Search results “Analysis of data sample”

Qualitative research is a strategy for systematic collection, organization, and interpretation of phenomena that are difficult to measure quantitatively. Dr. Leslie Curry leads us through six modules covering essential topics in qualitative research, including what it is qualitative research and how to use the most common methods, in-depth interviews and focus groups. These videos are intended to enhance participants' capacity to conceptualize, design, and conduct qualitative research in the health sciences. Welcome to Module 5.
Bradley EH, Curry LA, Devers K. Qualitative data analysis for health services research:
Developing taxonomy, themes, and theory. Health Services Research, 2007; 42(4):1758-1772.
Learn more about Dr. Leslie Curry
http://publichealth.yale.edu/people/leslie_curry.profile
Learn more about the Yale Global Health Leadership Institute
http://ghli.yale.edu

Views: 150000
YaleUniversity

In this video Dr. Ziene Mottiar, DIT, discusses issues around analyzing data and writing the analysing chapter. The difference between Findings and Analysis chapters is also discussed. This video is useful for anyone who is writing a dissertation or thesis.

Views: 65416
ZieneMottiar

Excerpt from Summer 2008 workshop titled "Integrating Cultural and Ethnic Influences on Mental Health" as part of the Collaborative Psychiatric Epidemiology Surveys (CPES) project.
Patricia Berglund, Harvard Medical School
PowerPoint files are available here: http://www.icpsr.umich.edu/files/CPES/berglund.ppt

Views: 4231
ICPSR

Visit us at http://www.statisticshowto.com for more Excel and statistics videos and tips.

Views: 19958
Stephanie Glen

Note for December 2018: Please support this project (I did):
https://www.gofundme.com/hjalpa-pa-plats
The guy behind it is Luai, and you can watch him in this video (only Swedish): https://www.youtube.com/watch?v=fKcb1Tfuoqs
The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends.
The steps are also described in writing below (Click Show more):
STEP 1, reading the transcripts
1.1. Browse through all transcripts, as a whole.
1.2. Make notes about your impressions.
1.3. Read the transcripts again, one by one.
1.4. Read very carefully, line by line.
STEP 2, labeling relevant pieces
2.1. Label relevant words, phrases, sentences, or sections.
2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant.
2.3. You might decide that something is relevant to code because:
*it is repeated in several places;
*the interviewee explicitly states that it is important;
*you have read about something similar in reports, e.g. scientific articles;
*it reminds you of a theory or a concept;
*or for some other reason that you think is relevant.
You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you.
It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds.
STEP 3, decide which codes are the most important, and create categories by bringing several codes together
3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand.
3.2. You can create new codes by combining two or more codes.
3.3. You do not have to use all the codes that you created in the previous step.
3.4. In fact, many of these initial codes can now be dropped.
3.5. Keep the codes that you think are important and group them together in the way you want.
3.6. Create categories. (You can call them themes if you want.)
3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever.
3.8. Be unbiased, creative and open-minded.
3.9. Your work now, compared to the previous steps, is on a more general, abstract level. You are conceptualizing your data.
STEP 4, label categories and decide which are the most relevant and how they are connected to each other
4.1. Label the categories. Here are some examples:
Adaptation (Category)
Updating rulebook (sub-category)
Changing schedule (sub-category)
New routines (sub-category)
Seeking information (Category)
Talking to colleagues (sub-category)
Reading journals (sub-category)
Attending meetings (sub-category)
Problem solving (Category)
Locate and fix problems fast (sub-category)
Quick alarm systems (sub-category)
4.2. Describe the connections between them.
4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study.
STEP 5, some options
5.1. Decide if there is a hierarchy among the categories.
5.2. Decide if one category is more important than the other.
5.3. Draw a figure to summarize your results.
STEP 6, write up your results
6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results.
6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example:
*results from similar, previous studies published in relevant scientific journals;
*theories or concepts from your field;
*other relevant aspects.
STEP 7 Ending remark
Nb: it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.)
Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze:
*notes from participatory observations;
*documents;
*web pages;
*or other types of qualitative data.
STEP 8 Suggested reading
Alan Bryman's book: 'Social Research Methods' published by Oxford University Press.
Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE.
Text and video (including audio) © Kent Löfgren, Sweden

Views: 677716
Kent Löfgren

Quick Data Analysis Workflow from data import, visual data inspection to dashboard presentation and more ...

