Search results “Confidence interval interpretation”

CORRECTION: Although my mistake is beyond the scope of the Step 1 exam, the interpretation of Confidence Interval that I used in the video is incorrect & a bit oversimplified. I stated that for an individual study there is a 95% chance that the true value lies within the 95% CI. However, confidence interval is a type of frequentist inference and the interpretation I gave in the video is really better suited for interpreting statistics of Bayesian Inference (Again please don’t feel like you need to know these terms for the exam). What I should have said is something like “if 100 similarly designed studies use a 95% confidence interval then 95 of these intervals will contain the true value and 5 will not. For more info on this misconception click here https://en.wikipedia.org/wiki/Bayesian_inference
A Confidence Interval (CI) is the range of values the true value in the population is expected to fall within based on the study results. The results we receive in any study do not perfectly mirror the overall population and the confidence interval lets us get a better idea of what the results in the overall population might be. The confidence interval is based on a certain level of confidence. Don't get this confused with the value of the sample population. If the measured BMI in 100 people in your study population and the mean is 25 than you are very confident that the actual mean BMI in that group is 25. Confidence interval only comes into play when you try to extrapolate your study results to other situations (like to the population overall).
If you have a 95% confidence interval (which is most common) that means there is a 95% chance that the true value lies somewhere in the confidence interval. You can also alter the width of the confidence interval by selecting a different percentage of confidence. 90% & 99% are also commonly used. A 99% confidence interval is wider (has more values) than a 95% confidence interval & 90% confidence interval is the most narrow.
The width of the CI changes with changes in sample size. The width of the confidence interval is larger with small sample sizes. You don't have enough data to get a clear picture of what is going on so your range of possible values is wider. Imagine your study on a group of 10 individuals shows an average shoe size of 9. If based on the results you are 95% sure that the actual average shoe size for the entire population is somewhere in between 6 and 12, then the 95% CI is 6-12. Based just on your results you don't really know what the average in the population is, because your study population is a very small sliver of the overall population. Now if you repeat the study with 10,000 individuals and you get an average shoe size of 9 the confidence interval is going to be smaller (something like 8.8 to 9.3). Here you have a much larger sample size and therefore your results give you a much clearer idea of what is going on with the entire population. Therefore, your 95% CI shrinks. The width of the confidence interval decreases with an increasing sample size (n). This is sort of like the standard deviation decreasing with an increased sample size.
Confidence intervals are often applied to RR & OR. For example, the odds ratio might be 1.2, but you aren't sure how much of an impact chance had on determining that value. Therefore, instead of just reporting the value of 1.2 you also report a range of values where the true value in the population is likely to lie. So we would report something like the odds ratio is 1.2 and we are 95% confident that the true value within the overall population is somewhere between .9 and 1.5.
You can use the confidence interval to determine statistical significance similar to how you use the p-Value. If the 95% confidence interval crosses the line of no difference that is the same things as saying there is a p-value of greater than 5%. This is intuitive because if the confidence interval includes the value of no difference then there is a reasonable chance that there is no difference between the groups. If the confidence interval does not cross the line of no difference than the observed difference is statistically significant, because you know it is highly unlikely that the two groups are the same.
For both relative risk (RR) and odds ratio (OR), the "line of no difference" is 1. So an RR or OR of 1 means there is no difference between the two groups being compared with respect to what you are measuring. This is because RR and OR are ratios and a value divided by itself is 1. If the 95% confidence interval of the RR or OR includes the value 1, that means it is possible the true value is 1 and there is no difference between groups. If that is the case, we say the null hypothesis cannot be rejected or that there is no statistically significant difference shown. This is the same thing as saying the p-value is greater than .05.

Views: 209509
Stomp On Step 1

Interpreting confidence level example.
View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/introduction-confidence-intervals/v/interpreting-confidence-intervals-example?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics
AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics.
Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today!
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Views: 24088
Khan Academy

This short video gives an explanation of the concept of confidence intervals, with helpful diagrams and examples.
Find out more on Statistics Learning Centre: http://statslc.com or to see more of our videos: https://wp.me/p24HeL-u6

Views: 711580
Dr Nic's Maths and Stats

Interpretation of Confidence Intervals

Views: 96386
Tess St. John

Interpreting a confidence interval for the population mean mu. Some reasonable interpretations are discussed, as are some common misconceptions. Many of these concepts hold for confidence intervals for other parameters.

