The document discusses implementing total quality management (TQM) in education. It provides an overview of TQM and its origins, then describes several quality control tools that can be used in education, including flow diagrams, brainstorming, data collection methods like checksheets, and analysis tools like histograms, cause-and-effect diagrams, Pareto charts, and stratification. It emphasizes applying these problem-solving techniques and statistical quality control methods to help educational organizations achieve excellence.
The document discusses implementing total quality management (TQM) in education. It describes how TQM was developed and adopted, then explains how some key TQM tools and techniques like the PDCA cycle, flow diagrams, brainstorming, data collection, graphs, and cause-and-effect diagrams can be applied to education to help solve problems and continually improve quality.
This document discusses 7 quality control tools: check sheets, Pareto diagrams, cause and effect diagrams, stratification, scatter diagrams, histograms, and graphs and control charts. It provides details on how to collect data and use check sheets, Pareto analysis, cause and effect diagrams, stratification, scatter diagrams, and histograms for quality control purposes. Key steps and considerations for constructing and interpreting these tools are outlined.
ABCi Skills for Improvement- Pareto ChartABCiABUHB
A Pareto chart presents causes of a problem in descending order based on their quantified contribution, highlighting the major causes. It helps focus improvement efforts on the most impactful issues. The chart arranges potential causes on the horizontal axis and frequency or cost on the vertical axis. It also includes a cumulative line to identify the "vital few" causes that make up 80% of the problem, where focusing efforts achieves the best results. Data on quantified causes is required and the chart is constructed by ranking and calculating percentages of the total problem.
BUSI 331Marketing Research Report Part 3 InstructionsData .docxhumphrieskalyn
BUSI 331
Marketing Research Report Part 3 Instructions
Data Submission
Review the Basic Data Analysis section in the Zikmund & Babin text and the presentation from Module/Week 4, Presentation: Using Excel for Data Analysis. There will be 2 submissions in this assignment: the Excel document with the raw data that includes a code guide and the Marketing Research Report as a continuation of your Part 1 Word document.
1. Submit the raw data from your survey results in an Excel document. To do this, you will need to build an Excel spreadsheet to organize your data. You may find that Survey Monkey or other online survey tools will already do this for you.
2. In order to get the best results from your data analysis, you will need to code your responses that are not already numerical. For example, if your question asked if the respondent was male or female, male=0, and female=1. If it was yes or no question, yes=0, no=1. Please include a code guide with your raw data.
Your Excel document submission is your raw data with a code chart to clarify what the raw numbers stand for. Please note that raw data is numerical and the data has not been manipulated in any way. You can post the Code Guide in Sheet 2 of your Excel document if that is easier for you. As an example, your raw data and code guide will look like this:
Respondent
Gender
Age
Q1
1
1
1
1
2
1
2
4
3
2
3
3
4
2
2
5
5
1
3
2
Code Guide:
Gender: 1=male, 2=female
Age Range: 1=18-24, 2=25-30, etc.
Q1 (5 point likert scale): 1=very unlikely, 2=unlikely, 3=neutral, etc.
3. Submit 3 tables that were created in Excel from your data, inclusive of 1 frequency table and 2 cross-tabulation tables. This needs to be relevant information that will directly impact your research problem. Please write 1 comprehensive paragraph underneath each individual table that clearly describes what the table is showing and what the inferences are from this table and information in relation to the research problem. Turn at least 1 of your tables into a graph (either a bar or pie chart) to show the data from the table. Place this material (three charts/tables and three written discussions of each) as Appendix 2 in your research report, and submit this part as a compilation with your Parts 1 and 2.
This assignment is due by 11:59 p.m. (ET) on Monday of Module/Week 6.
Show all your work neatly for full credit.
1) Solve the differential equations:
2) Compute the solution of the given initial value problem.
3) For the equation
a) determine the frequency of the beats.
b) determine the frequency of the rapid oscillations.
c) Use the informayion from parts a) and b) to give a rough sketch of the graph of a typical solution.
4) Consider the equation
a) Compute the general solution.
a)
Solve the initial value problem
...
This document discusses bunking lectures and uses a Pareto chart to analyze the key factors responsible. It introduces the Pareto principle, which states that a small number of causes are responsible for the majority of problems. A survey found that 80% of reasons for bunking lectures were to attend coaching classes, dislike a subject, peer pressure, course content available elsewhere, and issues with the teacher. The document defines a Pareto chart as a type of bar graph used to visualize important situations or causes. Analyzing the major factors through a Pareto chart can help address the primary issues and significantly improve outcomes.
This document discusses bunking lectures and uses a Pareto chart to analyze the key factors responsible. It introduces the Pareto principle, which states that a small number of causes are responsible for the majority of problems. A survey found that 80% of reasons for bunking lectures were to attend coaching classes, dislike a subject, peer pressure, course content available elsewhere, and issues with the teacher. The document defines a Pareto chart as a type of bar graph used to visualize important situations or causes. Analyzing the major factors through a Pareto chart can help address the biggest problems and improve outcomes.
The document discusses implementing total quality management (TQM) in education. It provides an overview of TQM and its origins, then describes several quality control tools that can be used in education, including flow diagrams, brainstorming, data collection methods like checksheets, and analysis tools like histograms, cause-and-effect diagrams, Pareto charts, and stratification. It emphasizes applying these problem-solving techniques and statistical quality control methods to help educational organizations achieve excellence.
The document discusses implementing total quality management (TQM) in education. It describes how TQM was developed and adopted, then explains how some key TQM tools and techniques like the PDCA cycle, flow diagrams, brainstorming, data collection, graphs, and cause-and-effect diagrams can be applied to education to help solve problems and continually improve quality.
This document discusses 7 quality control tools: check sheets, Pareto diagrams, cause and effect diagrams, stratification, scatter diagrams, histograms, and graphs and control charts. It provides details on how to collect data and use check sheets, Pareto analysis, cause and effect diagrams, stratification, scatter diagrams, and histograms for quality control purposes. Key steps and considerations for constructing and interpreting these tools are outlined.
ABCi Skills for Improvement- Pareto ChartABCiABUHB
A Pareto chart presents causes of a problem in descending order based on their quantified contribution, highlighting the major causes. It helps focus improvement efforts on the most impactful issues. The chart arranges potential causes on the horizontal axis and frequency or cost on the vertical axis. It also includes a cumulative line to identify the "vital few" causes that make up 80% of the problem, where focusing efforts achieves the best results. Data on quantified causes is required and the chart is constructed by ranking and calculating percentages of the total problem.