Views: 615
ANKHORFlowSheet

We check the significance of the difference in means between 2 samples using a T Test (in Excel).
Dataset can be downloaded at www.learnanalytics.in/blog/wp-content/uploads/2014/02/car_sales.xlsx

Views: 13461
Learn Analytics

Data Analysis with Javascript and Chartjs - Part 1 (Getting a Sample)
In This Video Ive chosen a dataset that has all of the Companies committed to RechargeNY. Ive Taken A sample Of All of The Companies in Brooklyn and added it To a Single Array
Check Out Recharge NY
and follow along!
Knowledge of Basic Programming is required....

Views: 502
Ty Reddick

Using a student's data, I show you how you can create some simple visuals, how to deal with some of the tricky parts of data formatting and some basic calculations to produce. Formatting can always be the save or the impediment when working in Excel. If you have troubles with time and date formats, you may simply have to reset the formats or even retype some data.

Views: 174
Heidi Baez

If you don't know how to install the Data Analysis Toolpak (PCs only), check the other video I uploaded. Here, the Data Analysis add-on to Excel 2007 (PC) is used to perform a two sample t-test. You might be able to get similar results just as easily with the Mac version and StatPlus, but I'm not sure. I doubt it.
I didn't show this in the video, but the original data is on Sheet 1. The Data Analysis output goes on a new sheet (Sheet 2).

Views: 4604
UIUCEconTA

Get 15% Promo code: https://goo.gl/TIo1T2?52513

Views: 1
Степан Меркушев

AUTHORS:
V. Pawlowsky-Glahn and J.J. Egozcue
SPEAKER:
V. Pawlowsky-Glahn
EVENT:
Probabilistic Microbial Modeling Symposium
San Diego (USA)
June 21-22, 2018
DESCRIPTION:
The sample space of observed data is usually explicitly or implicitly assumed to be the multidimensional real space or a subset of the same. In both cases the geometry is taken to be the usual Euclidean geometry. This basic aspect plays an essential role in the analysis of data, and very specially in the case of compositional data, where it can lead to spurious results or to poor approximations. We present a summary of the present attempts to analyse compositional data in the field of microbiome data, as well as the implications of the different approaches.

Views: 51
Escola Politècnica Superior - UdG

Views: 2314
harsh mistry

This video is part of a course at Simon Fraser University and is intended for students in the course. In it, students will learn how to prepare their data to allow proper analysis accounting for the complex sampling design of NHANES.

Views: 9131
Scott Venners

Lecture by professor Tom Freeman
Filmed during a half-day training course held at The Roslin Institute, January 2015
(Recommended Youtube playback settings for the best viewing experience: 1080p HD)
*********************************
Content list:
9. Network analysis of Expression data – sample-sample correlation graph 1 (Practical Session)
Example dataset 2 – GNF mouse tissue atlas dataset
- minimum correlation setting
- preprocessing; transpose data
- graph topology

Views: 131
The Roslin Institute - Training

Download data analysis venn digram questions
http://careerstudydefence.com/afcat-reasoning-3/

Views: 3353
Career Study

Seven different statistical tests and a process by which you can decide which to use.
The tests are:
Test for a mean,
test for a proportion,
difference of proportions,
difference of two means - independent samples,
difference of two means - paired,
chi-squared test for independence and
regression.
This video draws together videos about Helen, her brother, Luke and the choconutties.
There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.

