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CHM201 General Chemistry and Laboratory I
Laboratory 6 – Ideal Gas Experiments
November 3, 2021
Name
Group
PLEASE ENABLE EDITING BEFORE FILLING OUT THIS
REPORT!
Report Due by November 28, 2021.
No report will be accepted for credit after December 5, 2021
Grade:
Lab average to date:
Overall average to date:
1.
Determination of the Ideal Gas Constant "R" using Carbon
Dioxide. (Report 3 digits for this exercise. No points will be
deducted for significant digit errors.) (20 points)
Mass of beaker (optional)
Mass of plastic bag (optional)
Temperature (in the bag)
Volume of plastic bag
Barometric pressure
Trial
1
2
3
4 (wet)
5 (wet)
Mf
Mi
R
Rave
% Error
2. Determining the Molecular Weight of a Gas. (SIGNIFICANT
FIGURES MATTER HERE!) (30 pts)
Room temperature – TR
Water temperature - Tw
Barometric Pressure – Patm
Vapor Pressure of Water – Pwater
Pressure of Butane – Pbutane (Patm- Pwater)
Trial
1
2
3
Total
Mf
MI
Mbutane
Vbutane
Molar Mass
3. Pressure/Volume Measurements. (Report 3 digits for this
exercise. No points will be deducted for significant figure
errors.) (20 points)
V
20 cm3
16 cm3
9 cm3
6 cm3
4 cm3
P
PV
V
5 cm3
10 cm3
20 cm3
P
PV
V
20 cm3
10 cm3
5 cm3
P
PV
Questions (30 points)
1. How do you explain the large percent error in the gas
constant determination? There are both experimental and
scientific factors involved. Include both.
2. If some water remained on the lighter at the time of the
second weighing (after collecting the gas), how would this
affect your determination of molecular weight? Be specific.
Show a sample calculation to clarify your answer.
3. Which of the individual gas laws is confirmed by the results
of part 3?
1
Database Security Top Proposal
Student’s name
Institution affiliation
Course
Instructor’s name
Date
Introduction
Statistical database security will be the focus of the research
proposal. Because statistical data is used to answer statistical
questions about an organization's performance, it should be kept
private for any given organization. Private information could
fall into the hands of those wishing to harm the organization's
employees or customers in the event of a data breach. To
protect the confidentiality of sensitive transactional data,
statistical databases must be safeguarded. “Database Security
Technical Implementation Guide, states that database security
should provide “controlled, protected access to the contents of
your database and, in the process, preserves the integrity,
consistency, and overall quality of your data” (p. 9). The goal is
simple, the path to achieving the goal, a bit more complex.
Research Statement
The primary goal of statistical database protection is to ensure
data privacy while minimizing data loss. The most pressing
concerns for data owners are access to reliable and unlimited
data and ensuring that publicly disseminated information is kept
private. ‘database security encompasses three constructs:
confidentiality or protection of data from unauthorized
disclosure, integrity or prevention from unauthorized data
access, and availability or the identification of and recovery
from hardware and software errors or malicious activity
resulting in the denial of data availability.’ Because these two
actions are mutually exclusive, high-quality data must be
protected from both disclosure and identification.
Event Analysis
To keep statistical databases safe from intrusion, two methods
are used. Restriction means that the organization will only
present statistical data that has been deemed safe, whereas noise
addition means that data will be available as estimates rather
than exact figures. These two methods are critical for
determining whether or not data has been lost or stolen.When a
snooper is determined to obtain classified information about a
specific element, threats to statistical data arise. In a situation
like this, private information will likely be made public. When
snoopers derive filtered estimations of interest and exact
assessments of private values from the responses, one or more
statistical inquiries can lead to exposure.
Top Statistical Databases Threats
Most statistical databases can be easily abused and manipulated
by an overly powerful employee. This is more likely to occur
when employees' supervisors or managers grant them database
privileges that go above and beyond what their job descriptions
require. “Today's information security battleground is all about
entitlements – who’s got them, whether they were granted
properly, and how to enforce them” (p.117). Being able to
assess access control techniques is critical to student
understanding of database security. Bank employees can easily
increase or decrease customers' account balances and changes
their account information. It's not uncommon for businesses to
fail to update employees' access privileges when they change
departments or even leave (Murray, 2016). Malicious employees
have also taken over statistical databases and used them for
their gain. These employees commit illegal acts by abusing the
privileges bestowed upon them by their positions of authority
within the database.
Strategies to Protect Statistical Databases
Each sensitive statistical database should be kept separate from
the others. An accurate inventory of all statistical databases that
should be used throughout the company can assist in meeting
this goal. This can be used to identify sensitive data if it is
stored in these databases. Following that, all security flaws
must be addressed. The system administrator in question must
be actively involved in the ongoing assessment, identification,
and remediation of any vulnerability in the statistical database
in question.