BUSI 331Marketing Research Report Part 3 InstructionsData .docxhumphrieskalyn
BUSI 331
Marketing Research Report Part 3 Instructions
Data Submission
Review the Basic Data Analysis section in the Zikmund & Babin text and the presentation from Module/Week 4, Presentation: Using Excel for Data Analysis. There will be 2 submissions in this assignment: the Excel document with the raw data that includes a code guide and the Marketing Research Report as a continuation of your Part 1 Word document.
1. Submit the raw data from your survey results in an Excel document. To do this, you will need to build an Excel spreadsheet to organize your data. You may find that Survey Monkey or other online survey tools will already do this for you.
2. In order to get the best results from your data analysis, you will need to code your responses that are not already numerical. For example, if your question asked if the respondent was male or female, male=0, and female=1. If it was yes or no question, yes=0, no=1. Please include a code guide with your raw data.
Your Excel document submission is your raw data with a code chart to clarify what the raw numbers stand for. Please note that raw data is numerical and the data has not been manipulated in any way. You can post the Code Guide in Sheet 2 of your Excel document if that is easier for you. As an example, your raw data and code guide will look like this:
Respondent
Gender
Age
Q1
1
1
1
1
2
1
2
4
3
2
3
3
4
2
2
5
5
1
3
2
Code Guide:
Gender: 1=male, 2=female
Age Range: 1=18-24, 2=25-30, etc.
Q1 (5 point likert scale): 1=very unlikely, 2=unlikely, 3=neutral, etc.
3. Submit 3 tables that were created in Excel from your data, inclusive of 1 frequency table and 2 cross-tabulation tables. This needs to be relevant information that will directly impact your research problem. Please write 1 comprehensive paragraph underneath each individual table that clearly describes what the table is showing and what the inferences are from this table and information in relation to the research problem. Turn at least 1 of your tables into a graph (either a bar or pie chart) to show the data from the table. Place this material (three charts/tables and three written discussions of each) as Appendix 2 in your research report, and submit this part as a compilation with your Parts 1 and 2.
This assignment is due by 11:59 p.m. (ET) on Monday of Module/Week 6.
Show all your work neatly for full credit.
1) Solve the differential equations:
2) Compute the solution of the given initial value problem.
3) For the equation
a) determine the frequency of the beats.
b) determine the frequency of the rapid oscillations.
c) Use the informayion from parts a) and b) to give a rough sketch of the graph of a typical solution.
4) Consider the equation
a) Compute the general solution.
a)
Solve the initial value problem
...
This document discusses bunking lectures and uses a Pareto chart to analyze the key factors responsible. It introduces the Pareto principle, which states that a small number of causes are responsible for the majority of problems. A survey found that 80% of reasons for bunking lectures were to attend coaching classes, dislike a subject, peer pressure, course content available elsewhere, and issues with the teacher. The document defines a Pareto chart as a type of bar graph used to visualize important situations or causes. Analyzing the major factors through a Pareto chart can help address the primary issues and significantly improve outcomes.
This document discusses bunking lectures and uses a Pareto chart to analyze the key factors responsible. It introduces the Pareto principle, which states that a small number of causes are responsible for the majority of problems. A survey found that 80% of reasons for bunking lectures were to attend coaching classes, dislike a subject, peer pressure, course content available elsewhere, and issues with the teacher. The document defines a Pareto chart as a type of bar graph used to visualize important situations or causes. Analyzing the major factors through a Pareto chart can help address the biggest problems and improve outcomes.
This document discusses bunking lectures and uses a Pareto chart to analyze the key factors responsible. It introduces the Pareto principle, which states that a small number of causes are responsible for the majority of problems. A survey found that 80% of reasons for bunking lectures were to attend coaching classes, dislike a subject, peer pressure, course content available elsewhere, and issues with the teacher. The document defines a Pareto chart as a type of bar graph used to visualize important situations or causes. Analyzing the major factors through a Pareto chart can help address the biggest problems and improve outcomes.
The document discusses 7 quality control tools: 1) cause-and-effect diagram, 2) check sheets, 3) histogram, 4) Pareto chart, 5) flow chart, 6) scatter diagram, and 7) run chart. These tools help identify issues, collect and analyze quality data, find root causes of problems, and monitor processes over time to ensure quality. The tools are graphical techniques that can be used with little formal training to solve most quality issues.
The document provides an overview of tools and methods for data collation and analysis, including cause and effect analysis, the multiple whys technique, Pareto analysis, and root cause analysis. It uses an example of long queues at photocopy stations to illustrate how to apply these tools to identify the root causes of problems based on collected data.
The document provides an introduction and overview of Pareto analysis. It discusses how Vilfredo Pareto first observed the 80/20 principle in the distribution of wealth in Italy in the late 19th century. Joseph Juran later applied this principle to quality control, giving rise to Pareto analysis. The document then defines Pareto analysis and outlines the typical six-step process for conducting a Pareto analysis to identify the vital few causes of problems. Several applications and advantages of Pareto analysis in management and accounting are also discussed.
Big Data Analytics Tools..DS_Store__MACOSXBig Data Analyti.docxtangyechloe
Big Data Analytics Tools./.DS_Store
__MACOSX/Big Data Analytics Tools./._.DS_Store
Big Data Analytics Tools./ Final Exam/PROJECT - BETTER UNDERSTAND ATTRITION.docx
FINAL EXAM – EXERCISE – To Better Understand Attrition.
This is a final project – you are going to exam the HR-BalanceSheet dataset and write a short report on what you found. I will guide you through the analysis, but as we go through the analysis you are going to need to capture data for the final report.
1. Load the dataset into Statistica
2. Generate Histograms for all of the data
a. Make notes on what you observe from the histograms. Can you learn anything about the business from these histograms?
b. Capture all of the histograms.
3. Now generate a correlation matrix to see if any variables are highly correlated. If variables are highly correlated and you are doing a supervised method (e.g., decision tree), then one of them must be omitted from the analysis. Do you know why?
Statistics->Nonparametrics->Correlations Okay.
Now select ALL of the variables and select “Spearman rank R”.
4. Let’s copy this out to Excel.
a. Open a blank Excel file
b. Go to Statistica – the output correlation matrix –
i. Hit Ctrl – A - this will select everything.
ii. Right Click - select “Copy with Headers”
iii. Go To Excel – select Paste
5. Select all of the numbers in Excel
a. Go To Conditional Formatting
i. Highlight all values greater than 0.70
6. This tells you the values that are highly correlated. Record what they are – these cannot be used in a supervised modeling exercise together. For example, JobLevel and TotalWorkingYears are highly correlated.
a. Make a list of all of the variables that are highly correlated (>0.7).