Views: 695339
Dr Nic's Maths and Stats

BROWSE The Internet EASY way with The Audiopedia owned Lightina Browser Android app! INSTALL NOW - https://play.google.com/store/apps/details?id=com.LightinaBrowser_8083351
What is DESCRIPTIVE STATISTICS? What does DESCRIPTIVE STATISTICS mean? DESCRIPTIVE STATISTICS meaning - DESCRIPTIVE STATISTICS definition - DESCRIPTIVE STATISTICS explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
Descriptive statistics are statistics that quantitatively describe or summarize features of a collection of information. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. This generally means that descriptive statistics, unlike inferential statistics, are not developed on the basis of probability theory. Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented. For example in papers reporting on human subjects, typically a table is included giving the overall sample size, sample sizes in important subgroups (e.g., for each treatment or exposure group), and demographic or clinical characteristics such as the average age, the proportion of subjects of each sex, the proportion of subjects with related comorbidities etc.
Some measures that are commonly used to describe a data set are measures of central tendency and measures of variability or dispersion. Measures of central tendency include the mean, median and mode, while measures of variability include the standard deviation (or variance), the minimum and maximum values of the variables, kurtosis and skewness.
Descriptive statistics provide simple summaries about the sample and about the observations that have been made. Such summaries may be either quantitative, i.e. summary statistics, or visual, i.e. simple-to-understand graphs. These summaries may either form the basis of the initial description of the data as part of a more extensive statistical analysis, or they may be sufficient in and of themselves for a particular investigation.
For example, the shooting percentage in basketball is a descriptive statistic that summarizes the performance of a player or a team. This number is the number of shots made divided by the number of shots taken. For example, a player who shoots 33% is making approximately one shot in every three. The percentage summarizes or describes multiple discrete events. Consider also the grade point average. This single number describes the general performance of a student across the range of their course experiences.
The use of descriptive and summary statistics has an extensive history and, indeed, the simple tabulation of populations and of economic data was the first way the topic of statistics appeared. More recently, a collection of summarisation techniques has been formulated under the heading of exploratory data analysis: an example of such a technique is the box plot.
In the business world, descriptive statistics provides a useful summary of many types of data. For example, investors and brokers may use a historical account of return behavior by performing empirical and analytical analyses on their investments in order to make better investing decisions in the future.
Univariate analysis involves describing the distribution of a single variable, including its central tendency (including the mean, median, and mode) and dispersion (including the range and quantiles of the data-set, and measures of spread such as the variance and standard deviation). The shape of the distribution may also be described via indices such as skewness and kurtosis. Characteristics of a variable's distribution may also be depicted in graphical or tabular format, including histograms and stem-and-leaf display.

Views: 11721
The Audiopedia

This video shows how to conduct a one-sample hypothesis t-test for the mean in Microsoft Excel using the built-in Data Analysis (from raw data).
How to load Data Analysis in Excel: https://youtu.be/SqpSwxJ9t2k

Views: 81098
Joshua Emmanuel

Exploring some basic data analysis in excel

Views: 44213
Jon Jasinski

Views: 52
Darren Morton

This video is part of the University of Southampton, Southampton Education School, Digital Media Resources
http://www.southampton.ac.uk/education
http://www.southampton.ac.uk/~sesvideo/

Views: 189293
Southampton Education School

The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples.
Subtitles in English and Spanish.

Views: 799164
Dr Nic's Maths and Stats

This video demonstrates a sample data analysis using the data described in our second video. Here we perform an "in silico Northern" using grep.

