Measures of Central tendency-bio-statistics
Biostatistics and research methodology
Mean
Median
Mode
Mean- Arithmetic mean
weighted mean
harmonic mean
geometric mean
individual series
discrete series
continuous series
Relation between mean, median and mode
Statistical average
mathematical average
positional average
Merits and demerits of mean, median and mode
statistics
Bachelor of Pharmacy
8th Semester
Biostatistics
THIS PRESENTATION EXPLAINS MEAN DEVIATION IN A STEP BY STEP , EASY WAY.
PROBLEM FOR A DISCRETE AND GROUPED FREQUENCY DISTRIBUTION IS DISCUSSED.
IT WOULD BE USEFUL TO GRADE 11 MATH STUDENTS AND COLLEGE STUDENTS STUDYING STATISTICS.
IT IS ACCOMPANIED BY A VIDEO.
Measures of Central tendency-bio-statistics
Biostatistics and research methodology
Mean
Median
Mode
Mean- Arithmetic mean
weighted mean
harmonic mean
geometric mean
individual series
discrete series
continuous series
Relation between mean, median and mode
Statistical average
mathematical average
positional average
Merits and demerits of mean, median and mode
statistics
Bachelor of Pharmacy
8th Semester
Biostatistics
THIS PRESENTATION EXPLAINS MEAN DEVIATION IN A STEP BY STEP , EASY WAY.
PROBLEM FOR A DISCRETE AND GROUPED FREQUENCY DISTRIBUTION IS DISCUSSED.
IT WOULD BE USEFUL TO GRADE 11 MATH STUDENTS AND COLLEGE STUDENTS STUDYING STATISTICS.
IT IS ACCOMPANIED BY A VIDEO.
in biostatistics, a measure of central tendency is a single value that describes a set of data by of typical value. it is also called as average. Arithmetic meanâ or âmeanâ is the term used for average. The arithmetic mean or simply mean is the sum of the separate scores or measures divided by their number.
The lesson begins with students engaging in a review of some measures of central tendency by considering a numerical example. Students are also asked to examine both strengths and limitations of these measures. Assessments will be given to students on their ability to calculate these measures, and also to get an overall sense of whether they recognize how these measures respond to changes in data values.
STANDARD DEVIATION (2018) (STATISTICS)sumanmathews
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THIS IS A QUICK AND EASY METHOD TO LEARN STANDARD DEVIATION FOR DISCRETE AND GROUPED FREQUENCY DISTRIBUTION.
IT GIVES A STEP BY STEP, SIMPLE EXPLANATION OF PROBLEMS WITH FORMULAE.
SO WATCH THE ENTIRE VIDEO TODAY.
in biostatistics, a measure of central tendency is a single value that describes a set of data by of typical value. it is also called as average. Arithmetic meanâ or âmeanâ is the term used for average. The arithmetic mean or simply mean is the sum of the separate scores or measures divided by their number.
The lesson begins with students engaging in a review of some measures of central tendency by considering a numerical example. Students are also asked to examine both strengths and limitations of these measures. Assessments will be given to students on their ability to calculate these measures, and also to get an overall sense of whether they recognize how these measures respond to changes in data values.
STANDARD DEVIATION (2018) (STATISTICS)sumanmathews
Â
THIS IS A QUICK AND EASY METHOD TO LEARN STANDARD DEVIATION FOR DISCRETE AND GROUPED FREQUENCY DISTRIBUTION.
IT GIVES A STEP BY STEP, SIMPLE EXPLANATION OF PROBLEMS WITH FORMULAE.
SO WATCH THE ENTIRE VIDEO TODAY.
Average are generally the central part of the distribution and therefore they are also called as Measure of Central tendency. There are five types of measure of Central Tendency or averages .