BUSINESS PROBLEM: The company has employee data for the last several years. In this data set we have a wide range of data, including whether or not they left the company (i.e., Attrition). If Attrition is set to “Yes”, they left the company. If Attrition is set to “No”, they did not leave the company.
The first thing we want to do is take a “high” level look at those people who left the company.
Go to Selection Criteria – that is accessible through the Sel:Off setting at the bottom of the Statistica window. Click on “Sel:Off”
Set the selection criteria to Attribute = “Yes”.
7. Generate Histograms for all of the data
a. Make notes on what you observe from the histograms. Can you learn anything about the business from these histograms?
b. Capture the histograms that tell you something about the business.
Go back to the selection criteria and turn the Sel: back to “Off”.
8. Now build a decision tree (C&RT) to see if we can find out what influences where or not individuals decide to leave the company.
If you exclude the variables that are highly correlated, you can generate a tree.
Generate a C&RT tree
Pick your variables (Quick)
· Attrition is your dependent variable
· Select the categorical and continuous v.
Exercise 1 Risk Analysis Before you begin this assignment, be .docxgitagrimston
Exercise 1: Risk Analysis
Before you begin this assignment, be sure you have read the Case Study and completed the assignment for the Case Study Stage One and Stage Two projects. You should also review the reading “How To Guide to Risk Management.”
Purpose of this Exercise
This activity provides you the opportunity to apply a risk analysis to a specific technology solution. It directly supports the following course outcomes to enable you to:
· evaluate information systems and enterprise solutions to determine the best fit to enable the organization's strategic outcomes
· use information technology tools and techniques to support business intelligence gathering and decision making
· apply information technology best practices and methodologies to create information technology solutions
Assignment
Using the Case Study and the IT solution you proposed for Stage One of the Case Study project, complete the risk analysis matrix provided below.
1. Briefly describe your proposed IT solution.
2. Complete the Risk Matrix below:, describing for each Area of Risk:
a. Explain each are of risk and describe how that area applies to your proposed IT solution for the Case Study,
b. the probability (High/Medium/Low) of its occurrence,
c. impact (High/Medium/Low) on the organization if it does occur and
d. a strategy to mitigate the risk.
3. Explanations of each of the Areas of Risk are available in the document “How to Guide to Risk Management,” pages B3-B7. Definitions for probability of occurrence and impact may be found on page 7 and an example of a mitigation strategy is given on page 9 of the same document.
Your paper should be 2-3 pages in length and provide the brief description in a paragraph followed by the table below, that you may copy, paste into your file and then complete. Do not limit yourself to the space shown in table, but provide complete answers for “Description” and “Strategy for Mitigation.” Submit your paper via your Assignment Folder as a Word document with your last name included in the filename. Use the Grading Rubric below to be sure you have covered all aspects of the assignment.
Risk Analysis
4. Brief Description of Proposed IT
Solution
as it relates to the Case Study:
1. Risk Matrix
Area of Risk
Description
Probability of Occurrence
Impact
of Occurrence
Strategy for Mitigation
1. Strategic
1. Business
1. Feasibility
1. Capability to Manage Investment
1. Organization and Change Management
1. Dependencies and Interoperability
1. Security
1. Privacy
1. Project Resources
1. 0. Schedule
1. 1. Initial Cost
1. 2. Life Cycle Cost
1. 3. Technical Obsolescence
1. 4. Technology Environment
1. 5. Reliability of Systems
1. 6. Data and Information
1. 7. Overall Risk of Investment Failure
SPECIAL PUBLICATION Summer 1998
DATA “SANITY”:
STATISTICAL THINKING
APPLIED TO EVERYDAY DATA
DAVIS BALESTRACCI
HEALTHSYSTEM MINNESOTA
1.0 Introductory ...
Qualitative research data is interpretive and descriptive in nature. The best way to organize and manage qualitative data is through coding or grouping the data to look for patterns in the findings. Good qualitative data management involves having a clear file naming system, a data tracking system, and securely storing data during and after the research process. Qualitative data collection methods aim to understand people's experiences through techniques like interviews, observations, and focus groups to gain an in-depth perspective.
The 7 QC tools are statistical problem solving methods introduced in Japan after World War II. The most important tools are: 1) Pareto diagram, which identifies the major issues contributing to the most problems; 2) Cause and effect diagram, also known as a fishbone diagram, which maps the causes of a problem systematically; and 3) Histogram, which analyzes the distribution of data through bar charts of frequency distributions to identify patterns and draw conclusions about process control. These tools were foundational to Japan's post-war industrial recovery.
The document discusses 7 planning tools used in Total Quality Management (TQM): fishbone diagram, Pareto chart, checksheet, histogram, control charts, scatter diagram, and flow charts. It provides descriptions of each tool, including what they are used for and how to construct them. The fishbone diagram is used to identify and relate causes of a problem. The Pareto chart identifies the most important causes to address. The checksheet collects quantitative or qualitative data. Histograms show the distribution of data, and control charts monitor process stability. Scatter diagrams show relationships between variables. Flow charts map out process steps.
Steps for Effective Case Analysis Adapted from Harvard .docxrjoseph5
Steps for Effective Case Analysis
Adapted from Harvard Business Publishing
It's useful to think of a case analysis as digging deeper and deeper into the layers of a case.
You should make sure to follow these general steps in addition to answering the questions
from the case.
1. You start at the surface, Getting Oriented and examining the overall case
landscape.
2. Then you begin to dig, Identifying Problems, as well as possible alternative
solutions.
3. This is the section where you will spend most of your time.
Digging deeper, Performing Analyses you identify information that exposes the issues,
gather data, perform calculations that might provide insight. "Analysis" describes the
varied and crucial things you do with information in the case, to shed light on the problems
and issues you've identified. That might mean calculating and comparing cumulative
growth rates for different periods from the year-by-year financials in a case's exhibits. Or it
might mean pulling together seemingly unrelated facts from two different sections of the
case, and combining them logically to arrive at an important conclusion or conjecture.
Analysis usually doesn't provide definitive answers. But as you do more of it, a clearer
picture often starts to emerge, or the preponderance of evidence begins to point to one
interpretation rather than others. Don't expect a case analysis to yield a "final answer." If
you're accustomed to doing analysis that ends with a right answer, coming up with a
possible solution that simply reflects your best judgment might frustrate you. But
remember that cases, much like real-world business experiences, rarely reveal an
absolutely correct answer, no matter how deeply you analyze them. Typically, you'll do
qualitative analysis based on your reading and interpretation of the case. Ask yourself:
What is fact and what is opinion? Which facts are contributing to the problem? Which are
the causes?