Views: 1164
David Coil

Relative and absolute methods of qPCR analysis. Created for an assignment for BIOC3001: Molecular Biology at the University of Western Australia.
****SCRIPT**** [I know it's a bit fast]
qPCR or quantitative real-time PCR…
….is simply classic PCR monitored using fluorescent dyes or probes.
qPCR is accurate, reliable and extremely sensitive, it can even detect a SINGLE copy of a specific transcript.
qPCR is commonly coupled to reverse transcription to measure gene expression.
No wonder it is so important for molecular diagnostics, life sciences, agriculture, and medicine.
Firstly, let's go over the NUTS and BOLTS of qPCR. For this you use a fluorescent dye which binds to the DNA. As qPCR progresses, the fluorescent signal increases.
Ideally the signal should double with every cycle, which is then plotted.
Because there are few template strands to start with, initially there’s a faint signal.
Eventually, usually after 15 cycles, the signal rises above the background noise and can be detected. We call this the THRESHOLD CYCLE, Ct, the point from which all quantitative data analysis begins.
But how do you analyse qPCR data?
You can either use an absolute quantification method, with a standard curve, OR a relative method, using one or more reference genes to standardize and compare the differences in Ct values between two treatments.
The absolute standard curve method determines ORIGINAL DNA concentration by comparing the Ct value of the sample of interest with a standard curve.
To create the standard curve, you need to make DNA samples of different KNOWN concentrations.
After doing PCR on these, you will see different PCR plots for each standard …..
and unsurprisingly they have different Ct values. The GREATER the concentration of the original DNA sample, the SMALLER the Ct value.
So if you plot ORIGINAL DNA concentration against the Ct values. You will have a standard curve like this…..
Now let’s say the PCR plot of your unknown DNA sample is somewhere here…..
...which corresponds to this Ct value on the standard curve here….
Using the standard curve you can figure out the log concentration of your DNA sample to be x.
As this is in log scale, you can simply calculate your sample DNA concentration to be 10 to the power of x.
Absolute analysis is suitable when you want to determine the ACTUAL transcript copy number, that is the level of gene expression.
On the other hand, Relative quantification is used when you want to COMPARE the difference in gene expression BETWEEN two treatments, for example light or dark treated Arabadopsis thaliana.
This is done using one or more reference genes, such as actin, which are expressed at the SAME level for both treatments.
You then perform qPCR on both your samples and the reference genes, find out the DIFFERENCE between the two Cts values, delta Ct, in EACH treatment.
Now the RATIO of the two delta Cts …[pause a bit] . tells you how much gene expression has changed.
For instance, in the dark treatment, the Ct value of your reference gene is at THIS level, the Ct value of your target gene is THIS Level. So you have this delta Ct which is the difference in Cts in the first treatment.
in the dark treatment, the Ct value of your reference gene is STILL at THIS level, but the Ct value of your target gene may become only this much.
So the ratio of the two Ct values is..
delta Ct(dark treatment) divided by delta Ct(light treament) equals one third
….showing the delta Ct has DECREASED by a factor of 3, which means that gene expression of the target gene is GREATER in the dark treated sample.
This is how relative quantification using a reference gene helps detect change in the expression of your target gene.
In conclusion, there are two ways to quantify transcripts using qPCR: absolute quantification using a standard curve, and relative quantification using a reference gene.
The method used depends on whether you want to determine the ACTUAL number of transcripts or the RELATIVE change in gene expression.

Views: 183771
TARDIStennant

This short video details how to generate a random sample of data values using Excel's Data Analysis Toolpak. In particular, we generate two types of random sample. The first being a pure random sample, and the second being a systematic or periodic sample.

Views: 339
Maths and Stats

Speaker: Vera Pawlowsky-Glahn
Abstract:
The sample space of observed data is usually explicitly or implicitly assumed to be the multidimensional real space or a subset of the same. In both cases the geometry is taken to be the usual Euclidean geometry. This basic aspect plays an essential role in the analysis of data, and very specially in the case of compositional data, where it can lead to spurious results or to poor approximations. We present a summary of the present attempts to analyze compositional data in the field of microbiome data, as well as the implications of the different approaches.

Views: 201
Jamie Morton

Science and Engineering Practice 3:
Analyzing and Interpreting Data
Paul Andersen explains how scientists analyze and interpret data. Data can be organized in a table and displayed using a graph. Students should learn how to present and evaluate data.
Intro Music Atribution
Title: I4dsong_loop_main.wav
Artist: CosmicD
Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/
Creative Commons Atribution License

Views: 59889
Bozeman Science

This video demonstrates how to use the “z-Test: Two Samples for Means” analysis in Microsoft Excel. This z-test analysis is used to determine if there is a statistically significant difference between two sets of scores when the population variance is known.

Views: 16043
Dr. Todd Grande

In this video you will learn how to perform a single sample diversity analysis on processed metagenomics data in a BioNumerics Seven database.

