatory matching foreign
key values in another table
30. Integrity Constraints
• Integrity constraints guard against
accidental damage to the database, by
ensuring that authorized changes to the
database do not result in a loss of data
consistency.
– A checking account must have a balance
greater than $10,000.00
– A salary of a bank employee must be at
least $4.00 an hour
– A customer must have a (non-null) phone
number
31. Referential Integrity
• Ensures that a value that appears in one relation for a given set of
attributes also appears for a certain set of attributes in another
relation.
– Example: If “Perryridge” is a branch name appearing in one of the
tuples in the account relation, then there exists a tuple in the
branch relation for branch “Perryridge”.
• Primary and candidate keys and foreign keys can be specified as part
of the SQL create table statement:
– The primary key clause lists attributes that comprise the primary
key.
– The unique key clause lists attributes that comprise a candidate
key.
– The foreign key clause lists the attributes that comprise the
foreign key and the name of the relation referenced by the foreign
key. By default, a foreign key references the primary key attributes
of the referenced table.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42. Install BIOSQL locally
• Get latest version of mysql (MAMP,
mariaDB)
• Download biosqldb-mysql.sql
• Remove type=innodb
• Launch database server
• Connect using toad (port 8889)
• Create database biosql;
• Set as active database
• Use worksheet to execute biosqldb-
mysql.sql
44. How ODBC Works?
• ODBC inserts a middle layer called a Client
Driver
• Purpose of the Client Driver is to translate the
applications queries into commands that the
DBMS understands
45. Other Parts of the Architecture
• Application – calls functions defined in the
ODBC API to access a data source
• Driver Manager – implements the ODBC API
and provides information to the application
• Database – contains all the data
46. Setting Up a Data Source in Windows
• A data source is just a database that ODBC
connects to
• This allows the person to change database
types without any changes to the program
• Step 1. Get a database.
– Using access for this example because it’s on this
computer
48. Conclusion
• Advantages:
– Allows access to different types of databases
– Uniform way of retrieving information
– Highly efficient
– Low memory requirements
• Disadvantages
– Complex and steep learning curve
– All data in database must look like a relational
database
49. Conclusion
• ODBC changed the way people code their programs
that have to interact with databases.
• The efficiency of programmers in the business world
has increased due to ODBC because they no longer
are wasting time to create multiple copies of a
program.
• ODBC has vastly improved the way programmers
deal with databases.