Qualitative factors should be prioritized and fully developed to support your argument.
Make notes about your evolving interpretations, always being careful to list the evidence or
reasons that support them. Qualitative information in a case can be a mix of objective and
subjective information. For example, you may need to assess the validity of quotations from
company executives, each of whom has a subjective opinion. Reports from external
industry analysts or descriptions of what other companies in the industry have done might
seem more objective; no one in the case has a vested interest in this information. A
company's internal PowerPoint presentation should be considered separately and
differently from a newspaper article about the company. Cases mix firsthand quotations
and opinions with third-person narratives, so you need to consider the reliability of
sources. As in real life, you shouldn't take all case information at face value.
Quantitative data—such as amounts of.
The Easy Guide for Deployment Diagrams by Creately.
Risk management is a process in which risks are identified and controlled proactively. It allows businesses to improve their chances of success by minimizing threats and maximizing opportunities. Creately offers editable templates which you can use for your risk management process. A variety of different templates on Risk Management are included which you can use for each step throughout your Risk Management Process.
Also, you can find many more useful diagram templates in our diagram community and all our popular diagram templates are available for free. Just click on the "Use as Template" button to immediately start modifying it using our online diagramming tools.
The Problem Statement By Dr. Marilyn Simon Find this a.docxoscars29
The document provides information about a Monte Carlo simulation exercise to estimate the total costs of installing a backup generator at a government facility. It includes historical cost data for design, build, and test efforts and asks the reader to conduct 10 iterations of the simulation to generate a cost distribution. It then asks questions about calculating the average cost, the standard deviation of the distribution, and the probability of costs exceeding $105,000. The document provides information and examples to help calculate standard deviation.
Pareto analysis is a technique used to identify the most important causes of problems that need to be addressed. It is based on the Pareto principle (also known as the 80/20 rule), which states that roughly 80% of the effects come from 20% of the causes. Pareto analysis involves identifying problems, determining their root causes, scoring them based on frequency or impact, grouping the causes, and summing the scores to identify the vital few causes that should be prioritized to resolve the majority of problems. An example is provided of a service center manager who used Pareto analysis to identify that lack of training and too few staff were the primary root causes of customer complaints.
This document provides an introduction to statistical process control (SPC). SPC is used to monitor and control processes to maximize conforming product output while minimizing waste. The key purposes of SPC include preventing defects, indicating when corrective action is needed, and facilitating continuous process improvement. Common SPC tools described in the document are cause-and-effect diagrams, check sheets, flow diagrams, Pareto analysis, histograms, run charts, and control charts. Pareto analysis involves identifying problems, scoring them based on impact, and prioritizing addressing the highest scoring issues first. Histograms and run charts are used to analyze process variation over time. Control charts establish limits to determine whether a process is in or out of statistical control.
Seven Basic Quality Control Tools أدوات ضبط الجودة السبعةMohamed Khaled
The 7 QC tools are fundamental instruments to improve the process and product quality. They are used to examine the production process.
► The seven basic tools are:
1- Check sheet
2- Pareto analysis
3- Cause and Effect Diagram
4- Scatter plot
5- Histogram
6- Flowchart
7- Control charts
-------------------------------------------------------------------------------------
#7_Basic_Quality_Control_Tools #Check_sheet #Pareto_analysis #Fishbone #Scatter_plot #Histogram #Flowchart #Control_charts #CFturbo #Pump_simulation_using_ANSYS #Water_Hammer #أدوات_ضبط_الجودة_السبعة #نموذج_التحقق #مخطط_باريتو #مخطط_السبب_والأثر #مخطط_التشتت #مدرج_تكراري #خرائط_التدفق #خرائط_ضبط_الجودة
A power point presentation on statisticsKriace Ward
Statistics originated from Latin, Italian, and German words referring to organized states. Gottfried Achenwall is considered the "father of statistics" for coining the term to describe a specialized branch of knowledge. Modern statistics is defined as the science of judging collective phenomena through analysis and enumeration. While statistics can be an art and a science, its successful application depends on the skill of the statistician and their knowledge of the field being studied. Statistics are important across many domains from business, economics, and planning to the sciences. However, statistics also have limitations such as only studying aggregates, not individuals, and results being valid only on average and in the long run.
06-18-2024-Princeton Meetup-Introduction to MilvusTimothy Spann
06-18-2024-Princeton Meetup-Introduction to Milvus
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://github.com/milvus-io/milvus
Get Milvused!
https://milvus.io/
Read my Newsletter every week!
https://github.com/tspannhw/FLiPStackWeekly/blob/main/142-17June2024.md
For more cool Unstructured Data, AI and Vector Database videos check out the Milvus vector database videos here
https://www.youtube.com/@MilvusVectorDatabase/videos
Unstructured Data Meetups -
https://www.meetup.com/unstructured-data-meetup-new-york/
https://lu.ma/calendar/manage/cal-VNT79trvj0jS8S7
https://www.meetup.com/pro/unstructureddata/
https://zilliz.com/community/unstructured-data-meetup
https://zilliz.com/event
Twitter/X: https://x.com/milvusio https://x.com/paasdev
LinkedIn: https://www.linkedin.com/company/zilliz/ https://www.linkedin.com/in/timothyspann/
GitHub: https://github.com/milvus-io/milvus https://github.com/tspannhw
Invitation to join Discord: https://discord.com/invite/FjCMmaJng6
Blogs: https://milvusio.medium.com/ https://www.opensourcevectordb.cloud/ https://medium.com/@tspann
Expand LLMs' knowledge by incorporating external data sources into LLMs and your AI applications.
This document discusses bunking lectures and uses a Pareto chart to analyze the key factors responsible. It introduces the Pareto principle, which states that a small number of causes are responsible for the majority of problems. A survey found that 80% of reasons for bunking lectures were to attend coaching classes, dislike a subject, peer pressure, course content available elsewhere, and issues with the teacher. The document defines a Pareto chart as a type of bar graph used to visualize important situations or causes. Analyzing the major factors through a Pareto chart can help address the biggest problems and improve outcomes.