Views: 1655
BioNumerics

***This is an updated version of the Retail Analysis Sample video.***
Explore the Retail Analysis Sample, based on real data from obviEnce (http://www.obvience.com), and learn the ins and outs of Power BI while you are at it!
Sign up for the Power BI Preview at https://powerbi.com/dashboards and log in at https://app.powerbi.com

Views: 4903
Microsoft Power BI

Epi Info 7 allows users to rapidly develop questionnaires, customize data entry, analyze data and create custom reports. As part of the CDC's supported data tools, Epi Info provides interactive analysis of surveillance system data. Epi Info features case cluster mapping using Google maps, contact tracing using social network diagrams, SQL Server compatibility for large databases and multiuser applications, requires no IT support to install and future compatibility with hand-held devices.
Comments on this video are allowed in accordance with our comment policy: http://www.cdc.gov/SocialMedia/Tools/CommentPolicy.html
This video can also be viewed at
http://www.cdc.gov/ophss/csels/videos/epiinfo/18/18_Epi_Info_7_Complex_sample_analysis_low_res.mp4

Views: 2913
Centers for Disease Control and Prevention (CDC)

This video shows how to conduct a one-sample hypothesis z-test for the mean in Microsoft Excel using the built-in Data Analysis (from raw data).
How to load Data Analysis in Excel: https://youtu.be/SqpSwxJ9t2k
Data used:
Age
25
30
23
21
24
22
24
25
22
21
22
18
20
24
24
22
23
19
21
20
21
21
19
21
19
24
20
20
20
23
22
23
19
22
19

Views: 40395
Joshua Emmanuel

Views: 414
harsh mistry

Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ
This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.

Views: 1385551
Research By Design

Excel file: https://dl.dropboxusercontent.com/u/561402/TTEST.xls
In this video Paul Andersen explains how to run the student's t-test on a set of data. He starts by explaining conceptually how a t-value can be used to determine the statistical difference between two samples. He then shows you how to use a t-test to test the null hypothesis. He finally gives you a separate data set that can be used to practice running the test.
Do you speak another language? Help me translate my videos:
http://www.bozemanscience.com/translations/
Music Attribution
Intro
Title: I4dsong_loop_main.wav
Artist: CosmicD
Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/
Creative Commons Atribution License
Outro
Title: String Theory
Artist: Herman Jolly
http://sunsetvalley.bandcamp.com/track/string-theory
All of the images are licensed under creative commons and public domain licensing:
1.3.6.7.2. Critical Values of the Student’s-t Distribution. (n.d.). Retrieved April 12, 2016, from http://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm
File:Hordeum-barley.jpg - Wikimedia Commons. (n.d.). Retrieved April 11, 2016, from https://commons.wikimedia.org/wiki/File:Hordeum-barley.jpg
Keinänen, S. (2005). English: Guinness for strenght. Retrieved from https://commons.wikimedia.org/wiki/File:Guinness.jpg
Kirton, L. (2007). English: Footpath through barley field. A well defined and well used footpath through the fields at Nuthall. Retrieved from https://commons.wikimedia.org/wiki/File:Footpath_through_barley_field_-_geograph.org.uk_-_451384.jpg
pl.wikipedia, U. W. on. ([object HTMLTableCellElement]). English: William Sealy Gosset, known as “Student”, British statistician. Picture taken in 1908. Retrieved from https://commons.wikimedia.org/wiki/File:William_Sealy_Gosset.jpg
The T-Test. (n.d.). Retrieved April 12, 2016, from http://www.socialresearchmethods.net/kb/stat_t.php

Views: 419011
Bozeman Science

Principal Component Analysis, is one of the most useful data analysis and machine learning methods out there. It can be used to identify patterns in highly complex datasets and it can tell you what variables in your data are the most important. Lastly, it can tell you how accurate your new understanding of the data actually is.
In this video, I go one step at a time through PCA, and the method used to solve it, Singular Value Decomposition. I take it nice and slowly so that the simplicity of the method is revealed and clearly explained.
If you are interested in doing PCA in R see: https://youtu.be/0Jp4gsfOLMs
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt...
https://teespring.com/stores/statquest
...or buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/

Views: 149343
StatQuest with Josh Starmer

It’s easy to get lost in a lot of text-based data. NVivo is qualitative data analysis software that provides structure to text, helping you quickly unlock insights and make something beautiful to share.
http://www.qsrinternational.com

Views: 118693
NVivo by QSR

This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000

Views: 285183
Udacity

This presentation describes an approach to analyze a case study - especially case studies from management discipline.
Dr. Pradeep Racherla, Program Director & Associate Professor Marketing, Woxsen School of Business, elucidates different components of a case study and offers a framework to analyze a case study.

