This document provides an overview of key concepts in descriptive statistics, including measures of center, variation, and relative standing. It discusses the mean, median, mode, range, standard deviation, z-scores, percentiles, quartiles, interquartile range, and boxplots. Formulas and properties of these statistical concepts are presented along with guidelines for interpreting and applying them to describe data distributions.
This will help you to understand the basic statistics particularly Discriptive Statistics.
Basic terminologies used in statistics,measure of central tendancy,measure of frequency,measure of dispersion.
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Tools and Techniques - Statistics: descriptive statistics Ramachandra Barik
Tools and Techniques - Statistics: descriptive statistics - See more at: http://www.pcronline.com/eurointervention/67th_issue/volume-9/number-8/167/tools-and-techniques-statistics-descriptive-statistics.html#sthash.rtzcQ3ah.dpuf
This will help you to understand the basic statistics particularly Discriptive Statistics.
Basic terminologies used in statistics,measure of central tendancy,measure of frequency,measure of dispersion.
#nafeesupdates
#nafeesmedicos
Tools and Techniques - Statistics: descriptive statistics Ramachandra Barik
Tools and Techniques - Statistics: descriptive statistics - See more at: http://www.pcronline.com/eurointervention/67th_issue/volume-9/number-8/167/tools-and-techniques-statistics-descriptive-statistics.html#sthash.rtzcQ3ah.dpuf
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
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.
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!
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.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
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.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
1. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by Mario F. Triola
2. Chapter 3 Statistics for Describing, Exploring, and Comparing Data 3-1 Review and Preview 3-2 Measures of Center 3-3 Measures of Variation 3-4 Measures of Relative Standing and Boxplots
3. Created by Tom Wegleitner, Centreville, Virginia Section 3-1 Review and Preview
8. Key Concept Characteristics of center. Measures of center, including mean and median, as tools for analyzing data. Not only determine the value of each measure of center, but also interpret those values.
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16. Finding the Median 1. If the number of data values is odd, the median is the number located in the exact middle of the list. 2. If the number of data values is even, the median is found by computing the mean of the two middle numbers. First sort the values (arrange them in order), the follow one of these
17. 5.40 1.10 0.42 0.73 0.48 1.10 0.66 0.42 0.48 0.66 0.73 1.10 1.10 5.40 (in order - odd number of values) exact middle MEDIAN is 0.73 5.40 1.10 0.42 0.73 0.48 1.10 0.42 0.48 0.73 1.10 1.10 5.40 0.73 + 1.10 2 (in order - even number of values – no exact middle shared by two numbers) MEDIAN is 0.915
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27. Weighted Mean When data values are assigned different weights, we can compute a weighted mean . x = w ( w • x )
63. Key Concept This section introduces measures of relative standing, which are numbers showing the location of data values relative to the other values within a data set. They can be used to compare values from different data sets, or to compare values within the same data set. The most important concept is the z score . We will also discuss percentiles and quartiles, as well as a new statistical graph called the boxplot.
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67. Interpreting Z Scores Whenever a value is less than the mean, its corresponding z score is negative Ordinary values: –2 ≤ z score ≤ 2 Unusual Values: z score < –2 or z score > 2
68. Percentiles are measures of location. There are 99 percentiles denoted P 1 , P 2 , . . . P 99 , which divide a set of data into 100 groups with about 1% of the values in each group.
69. Finding the Percentile of a Data Value Percentile of value x = • 100 number of values less than x total number of values
70. n total number of values in the data set k percentile being used L locator that gives the position of a value P k k th percentile Notation Converting from the k th Percentile to the Corresponding Data Value L = • n k 100
78. Boxplots - Normal Distribution Normal Distribution: Heights from a Simple Random Sample of Women
79. Boxplots - Skewed Distribution Skewed Distribution: Salaries (in thousands of dollars) of NCAA Football Coaches
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83. Outliers for Modified Boxplots For purposes of constructing modified boxplots , we can consider outliers to be data values meeting specific criteria. In modified boxplots, a data value is an outlier if it is . . . above Q 3 by an amount greater than 1.5 IQR below Q 1 by an amount greater than 1.5 IQR or
84. Modified Boxplots Boxplots described earlier are called skeletal (or regular ) boxplots. Some statistical packages provide modified boxplots which represent outliers as special points.
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86. Modified Boxplots - Example Pulse rates of females listed in Data Set 1 in Appendix B.