The document discusses 7 quality control tools: 1) cause-and-effect diagram, 2) check sheets, 3) histogram, 4) Pareto chart, 5) flow chart, 6) scatter diagram, and 7) run chart. These tools help identify issues, collect and analyze quality data, find root causes of problems, and monitor processes over time to ensure quality. The tools are graphical techniques that can be used with little formal training to solve most quality issues.
The document provides an overview of tools and methods for data collation and analysis, including cause and effect analysis, the multiple whys technique, Pareto analysis, and root cause analysis. It uses an example of long queues at photocopy stations to illustrate how to apply these tools to identify the root causes of problems based on collected data.
The document provides an introduction and overview of Pareto analysis. It discusses how Vilfredo Pareto first observed the 80/20 principle in the distribution of wealth in Italy in the late 19th century. Joseph Juran later applied this principle to quality control, giving rise to Pareto analysis. The document then defines Pareto analysis and outlines the typical six-step process for conducting a Pareto analysis to identify the vital few causes of problems. Several applications and advantages of Pareto analysis in management and accounting are also discussed.
Big Data Analytics Tools..DS_Store__MACOSXBig Data Analyti.docxtangyechloe
Big Data Analytics Tools./.DS_Store
__MACOSX/Big Data Analytics Tools./._.DS_Store
Big Data Analytics Tools./ Final Exam/PROJECT - BETTER UNDERSTAND ATTRITION.docx
FINAL EXAM – EXERCISE – To Better Understand Attrition.
This is a final project – you are going to exam the HR-BalanceSheet dataset and write a short report on what you found. I will guide you through the analysis, but as we go through the analysis you are going to need to capture data for the final report.
1. Load the dataset into Statistica
2. Generate Histograms for all of the data
a. Make notes on what you observe from the histograms. Can you learn anything about the business from these histograms?
b. Capture all of the histograms.
3. Now generate a correlation matrix to see if any variables are highly correlated. If variables are highly correlated and you are doing a supervised method (e.g., decision tree), then one of them must be omitted from the analysis. Do you know why?
Statistics->Nonparametrics->Correlations Okay.
Now select ALL of the variables and select “Spearman rank R”.
4. Let’s copy this out to Excel.
a. Open a blank Excel file
b. Go to Statistica – the output correlation matrix –
i. Hit Ctrl – A - this will select everything.
ii. Right Click - select “Copy with Headers”
iii. Go To Excel – select Paste
5. Select all of the numbers in Excel
a. Go To Conditional Formatting
i. Highlight all values greater than 0.70
6. This tells you the values that are highly correlated. Record what they are – these cannot be used in a supervised modeling exercise together. For example, JobLevel and TotalWorkingYears are highly correlated.
a. Make a list of all of the variables that are highly correlated (>0.7).
BUSINESS PROBLEM: The company has employee data for the last several years. In this data set we have a wide range of data, including whether or not they left the company (i.e., Attrition). If Attrition is set to “Yes”, they left the company. If Attrition is set to “No”, they did not leave the company.
The first thing we want to do is take a “high” level look at those people who left the company.
Go to Selection Criteria – that is accessible through the Sel:Off setting at the bottom of the Statistica window. Click on “Sel:Off”
Set the selection criteria to Attribute = “Yes”.
7. Generate Histograms for all of the data
a. Make notes on what you observe from the histograms. Can you learn anything about the business from these histograms?
b. Capture the histograms that tell you something about the business.
Go back to the selection criteria and turn the Sel: back to “Off”.
8. Now build a decision tree (C&RT) to see if we can find out what influences where or not individuals decide to leave the company.
If you exclude the variables that are highly correlated, you can generate a tree.
Generate a C&RT tree
Pick your variables (Quick)
· Attrition is your dependent variable
· Select the categorical and continuous v.
Exercise 1 Risk Analysis Before you begin this assignment, be .docxgitagrimston
Exercise 1: Risk Analysis
Before you begin this assignment, be sure you have read the Case Study and completed the assignment for the Case Study Stage One and Stage Two projects. You should also review the reading “How To Guide to Risk Management.”
Purpose of this Exercise
This activity provides you the opportunity to apply a risk analysis to a specific technology solution. It directly supports the following course outcomes to enable you to:
· evaluate information systems and enterprise solutions to determine the best fit to enable the organization's strategic outcomes
· use information technology tools and techniques to support business intelligence gathering and decision making
· apply information technology best practices and methodologies to create information technology solutions
Assignment
Using the Case Study and the IT solution you proposed for Stage One of the Case Study project, complete the risk analysis matrix provided below.
1. Briefly describe your proposed IT solution.
2. Complete the Risk Matrix below:, describing for each Area of Risk:
a. Explain each are of risk and describe how that area applies to your proposed IT solution for the Case Study,
b. the probability (High/Medium/Low) of its occurrence,
c. impact (High/Medium/Low) on the organization if it does occur and
d. a strategy to mitigate the risk.
3. Explanations of each of the Areas of Risk are available in the document “How to Guide to Risk Management,” pages B3-B7. Definitions for probability of occurrence and impact may be found on page 7 and an example of a mitigation strategy is given on page 9 of the same document.
Your paper should be 2-3 pages in length and provide the brief description in a paragraph followed by the table below, that you may copy, paste into your file and then complete. Do not limit yourself to the space shown in table, but provide complete answers for “Description” and “Strategy for Mitigation.” Submit your paper via your Assignment Folder as a Word document with your last name included in the filename. Use the Grading Rubric below to be sure you have covered all aspects of the assignment.
Risk Analysis
4. Brief Description of Proposed IT
Solution
as it relates to the Case Study:
1. Risk Matrix
Area of Risk
Description
Probability of Occurrence
Impact
of Occurrence
Strategy for Mitigation
1. Strategic
1. Business
1. Feasibility
1. Capability to Manage Investment
1. Organization and Change Management
1. Dependencies and Interoperability
1. Security
1. Privacy
1. Project Resources
1. 0. Schedule
1. 1. Initial Cost
1. 2. Life Cycle Cost
1. 3. Technical Obsolescence
1. 4. Technology Environment
1. 5. Reliability of Systems
1. 6. Data and Information
1. 7. Overall Risk of Investment Failure
SPECIAL PUBLICATION Summer 1998
DATA “SANITY”:
STATISTICAL THINKING
APPLIED TO EVERYDAY DATA
DAVIS BALESTRACCI
HEALTHSYSTEM MINNESOTA
1.0 Introductory ...
Qualitative research data is interpretive and descriptive in nature. The best way to organize and manage qualitative data is through coding or grouping the data to look for patterns in the findings. Good qualitative data management involves having a clear file naming system, a data tracking system, and securely storing data during and after the research process. Qualitative data collection methods aim to understand people's experiences through techniques like interviews, observations, and focus groups to gain an in-depth perspective.