Views: 167422
Sanjay

This a sample for analyzing a volunteers data and their statistics in different kind of skills(the legend and labels are in Arabic)

Views: 12
Hani Mounla

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Views: 331535
Free Coaching @ talentsprint.com/examprep

Datalab setup in the google Cloud platform and sample data analysis in datalab by Dr N Senthil Madasamy Associate Professor

Views: 109
Dr. N. Senthil Madasamy

Metabolomics is the comprehensive analysis of endogenous metabolites in biological specimens. Metabolomics technologies are increasingly used to study metabolism in model systems and for discovery of disease signatures using samples from clinical cohorts. It is a technically challenging field owing to the wide dynamic of concentrations that must be measured as well as the diversity of physical properties among the molecules that constitute the metabolome, for example ranging from polar and acidic compounds of the TCA cycle to nonpolar and neutral compounds like triglycerides. Liquid chromatography tandem mass spectrometry (LC-MS) is an analytical technology that is well matched to this challenge and has found wide use in the field.
In this webinar, Dr. Clary Clish (Broad Institute of MIT and Harvard) will discuss scientific challenges posed by metabolomics and LC-MS-based measurements and provide an overview of LC-MS workflows. He will describe the utility and limitations of LC-MS methods, what information can be obtained from each, and how to match techniques with experimental questions about the metabolome.
What you will learn in this webinar:
The primary challenges encountered in LC-MS-based metabolomics
Methods for preparing samples, including quality measures
The types of information that can be obtained using this method
Who should attend:
Those needing a more complete understanding of the complexities involved in LC-MS-based metabolomics
Bench scientists and clinicians who need to become knowledgeable about designing experiments or studies in which metabolomics will be used
View more webinars on currentprotocols.com!

Views: 19109
CurrentProtocols

An overview of the process of qualitative data analysis based on Alan Bryman's four stages of analysis.
Reference
Bryman, A (2001) Social Research Methods, Oxford: Oxford University Press
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
http://creativecommons.org/licenses/by-nc-sa/4.0/

Views: 194088
Graham R Gibbs

Download files: http://people.highline.edu/mgirvin/excelisfun.htm
Topics in this video:
1. (00:12) Review Handwritten PDF Notes about Probability, Random Events, Sample Points, Sample Space, Count Rule For Size of Sample Space, Listing all Sample Points with Tree Diagram and Table, Methods of Probability such as Classical, Relative Frequency and Subjective, Requirements for Probability, Events and Probability of Events
2. (14:30) In Excel: Experiment of Flipping Coin Three Times: Find all Sample Points, Calculate Probabilities and practice finding Probabilities of Events by listing all the sample points and then adding all the probabilities for each Sample Point to get the Probability of the Event
3. (21:09) Frequency Distribution Built from Sample Space in order to find Probabilities for Events
4. (23:46) In Excel: Experiment of Rolling Two Die: Find all Sample Points, Calculate Probabilities and practice finding Probabilities of Events by listing all the sample points and then adding all the probabilities for each Sample Point to get the Probability of the Event

Views: 14674
ExcelIsFun

Primary teaching personal statements examples

Scientific dissertation discussion

The biggest resume mistake you can make

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Diving Boards. Pool Decks. A simple and classic look to surround your pool. Colored and stamped concrete. multiple colors and stamp patterns are available Concrete cantilever edge. Add a beautiful finished concrete edge around your pool Rubber safety surfacing. A gorgeous slip resistant safety surface for your pool area or patio Barkman pavers. Be Inspired. POOL CLEANERS. Create atmosphere with pool lights and controls on your pool. From a simple white light to multiple-multi color LED lights to create a light show in your back yard, we have a pool lighting system to elevate your pool after dark. The walk in pool stair is a must for any in ground pool. Whether you want a simple white walk in stair or a jetted lagoon stair, the stair is not only for the ease of access into the pool but a gathering place in your pool for friends and family. Safety Covers.