Reference;Quantitative Apptitude by Dr P.N Arora,S.Arora
Wikipedia
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
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Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
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Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
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In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
DevOps and Testing slides at DASA ConnectKari Kakkonen
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My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
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As AI technology is pushing into IT I was wondering myself, as an âinfrastructure container kubernetes guyâ, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefitâs both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
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Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
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Are you looking to streamline your workflows and boost your projectsâ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, youâre in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part âEssentials of Automationâ series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Hereâs what youâll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
Weâll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Donât miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
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Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But thereâs more:
In a second workflow supporting the same use case, youâll see:
Your campaign sent to target colleagues for approval
If the âApproveâ button is clicked, a Jira/Zendesk ticket is created for the marketing design team
Butâif the âRejectâ button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Connector Corner: Automate dynamic content and events by pushing a button
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Statistics For Entrepreneurs
1. Statistics for Entrepreneurs by : DR. T.K. JAIN AFTERSCHO âș OL centre for social entrepreneurship sivakamu veterinary hospital road bikaner 334001 rajasthan, india FOR â PGPSE PARTICIPANTS mobile : 91+9414430763
6. What do you understand from Deseasonalisation of Data Removing the impact of seasonality is called deseasonalisation. Here we divide each element of data by seasonal index. Here we assume that the impact of seasonality is uniform throughout the data.
7. Example : Data for sale of Air conditioners is as under : summer 09 : 20000 winter 09: 1200 summer 2010 : 21000 seasonality index for summer is 400 and for winter is 20 thus the sale should be :20000/400 *100 = 5000 thus sale is : 5000, 6000, 5250 ...
8. What are the methods of forecasting ... Survey method / trend analysis methods / index number based methods survey can be of following types : 1. complete enumeration method 2. sample survey method in complete enumeration, we contact each person. It is also called census survey method.
9. What is delphi technique ? It is a teachnique to collect opinion of experts. Here you have to find out experts who are willing to give their projection. Then we obtain opinion of experts and try to compile their opinion. Each ideas is tested out and feasibility report is prepared. Thus final ideas is accepted on the basis of delhipi we are able to get the opinion of experts.
10. What are the smoothing methods used in statistical analysis ? In research we try to use smoothing method in order to remove vriations in data. There are mainly 2 methods for this: (i) Method of Moving Average, discussed earlier and (ii) Method of Exponential Smoothing smooth = without variations.
11. What are Barometric Technique or Lead or Lag Technique Lead and lag are those events which have close association with those variables which we want to study. Thus using statistical techniques, we can predict relation between lead / lag and the variable that we want to study. Thus we are able to search out a new variable (let us say x) which is a lead or a lag event to the variable Y that we want to predict.
12. What is the difference between laspeyre and paasche index? Laspeyre uses base year quantity paasche uses current year quantity as weights. Thus this is the only difference.
13. Do you agree : Arithmetic mean can be calculated for a distribution with open ends. Distribution means a range of data. Distribution with open end means â there is no opening no closing limit to the distribution. No â unless it is specified that it is normal distribution
14. The mean of a certain number of observations is 40. If two or more items with values 50 and 64 are added to this data, the mean rises to 42. Find the number of items in the original data. 40X + 50+64 = 42 (X+2) 40X-42X = -114+84 -2X = - 30 X = 15 answer