The 7 QC tools are statistical problem solving methods introduced in Japan after World War II. The most important tools are: 1) Pareto diagram, which identifies the major issues contributing to the most problems; 2) Cause and effect diagram, also known as a fishbone diagram, which maps the causes of a problem systematically; and 3) Histogram, which analyzes the distribution of data through bar charts of frequency distributions to identify patterns and draw conclusions about process control. These tools were foundational to Japan's post-war industrial recovery.
The document discusses 7 planning tools used in Total Quality Management (TQM): fishbone diagram, Pareto chart, checksheet, histogram, control charts, scatter diagram, and flow charts. It provides descriptions of each tool, including what they are used for and how to construct them. The fishbone diagram is used to identify and relate causes of a problem. The Pareto chart identifies the most important causes to address. The checksheet collects quantitative or qualitative data. Histograms show the distribution of data, and control charts monitor process stability. Scatter diagrams show relationships between variables. Flow charts map out process steps.
Steps for Effective Case Analysis Adapted from Harvard .docxrjoseph5
Steps for Effective Case Analysis
Adapted from Harvard Business Publishing
It's useful to think of a case analysis as digging deeper and deeper into the layers of a case.
You should make sure to follow these general steps in addition to answering the questions
from the case.
1. You start at the surface, Getting Oriented and examining the overall case
landscape.
2. Then you begin to dig, Identifying Problems, as well as possible alternative
solutions.
3. This is the section where you will spend most of your time.
Digging deeper, Performing Analyses you identify information that exposes the issues,
gather data, perform calculations that might provide insight. "Analysis" describes the
varied and crucial things you do with information in the case, to shed light on the problems
and issues you've identified. That might mean calculating and comparing cumulative
growth rates for different periods from the year-by-year financials in a case's exhibits. Or it
might mean pulling together seemingly unrelated facts from two different sections of the
case, and combining them logically to arrive at an important conclusion or conjecture.
Analysis usually doesn't provide definitive answers. But as you do more of it, a clearer
picture often starts to emerge, or the preponderance of evidence begins to point to one
interpretation rather than others. Don't expect a case analysis to yield a "final answer." If
you're accustomed to doing analysis that ends with a right answer, coming up with a
possible solution that simply reflects your best judgment might frustrate you. But
remember that cases, much like real-world business experiences, rarely reveal an
absolutely correct answer, no matter how deeply you analyze them. Typically, you'll do
qualitative analysis based on your reading and interpretation of the case. Ask yourself:
What is fact and what is opinion? Which facts are contributing to the problem? Which are
the causes?
Qualitative factors should be prioritized and fully developed to support your argument.
Make notes about your evolving interpretations, always being careful to list the evidence or
reasons that support them. Qualitative information in a case can be a mix of objective and
subjective information. For example, you may need to assess the validity of quotations from
company executives, each of whom has a subjective opinion. Reports from external
industry analysts or descriptions of what other companies in the industry have done might
seem more objective; no one in the case has a vested interest in this information. A
company's internal PowerPoint presentation should be considered separately and
differently from a newspaper article about the company. Cases mix firsthand quotations
and opinions with third-person narratives, so you need to consider the reliability of
sources. As in real life, you shouldn't take all case information at face value.
Quantitative data—such as amounts of.
The Easy Guide for Deployment Diagrams by Creately.
Risk management is a process in which risks are identified and controlled proactively. It allows businesses to improve their chances of success by minimizing threats and maximizing opportunities. Creately offers editable templates which you can use for your risk management process. A variety of different templates on Risk Management are included which you can use for each step throughout your Risk Management Process.
Also, you can find many more useful diagram templates in our diagram community and all our popular diagram templates are available for free. Just click on the "Use as Template" button to immediately start modifying it using our online diagramming tools.
The Problem Statement By Dr. Marilyn Simon Find this a.docxoscars29
The document provides information about a Monte Carlo simulation exercise to estimate the total costs of installing a backup generator at a government facility. It includes historical cost data for design, build, and test efforts and asks the reader to conduct 10 iterations of the simulation to generate a cost distribution. It then asks questions about calculating the average cost, the standard deviation of the distribution, and the probability of costs exceeding $105,000. The document provides information and examples to help calculate standard deviation.
Pareto analysis is a technique used to identify the most important causes of problems that need to be addressed. It is based on the Pareto principle (also known as the 80/20 rule), which states that roughly 80% of the effects come from 20% of the causes. Pareto analysis involves identifying problems, determining their root causes, scoring them based on frequency or impact, grouping the causes, and summing the scores to identify the vital few causes that should be prioritized to resolve the majority of problems. An example is provided of a service center manager who used Pareto analysis to identify that lack of training and too few staff were the primary root causes of customer complaints.
This document provides an introduction to statistical process control (SPC). SPC is used to monitor and control processes to maximize conforming product output while minimizing waste. The key purposes of SPC include preventing defects, indicating when corrective action is needed, and facilitating continuous process improvement. Common SPC tools described in the document are cause-and-effect diagrams, check sheets, flow diagrams, Pareto analysis, histograms, run charts, and control charts. Pareto analysis involves identifying problems, scoring them based on impact, and prioritizing addressing the highest scoring issues first. Histograms and run charts are used to analyze process variation over time. Control charts establish limits to determine whether a process is in or out of statistical control.
Seven Basic Quality Control Tools أدوات ضبط الجودة السبعةMohamed Khaled
The 7 QC tools are fundamental instruments to improve the process and product quality. They are used to examine the production process.
► The seven basic tools are:
1- Check sheet
2- Pareto analysis
3- Cause and Effect Diagram
4- Scatter plot
5- Histogram
6- Flowchart
7- Control charts
-------------------------------------------------------------------------------------
#7_Basic_Quality_Control_Tools #Check_sheet #Pareto_analysis #Fishbone #Scatter_plot #Histogram #Flowchart #Control_charts #CFturbo #Pump_simulation_using_ANSYS #Water_Hammer #أدوات_ضبط_الجودة_السبعة #نموذج_التحقق #مخطط_باريتو #مخطط_السبب_والأثر #مخطط_التشتت #مدرج_تكراري #خرائط_التدفق #خرائط_ضبط_الجودة
A power point presentation on statisticsKriace Ward
Statistics originated from Latin, Italian, and German words referring to organized states. Gottfried Achenwall is considered the "father of statistics" for coining the term to describe a specialized branch of knowledge. Modern statistics is defined as the science of judging collective phenomena through analysis and enumeration. While statistics can be an art and a science, its successful application depends on the skill of the statistician and their knowledge of the field being studied. Statistics are important across many domains from business, economics, and planning to the sciences. However, statistics also have limitations such as only studying aggregates, not individuals, and results being valid only on average and in the long run.