References
Murray, M. C. (2016). Database security: What students need to
know. Journal of information technology education: Innovations
in practice, 9, IIP-61.
https://digitalcommons.kennesaw.edu/facpubs/1389/
1
Database Security Top Proposal
Student’s name
Institution affiliation
Course
Instructor’s name
Date
1
Database Security Top Proposal
Student’s name
Institution affiliation
Course
Instructor’s name
Date

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CHM201 General Chemistry and Laboratory ILaboratory 6 – Ideal Ga

  • 1. CHM201 General Chemistry and Laboratory I Laboratory 6 – Ideal Gas Experiments November 3, 2021 Name Group PLEASE ENABLE EDITING BEFORE FILLING OUT THIS REPORT! Report Due by November 28, 2021. No report will be accepted for credit after December 5, 2021 Grade: Lab average to date: Overall average to date: 1. Determination of the Ideal Gas Constant "R" using Carbon Dioxide. (Report 3 digits for this exercise. No points will be deducted for significant digit errors.) (20 points) Mass of beaker (optional)
  • 2. Mass of plastic bag (optional) Temperature (in the bag) Volume of plastic bag Barometric pressure Trial 1 2 3 4 (wet) 5 (wet) Mf Mi R
  • 3. Rave % Error 2. Determining the Molecular Weight of a Gas. (SIGNIFICANT FIGURES MATTER HERE!) (30 pts) Room temperature – TR Water temperature - Tw Barometric Pressure – Patm Vapor Pressure of Water – Pwater Pressure of Butane – Pbutane (Patm- Pwater) Trial 1 2 3
  • 4. Total Mf MI Mbutane Vbutane Molar Mass 3. Pressure/Volume Measurements. (Report 3 digits for this exercise. No points will be deducted for significant figure errors.) (20 points) V 20 cm3 16 cm3 9 cm3
  • 5. 6 cm3 4 cm3 P PV V 5 cm3 10 cm3 20 cm3 P PV V 20 cm3 10 cm3 5 cm3 P
  • 6. PV Questions (30 points) 1. How do you explain the large percent error in the gas constant determination? There are both experimental and scientific factors involved. Include both. 2. If some water remained on the lighter at the time of the second weighing (after collecting the gas), how would this affect your determination of molecular weight? Be specific. Show a sample calculation to clarify your answer.
  • 7. 3. Which of the individual gas laws is confirmed by the results of part 3? 1 Database Security Top Proposal Student’s name
  • 8. Institution affiliation Course Instructor’s name Date Introduction Statistical database security will be the focus of the research proposal. Because statistical data is used to answer statistical questions about an organization's performance, it should be kept private for any given organization. Private information could fall into the hands of those wishing to harm the organization's employees or customers in the event of a data breach. To protect the confidentiality of sensitive transactional data, statistical databases must be safeguarded. “Database Security Technical Implementation Guide, states that database security should provide “controlled, protected access to the contents of your database and, in the process, preserves the integrity, consistency, and overall quality of your data” (p. 9). The goal is simple, the path to achieving the goal, a bit more complex. Research Statement The primary goal of statistical database protection is to ensure data privacy while minimizing data loss. The most pressing concerns for data owners are access to reliable and unlimited data and ensuring that publicly disseminated information is kept private. ‘database security encompasses three constructs: confidentiality or protection of data from unauthorized disclosure, integrity or prevention from unauthorized data access, and availability or the identification of and recovery from hardware and software errors or malicious activity resulting in the denial of data availability.’ Because these two actions are mutually exclusive, high-quality data must be protected from both disclosure and identification. Event Analysis To keep statistical databases safe from intrusion, two methods are used. Restriction means that the organization will only
  • 9. present statistical data that has been deemed safe, whereas noise addition means that data will be available as estimates rather than exact figures. These two methods are critical for determining whether or not data has been lost or stolen.When a snooper is determined to obtain classified information about a specific element, threats to statistical data arise. In a situation like this, private information will likely be made public. When snoopers derive filtered estimations of interest and exact assessments of private values from the responses, one or more statistical inquiries can lead to exposure. Top Statistical Databases Threats Most statistical databases can be easily abused and manipulated by an overly powerful employee. This is more likely to occur when employees' supervisors or managers grant them database privileges that go above and beyond what their job descriptions require. “Today's information security battleground is all about entitlements – who’s got them, whether they were granted properly, and how to enforce them” (p.117). Being able to assess access control techniques is critical to student understanding of database security. Bank employees can easily increase or decrease customers' account balances and changes their account information. It's not uncommon for businesses to fail to update employees' access privileges when they change departments or even leave (Murray, 2016). Malicious employees have also taken over statistical databases and used them for their gain. These employees commit illegal acts by abusing the privileges bestowed upon them by their positions of authority within the database. Strategies to Protect Statistical Databases Each sensitive statistical database should be kept separate from the others. An accurate inventory of all statistical databases that should be used throughout the company can assist in meeting this goal. This can be used to identify sensitive data if it is stored in these databases. Following that, all security flaws must be addressed. The system administrator in question must be actively involved in the ongoing assessment, identification,
  • 10. and remediation of any vulnerability in the statistical database in question. References Murray, M. C. (2016). Database security: What students need to know. Journal of information technology education: Innovations in practice, 9, IIP-61. https://digitalcommons.kennesaw.edu/facpubs/1389/ 1 Database Security Top Proposal Student’s name Institution affiliation Course Instructor’s name Date
  • 11. 1 Database Security Top Proposal Student’s name Institution affiliation Course Instructor’s name Date