15. The mean salary paid per week to 1000 employees of an establishment was found to be Rs. 900. Later on, it was discovered that the salaries of two employees were wrongly recorded as Rs. 750 and 365 instead of 570 and 635. Find the corrected mean salary. Difference is : subtract (750-570) add (365-635) =270-180 = +90 divide 90/1000 = .09 so answer is : 900+.9 = 900.09
16. Find median of the observations in each of the following two cases : A : 25, 14, 28, 30, 25, 15, 32 B: 35, 20, 55, 27, 15, 40 Step 1. : arrange them Step 2 find mid position : 14,15,25,25,28,30,32 so median = 25 B : 15,20,27,35,40,55 so mid point is between 27 and 35, which is : (27+35)/2 = 31
17. Find the median of the distribution. Marks obtained 0-15 15-30 30-45 45-60 60-75 75-90 90-100 No. of students 26 34 64 76 60 30 10 Calculate CF : 26,60,124,200,260,290,300 the mid point is 150, which is in 45-60 range. =45 + (150-124) * 15/76 = 50.13 answer
18. Find median of the following data Age greater than (in yrs.) 0 10 20 30 40 50 60 70 230 218 200 165 123 73 28 8 Divide 230/2 = 115 (the values are in cumulative frequency) thus it is : between 40 to 50. =40+(123-115)*10/50 =40+1.6 = 41.6 answer
19. If the median of the distribution is Rs. 59.25, find the missing frequencies (total = 900) Wages (Rs.) 30-40 40-50 50-60 60-70 70-80 No. of Workers 120 ? 200 ? 185 First missing value is X 50+ (450-(120+x))*10/200 = 59.25 330-x = 185 -X =-145 or X = 145 total of all known values is 650 second value is 900-650 = 250 answer. :
20. Find mode in the above table : by observation it is 13 (highest frequency is 100 so this is mode), but if you prepare telly bars, the answer will be different. Since 13 is not the mid point and frequencies after this are constantly high, and frequencies below it are low, so we have to use telly bars to find exact mode. Based on this the answer is 14
22. Solution Formula : L1 + (f1-f0) / ((f1-0)+(f1-f2) * interval L1= lower limit of the modal class F1 = the value of highest frequency F0 = just before the modal class F2=just after the modal class =45+ (18-12) / ((18-12) +(18-14)) * 5 =45+6/10 * 5 = 45+3 = 48 answer
23. Mode and median are 75 and 60 what is mean? Mean â mode = 3 (mean â median) X-75= 3(X-60) X-3X = -180+75 -2X = -105 X = 52.5 answer
25. Solution 1. first of all calculate mean and median so that we can solve this problem. 2 then find difference of each value from the mean / median 3. square the values and total them up
27. Find mean deviation ? X : 10 11 12 13 F : 3 12 18 12 find mean, find its difference, multily difference with F and find the average : (30+132+216+156)/45 =547/45 =12.16 2.16, 1.16, .16,.84 multiply these to frequencies : (6.48+13.92+2.89+10.08)/45= .74 ans
29. Price of a commodity went up by 6%, 10% and 15% respectively, in the last three years. What is the annual average change of price? Let us assume the price was 100, it went up to 106 after 1 year and (106)*110/100 = 116.6, now it went up to : 116 * 115/100 = 134.9 the average growth is : (1.349)^/1/3 = 1.1 thus 10% approximately OR first multiply 1.06*1.1*1.15 and find cubic root (as there are 3 values) of the resulting number.
30. Calculate the range and its coefficient from the following data : 159, 165, 140, 125, 110, 170, 132, 150 Range = (highest â least value) =170-110= 60 Coefficient of range = 60 / (170+110) =60/280 * 100 = 21.4%
31. There are 60 male and 40 female workers in a factory. The standard deviation of their wages (per hour) were computed as Rs. 8 and 11 respectively. The mean wages of the two groups were found to be equal. Compute the combined standard deviation of the Wages of all the workers. Combined mean= (60*X+40X)/100 = X =sqrt((60*64)+(40*121)/100) =sqrt((3840+4840)/100)=sqrt(86.8) =9.31 answer (mean of both groups is same â so there is no need to calculate combined mean and the value is zero in formula).
32. The mean, standard deviation and range of a symmetrical distribution of weights of a group of 20 boys are 40, 5 and 6 Kgs. respectively. Find the mean and standard deviation of the group if the lightest and the heaviest boys are excluded. Highest value : 40+3 = 43, least value = 37 (assuming rage to be eqully spread). Mean will remain same. old variance : 25 Total of variance = 25*20 = 500 less variance of excluded value : (9+9) = 482 482/18 =26.78, its square root = 5.17, so new standard deviation is 5.17 ans.
33. For a group of 30 male workers, the mean and standard deviation of weekly overtime work (number of hours) are 10 and 4 respectively. For another group 20 female workers, the mean and standard deviation of weekly overtime work are 5 and 3 respectively. Calculate combined mean & Std. Deviation. Combined mean = ((30*10)(20*5)/(30+20)) =8 combined variance= ((30*16)+(20*9)/50 + (30*4)+(20*9)/50) ) =19.2 combined st.dev.= 4.38 answer
34. THANKS.... GIVE YOUR SUGGESTIONS AND JOIN AFTERSCHOOOL NETWORK / START AFTERSCHOOOL SOCIAL ENTREPRENEURSHIP NETWORK IN YOUR CITY [email_address] PGPSE â WORLD'S MOST COMPREHENSIVE PROGRAMME IN SOCIAL ENTREPRENEURSHIP