06-18-2024-Princeton Meetup-Introduction to MilvusTimothy Spann
06-18-2024-Princeton Meetup-Introduction to Milvus
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://github.com/milvus-io/milvus
Get Milvused!
https://milvus.io/
Read my Newsletter every week!
https://github.com/tspannhw/FLiPStackWeekly/blob/main/142-17June2024.md
For more cool Unstructured Data, AI and Vector Database videos check out the Milvus vector database videos here
https://www.youtube.com/@MilvusVectorDatabase/videos
Unstructured Data Meetups -
https://www.meetup.com/unstructured-data-meetup-new-york/
https://lu.ma/calendar/manage/cal-VNT79trvj0jS8S7
https://www.meetup.com/pro/unstructureddata/
https://zilliz.com/community/unstructured-data-meetup
https://zilliz.com/event
Twitter/X: https://x.com/milvusio https://x.com/paasdev
LinkedIn: https://www.linkedin.com/company/zilliz/ https://www.linkedin.com/in/timothyspann/
GitHub: https://github.com/milvus-io/milvus https://github.com/tspannhw
Invitation to join Discord: https://discord.com/invite/FjCMmaJng6
Blogs: https://milvusio.medium.com/ https://www.opensourcevectordb.cloud/ https://medium.com/@tspann
Expand LLMs' knowledge by incorporating external data sources into LLMs and your AI applications.
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of May 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
Do People Really Know Their Fertility Intentions? Correspondence between Sel...Xiao Xu
Fertility intention data from surveys often serve as a crucial component in modeling fertility behaviors. Yet, the persistent gap between stated intentions and actual fertility decisions, coupled with the prevalence of uncertain responses, has cast doubt on the overall utility of intentions and sparked controversies about their nature. In this study, we use survey data from a representative sample of Dutch women. With the help of open-ended questions (OEQs) on fertility and Natural Language Processing (NLP) methods, we are able to conduct an in-depth analysis of fertility narratives. Specifically, we annotate the (expert) perceived fertility intentions of respondents and compare them to their self-reported intentions from the survey. Through this analysis, we aim to reveal the disparities between self-reported intentions and the narratives. Furthermore, by applying neural topic modeling methods, we could uncover which topics and characteristics are more prevalent among respondents who exhibit a significant discrepancy between their stated intentions and their probable future behavior, as reflected in their narratives.
Discover the cutting-edge telemetry solution implemented for Alan Wake 2 by Remedy Entertainment in collaboration with AWS. This comprehensive presentation dives into our objectives, detailing how we utilized advanced analytics to drive gameplay improvements and player engagement.
Key highlights include:
Primary Goals: Implementing gameplay and technical telemetry to capture detailed player behavior and game performance data, fostering data-driven decision-making.
Tech Stack: Leveraging AWS services such as EKS for hosting, WAF for security, Karpenter for instance optimization, S3 for data storage, and OpenTelemetry Collector for data collection. EventBridge and Lambda were used for data compression, while Glue ETL and Athena facilitated data transformation and preparation.
Data Utilization: Transforming raw data into actionable insights with technologies like Glue ETL (PySpark scripts), Glue Crawler, and Athena, culminating in detailed visualizations with Tableau.
Achievements: Successfully managing 700 million to 1 billion events per month at a cost-effective rate, with significant savings compared to commercial solutions. This approach has enabled simplified scaling and substantial improvements in game design, reducing player churn through targeted adjustments.
Community Engagement: Enhanced ability to engage with player communities by leveraging precise data insights, despite having a small community management team.
This presentation is an invaluable resource for professionals in game development, data analytics, and cloud computing, offering insights into how telemetry and analytics can revolutionize player experience and game performance optimization.
1. 1
Diagrama de pareto
Angie Gabriela Bastidas Home
Gabriela Jojoa Sanchez
Danna Michel Montes Gomes
Monica yutliza Ceron Urbano
Valentina Mosquera Arenas
Valentina Vasgas Buitrago
Grado:11-5
I.E Liceo Departamental
Area De Investigación Y Desarrollo Humano
Santiago De Cali
2022
2. 2
Diagrama de pareto
Angie Gabriela Bastidas Home
Gabriela Jojoa Sanchez
Danna Michel Montes Gomes
Monica yutliza Ceron Urbano
Valentina Mosquera Arenas
Valentina Vasgas Buitrago
Grado:11-5
Guillermo Mondragon
I.E Liceo Departamental
Area De Investigación Y Desarrollo Humano
Santiago De Cali
2022
3. 3
Tabla de contenido
Portada……………………………………………………………………………………1
Contraportada……………………………………………………………………………2
Tabla de contenido………………………………………………………………………3
Desarrollo temático….…………………………………………………………………..4
Principio de Pareto………………………………………………………………………5
Qué es el diagrama de Pareto…………………………………………………………6
Comó se hace el diagrama…………………………………………………………….7
Comó hacer un Pareto en Excel- elabore un ejercicio resolviendo un problema y su
análisis……………………………………………………………………………………8
Cuál es el enfoque CTS (ciencias, tecnología y sociedad)....................................9
Mapa conceptual ……………………………………………………………………….10
Conclusiones ……………………………………………………………………………10
4. 4
DESARROLLO TEMÁTICO
En este trabajo mis compañeras y yo le vamos a presentar el tema de diagrama de pareto.
Primero se va a informar sobre el principio de pareto, lo que nos introduce a cómo se creó y
por qué lo hizo. Seguido a esto se hace saber que es este diagrama para poder comprender
mejor el tema. Después se aborda el cómo se hace el diagrama, esta explicación se da paso a
paso para poder entender cómo se realiza y desarrollarlo correctamente. Luego de tener claro
todo este concepto se presenta como se hace el diagrama en excel, de esta manera se enseña a
lo largo del trabajo como se hace de las dos maneras, tanto gráfica como numéricamente,
sumado a esto se presenta un ejemplo de todo lo que se presentó anteriormente.