Views: 25965
jbstatistics

Discusses the meaning of a 95% confidence interval. Part 1 of 2.
Made by faculty at the University of Colorado Boulder, Department of Chemical & Biological Engineering.
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Views: 48703
LearnChemE

Confidence intervals and margin of error.
View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/introduction-confidence-intervals/v/confidence-intervals-and-margin-of-error?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics
AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics.
Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today!
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Khan Academy

Get the full course at: http://www.MathTutorDVD.com
In this lesson, we'll discuss the concept of the confidence interval in statistics. We'll solve a few problems where we must calculate the confidence interval of a population mean when given information such as the sample size, margin of error, and the sample mean.

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mathtutordvd

Confidence Interval Example
Watch the next lesson: https://www.khanacademy.org/math/probability/statistics-inferential/confidence-intervals/v/small-sample-size-confidence-intervals?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics
Missed the previous lesson?
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Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it!
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Khan Academy

Two important measures of statistical significance. P value is the probability of false positive, i.e. the result not being due to chance. According to the recent ASA statement - p value is the probability of getting a result at least as extreme as the one you got or more extreme. CI is the range of values between which the true population measure lies for a given confidence level.

Views: 36795
PsychScene Hub

What is CONFIDENCE INTERVAL? What does CONFIDENCE INTERVAL mean? CONFIDENCE INTERVAL meaning - CONFIDENCE INTERVAL definition - CONFIDENCE INTERVAL explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
In statistics, a confidence interval (CI) is a type of interval estimate of a population parameter. It is an observed interval (i.e., it is calculated from the observations), in principle different from sample to sample, that frequently includes the value of an unobservable parameter of interest if the experiment is repeated. How frequently the observed interval contains the parameter is determined by the confidence level or confidence coefficient. More specifically, the meaning of the term "confidence level" is that, if CI are constructed across many separate data analyses of replicated (and possibly different) experiments, the proportion of such intervals that contain the true value of the parameter will match the given confidence level. Whereas two-sided confidence limits form a confidence interval, their one-sided counterparts are referred to as lower/upper confidence bounds (or limits).
Confidence intervals consist of a range of values (interval) that act as good estimates of the unknown population parameter; however, the interval computed from a particular sample does not necessarily include the true value of the parameter. When we say, "we are 99% confident that the true value of the parameter is in our confidence interval", we express that 99% of the hypothetically observed confidence intervals will hold the true value of the parameter. After any particular sample is taken, the population parameter is either in the interval, realized or not; it is not a matter of chance. The desired level of confidence is set by the researcher (not determined by data). If a corresponding hypothesis test is performed, the confidence level is the complement of respective level of significance, i.e. a 95% confidence interval reflects a significance level of 0.05. The confidence interval contains the parameter values that, when tested, should not be rejected with the same sample. Greater levels of variance yield larger confidence intervals, and hence less precise estimates of the parameter. Confidence intervals of difference parameters not containing 0 imply that there is a statistically significant difference between the populations.
In applied practice, confidence intervals are typically stated at the 95% confidence level. However, when presented graphically, confidence intervals can be shown at several confidence levels, for example 90%, 95% and 99%.
Certain factors may affect the confidence interval size including size of sample, level of confidence, and population variability. A larger sample size normally will lead to a better estimate of the population parameter.
Confidence intervals were introduced to statistics by Jerzy Neyman in a paper published in 1937.

Views: 5682
The Audiopedia

Watch my newer Video (2014) on the same topic:
https://www.youtube.com/watch?v=ss6erwmg7ac
Amir H. Ghaseminejad shows the meaning of Confidence Interval with a simple example.
There are two schools in statistics.
In the frequentist school, The parameters of population are unknown constants, 90% confidence interval means that with a large number of repeated samples, 90% of the calculated confidence intervals would include the true value of the mean.
In the Bayesian school, a 90% credible interval for the parameter means that the posterior probability that the parameter lies in the interval is 0.9.
An alternative terminology is to use "Bayesian confidence interval" instead of "credible interval".
Many professional statisticians and decisions scientists as well as non-statisticians intuitively interpret confidence intervals in the Bayesian credible interval sense and hence "credible intervals" are sometimes called "confidence intervals".
It is widely accepted, especially in the decision sciences, that "credible interval" is merely the subjective subset of "confidence intervals".
In fact, much research in calibrated probability assessments never uses the term "credible interval" and it is common to simply use "confidence interval".
Credible interval. (2009, June 1). In Wikipedia, The Free Encyclopedia. Retrieved 18:28, May 16, 2010, from http://en.wikipedia.org/w/index.php?title=Credible_interval&oldid=293787574

Views: 477151
Amir H. Ghaseminejad

An introduction to confidence intervals.

Views: 208675
jbstatistics

This video carries on from "Understanding Confidence Intervals" and introduces a formula for calculating a confidence interval for a mean. It uses graphics and animation to help understanding.

Views: 257617
Dr Nic's Maths and Stats

They include much more information, including an estimate on precision and information on clinical vs statistical significance. The sound here is very quiet. So here's a version that is exactly the same but louder. https://www.youtube.com/watch?v=1tWhe4fWp-o
https://www.youtube.com/watch?v=1tWhe4fWp-o

Views: 21155
Rahul Patwari

Video describing the role and interpretation of confidence intervals

Views: 37092
Terry Shaneyfelt

Calculating a 95% confidence interval for one proportion - worked example

Views: 45017
Keith Bower

This video examines how to interpret the confidence interval for the one sample t test in SPSS. Confidence intervals can be used instead of the p-value to assess whether or not the test is significant.
Video Transcript: What I'd like to do in this video is talk a little bit about this 95% confidence interval of the difference, which can be another way to assess the significance of the (t) test. First of all, notice that there was a six point three three-point mean difference between the students who took the program and the untreated population. How is this obtained? Well notice the mean is 86.33 for our sample. The untreated population mean is 80. So if I take 86.33 and subtract 80 from that, I will get, in fact, 6.33. So that's where this value comes from. And what we can do is we can build a confidence interval which is done for us automatically in SPSS around this mean difference of 6.33. And this confidence interval ranges from 1.84 all the way up to 10.82. OK this is our 95% confidence interval of the difference. And the way you interpret this is, from a hypothesis testing perspective, or through significance testing, is that if this range includes the value of zero anywhere in it, then the test is not significant. If 0 is in this range, then the p value will be greater than .05, the test will not be significant. Notice here 0 is not in this range. The bottom of the interval is 1.84, so this does not include 0. If this was, say, -1.84, then zero would be included in this range. And if this was -1.84 then this would be greater than .05, the p value, by definition. So these will always agree, in the sense that, if this test is significant, then this will not include 0. If it's not significant, then zero will be in this range. What I would like to do is to play with the data just for a minute to try and show you how this is the case. So let's go back to our Data Editor window here, and recall that the untreated population mean is 80, so I'm going to make some of these values much closer to 80. And of course I'm doing this just for instructive purposes. I wouldn't normally do this with real data. We'd never change data, of course. But to make a point here, I want to show you what would happen if we did have a nonsignificant result. So let's do one more just to be safe here. So let's see how this turns out, I'm going to rerun the test so Analyze, Compare Means, One Sample t Test. And everything looks good here, so let's click OK. And here's my new result. Now notice here that the mean was a 80.13, with these fictitious values here. And my p value was .929. So to review, let's assess that. Is the test significant? Well recall my decision rule, if p is less than or equal to .05, the test is significant. And if p is greater than .05, the test is not. So here we have a p value of .929, definitely greater than .05, so the test is not significant. And look at our confidence interval. The confidence interval, does it include 0? It does, right, because its range is basically from -3, with rounding, all the way to 3.26, 3.27 rounding to two decimal places. So notice here how this interval includes 0, and the test is not significant, whereas this interval did not include zero and the test was significant. So these two things will always agree, the 95% confidence interval and the outcome of the tests.
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Channel Description: For step by step help with statistics, with a focus on SPSS (with Excel videos now too). Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Videos series coming soon include: multiple regression in spss, factor analysis in spss, nonparametric tests in spss, multiple comparisons in spss, linear contrasts in spss, and many more. Subscribe today!
YouTube Channel: https://www.youtube.com/user/statisticsinstructor

Views: 6161
Quantitative Specialists

This problem is from the following book: http://goo.gl/t9pfIj
From a confidence interval we calculate the point estimate and margin of error. We also interpret confidence level and determine how it affects the width of the interval.