Continuando con el tema se va a abordar que es el enfoque cts lo que nos informará sobre
este tipo de enfoque que está concentrado en tres puntos importantes para todos, tanto natural,
tecnologa como socialmente y nos ayudará a comprender más de que se trata. por
consiguiente se presentará un mapa conceptual del tema para una mejor comprensión y
asimilación de lo que se está hablando. Por último, se harán saber las conclusiones que se
sacaron respecto a todo el tema y lo que se investigó. Con esto llegamos al final del trabajo
sobre el diagrama de pareto, el cual se quiso llenar de información acertada y confiable.
5. 5
PRINCIPIO DE PARETO
La también conocida ley del 80/20 establece que el 80% de las consecuencias de alguna
situación o escenario se obtiene o está motivado por el 20% de las causas. En otras palabras,
el 80% de lo que tiene tu empresa hoy se debe al 20% de las acciones, actividades y recursos
del día a día.
Ahora bien, ¿es tan así? No se puede afirmar como tal completamente. Pero lo que sí es cierto
es que el reparto de los resultados no es proporcional al esfuerzo.
En cuanto a su historia, quien se refirió a este principio por primera vez fue Vilfredo Federico
Pareto en 1986, cuyo objetivo fue evidenciar el enfoque que hay que poner en las acciones
que nos generan mayores resultados para eficientarlos y optimizarlos de manera que puedan
ser obtenidos con el uso de los menores recursos posibles.
Pareto pudo reconocer patrones desequilibrados de los ingresos de su familia, en los cuales el
80% de la riqueza en su natal Italia estaba en manos del 20% de las personas: esto mismo le
llevó a extrapolar esta hipótesis a otros ambientes más allá de las finanzas.
De ello resultó una teoría o técnica sencilla para evaluar los problemas de una organización y
medir el impacto que se necesitaría para resolverlos con el objetivo de una mejor toma de
decisiones y, por supuesto, mejores resultados.
6. 6
QUE ES EL DIAGRAMA DE PARETO
Un diagrama de Pareto es una técnicaque permite clasificar gráficamente lainformación
de mayor a menor relevancia, conel objetivo de reconocer los problemas más importantes
en los que deberías enfocarte ysolucionarlos.
Esta técnicase basa en el principio de Pareto o regla80/20, lacual establece unarelación
de correspondenciaentre losgrupos 80-20, donde el 80 % de las consecuencias provienen
del 20 % de las causas.
El diagrama de Pareto, tambiénconocido comocurva de distribuciónABC, consiste en
una gráfica que clasificalos aspectos relacionados conuna problemáticay los ordenade
mayor a menor frecuencia, conlo que permite visualizar de formaclara cuál es la causa
principal de una consecuencia.
Muchos negocios no comprendenque la manera de aumentar las ganancias no siempre es
aumentando la variedad de los productos. A veces, nosotrosmismospodemos serel peor
enemigo de nuestros productos quitándole ventas para ofrecer otros.
Entonces, la funcióndel diagrama de Pareto es que las empresas puedan reconocer cuáles
sonlas necesidades más importantes alas que deberíadirigir sus esfuerzos yno
malgasten recursos enasuntos poco relevantes, de ahí la importanciade siempre hacer un
análisis de datos.
7. 7
COMO SE HACE EL DIAGRAMA
Como se hace el diagrama
El diagrama de pareto se hace de la siguiente manera:
1. Determina la situación problemática: ¿Hay un problema? ¿Cuál es?
2. Determina los problemas (causas o categorías) en torno a la situación problemática,
incluyendo el período de tiempo.
3. Recolecta datos: Hay una situación problemática presentándose y tienes las posibles
causas que lo generan, pues entonces comienza a recolectar los datos. Estos dependen
de la naturaleza del problema.
4. Ordena de mayor a menor: Ordenamos de mayor a menor las causas con base en los
datos que recolectamos y su medida.
5. Realiza los cálculos: A partir de los datos ordenados, calculamos el acumulado, el
porcentaje y el porcentaje acumulado.
6. Graficamos las causas:El eje X lo destinamos a colocar las causas. Vamos a usar eje
Y izquierdo y eje Y derecho. El izquierdo es para la frecuencia de cada causa,lo
usamos para dibujarlas con barras verticales.
7. Graficamos la curva acumulada: El eje Y derecho es para el porcentaje acumulado,
por lo tanto va desde 0 hasta 100%. Lo usamos para dibujar la curva acumulada.
8. Analizamos el diagrama.
8. 8
Diagrama de pareto
tecnologia
Con el siguiente diagrama de pareto podemos concluir, en que los principales problemas que presenta
la empresa “ LA RAPIDÍSIMA” son:
1. Clientes insatisfechos en la atención por vía telefónica.
2. Excesivas colas.
3. Mala señalización de las oficinas.
9. 9
Que es el enfoque cts
El enfoque más interesante, en torno a la incorporación de tópicos curriculares, metodologías
y estrategias CTS, es el ENFOQUE POR SITUACIONES PROBLEMAS, puesto que al
vincular una determinada temática de ciencias naturales con la efectividad este tema no queda
como una mera adquisición de conocimientos, sino que, al estar correctamente planteado,
podría contribuir a la posibilidad de este inconveniente. Por ende, al realizar esta contribución,
los temas tratados en clases son reflexionados, discutidos, investigados a fondo y expuestos
con fundamentación científica.
De acuerdo con Iuliani (s.f.), el enfoque por situaciones problemas, resume a los demás
enfoques al conectar los intereses sociales y valoraciones éticas con la selección y
secuenciación de contenidos curriculares de las clases de ciencias naturales. Al establecer estas
conexiones, la resolución de problemas en el interior del clase necesita partir de un enfoque
histórico, ya que, los y las estudiantes deben conocer los circunstancias de dichos
inconvenientes y las causas que los suscitaron, para esto es imprescindible una investigación
científica que determine adicionalmente el impacto social, ambiental, financiero, político, entre
otros, aquí es donde interviene el enfoque por relevancia.
MAPA CONCEPTUAL
10. 10
CONCLUSIONES
En conclusión podemos decir que el diagrama de Pareto permite determinar irregularidades
de una organización, identificar sus puntos de mejora y definir cuál plan de acción es
primordial para atacar sus pérdidas.
● No es conveniente que la categoría de “otros” represente un porcentaje de los más
altos. De ser así, se debe realizar un método diferente de clasificación.
● Es preferible representar los datos (si es posible) en valores monetarios.
● Si un factor se puede solucionar fácilmente debe afrontarse de inmediato aunque sea
de poca importancia.
● Es imprescindible realizar un diagrama de causas si se quieren realizar mejoras
Referencias