Views: 5687
MATHRoberg

I take made-up ice cream sales vs. temperature data to demonstrate how to get and interpret a 90% confidence interval for the slope coefficient of a simple regression.

Views: 32849
ProfTDub

Confidence Interval of Difference of Means
Watch the next lesson: https://www.khanacademy.org/math/probability/statistics-inferential/hypothesis-testing-two-samples/v/clarification-of-confidence-interval-of-difference-of-means?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics
Missed the previous lesson?
https://www.khanacademy.org/math/probability/statistics-inferential/hypothesis-testing-two-samples/v/difference-of-sample-means-distribution?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics
Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it!
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to KhanAcademy’s Probability and Statistics channel:
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Views: 218580
Khan Academy

Check conditions, calculate, and interpret a confidence interval to estimate a population proportion.
View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-z-interval-proportion/v/example-calculating-confidence-interval?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics
AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics.
Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today!
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Views: 14813
Khan Academy

People will often compare two confidence intervals and if they do not overlap, take that as evidence of a 'significant' difference. However, in doing so people are performing a 'test' with a much smaller significance level than they think. You can have a 'significant' difference even when the confidence intervals overlap. Darryl explains.
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Proteus is a statistical consulting company that specialises in ecological and wildlife applications. We can help you design your study and analyse the data. Proteus also provides statistical training courses and workshops, both open and private courses are available on request.
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#darrylmackenzie, #proteus, #ecologicalstatistician, #statisticalconsultant, #capturerecapture, #markrecapture, #occupancymodelling, #distancesampling, #wildlifestatistics, #statistics

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Proteus

Learn the concept of a confidence interval, as it applies to a population mean. A Confidence Interval provides a range of possible values for the population mean. This video provides a fun, and conceptual introduction to confidence intervals, and their use in statistical inference.
Check out the web visualizations here: http://www.zoology.ubc.ca/~whitlock/kingfisher/CIMean.htm

Views: 18370
MarinStatsLectures-R Programming & Statistics

How to calculate the 95% confidence interval and what it means.
Watch my new 95% Confidence Interval video:
https://www.youtube.com/watch?v=que_YzwzqGo

Views: 549650
mathwithmrbarnes

statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!

Views: 174188
statslectures

This is the difference between confidence intervals and confidence levels. These are often confused on the AP exam.

Views: 4018
David

Definition and estimation of the standard error of the mean. Calculation and interpretation of confidence intervals.

Views: 12088
Matthew E. Clapham

An introduction to confidence intervals for the population mean mu. These methods are appropriate when we are sampling from a normally distributed population, where the population standard deviation sigma is known. When the population standard deviation is not known, as is usually the case, we need to use a slightly different method (a method based on the t distribution).
The 2D:4D ratio data (from the right hand) is simulated data with the same summary statistics as found in:
Stevenson et al. (2007). Attention Deficit/Hyperactivity Disorder (ADHD) Symptoms and Digit Ratios in a College Sample. American Journal of Human Biology. 19:41-50.

Views: 148590
jbstatistics

Calculating a 95% confidence interval for one population mean - worked example

Views: 214151
Keith Bower

Views: 63798
Aliosha Alexandrov

Mr. Snoothouse explains the proper interpretation of a confidence interval for the population mean to Jimmy.

Views: 7891
jbstatistics

This video examines how to interpret the confidence interval for the independent samples t test in SPSS. Confidence intervals can be used instead of the p-value to assess whether or not the test is significant.
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Channel Description: For step by step help with statistics, with a focus on SPSS (with Excel videos now too). Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Videos series coming soon include: multiple regression in spss, factor analysis in spss, nonparametric tests in spss, multiple comparisons in spss, linear contrasts in spss, and many more. Subscribe today!
YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Video Transcript:
In the previous video we ran the independent samples t-test for a problem where we were comparing the no music group versus the high volume group and examining whether there was a significant difference between these two groups in terms of their test scores. When we ran that we had the output that showed a significant difference with the p of .014 between our two groups. Now, alternatively, instead of looking at the p-value we could interpret the ninety-five percent confidence interval and that's what I want to do here. Notice this range does not include zero and you may recall from a previous presentation on the one-sample t that we had said that if zero was not in this range, that indicates that the test is statistically significant; that is, there's a significant difference between our two groups and since this range does not
include zero, the test is significant and we can see that confirmed by a p-value of less than or equal to .05. Another way to think about it is if zero was in this range, say this was negative 1.69
and this was 13.11, zero would be in this range if this was negative
if you saw that then the p-value here would also be greater than .05. So this is another way to interpret the results of the independent samples t-test - we can look at the ninety-five percent confidence interval and once again if zero is not in the range that means the test is statistically significant whereas if zero is included in this range then the test is not statistically significant.
This concludes the presentation on the ninety-five percent confidence interval for the independent samples t-test. Thanks for watching.

Views: 4786
Quantitative Specialists

How to find the sample proportion confidence interval

Views: 97058
searching4math

This video demonstrates a common misinterpretation of confidence intervals and a game to help users improve their accuracy in interpreting confidence intervals.

Views: 1101
db91711

Learn how to calculate the 95% confidence interval of proportions in Stata.

Views: 2501
272analytics Videos

When you perform a linear regression, what you're implicitly assuming is that there is some reason that the data are linearly related. The goal of a regression analysis is to identify the true slope and the true intercept (which you never get to know in real life). If you performed an experiment 100 times and collected 100 different data sets, and then calculated the 95% confidence intervals for the slope and the intercept, on average 95 of your confidence intervals would have contained the true values of the slope and the intercept. However, you never get to know which of your 5 confidence intervals did not contain the true values. This screencast presents some simulations to show how that might play out in real life.
Made by faculty at the University of Colorado Boulder, Department of Mechanical Engineering and produced by the Department of Chemical & Biological Engineering.
Check out our Engineering Computing playlists: https://www.youtube.com/user/LearnChemE/playlists?sort=dd&view=50&shelf_id=4
Are you using a textbook? Check out our website for videos organized by textbook chapters: http://www.learncheme.com/screencasts

Views: 7173
LearnChemE

Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys
Construct and Interpret a Confidence Interval for the Population Mean

Views: 714
The Math Sorcerer

Today we’re going to talk about confidence intervals. Confidence intervals allow us to quantify our uncertainty, by allowing us to define a range of values for our predictions and assigning a likelihood that something falls within that range. And confidence intervals come up a lot like when you get delivery windows for packages, during elections when pollsters cite margin of errors, and we use them instinctively in everyday decisions. But confidence intervals also demonstrate the tradeoff of accuracy for precision - the greater our confidence, usually the less useful our range.
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CrashCourse

Calculating a 95% confidence interval for 2 means - worked example

Views: 55484
Keith Bower

Tutorial on using Microsoft Excel to determine confidence internals, margin of error, range, max, min and margin of error
Playlist on Confidence Intervals
http://www.youtube.com/course?list=EC36B51DB57E3A3E8E
Related Videos:
How to Read A Normalized Table (for z scores).
http://www.youtube.com/watch?v=dWu0KLXuEpA
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David Longstreet Professor of the Universe
Professor of the Universe: David Longstreet http://www.linkedin.com/in/davidlongstreet/
MyBookSucks.Com

Views: 548025
statisticsfun

What is the difference between Confidence Intervals and Prediction Intervals? And how do you calculate and plot them in your graphs?

Views: 69326
Dr. Gerard Verschuuren

Lecture with Peder Bacher. Kapitler:

Views: 2250
DTUdk

While the overall result of an intervention is important, the range of effect is just as critical. That’s where confidence intervals come in. They describe the range of results found in a research study. Understanding a Confidence Interval describes the 95% confidence interval, which tells us that 95 times out of 100, the effect of an intervention will be within the range specified.
Knowing the confidence interval provides a measure of certainty of the effectiveness of an intervention in the real world. To explain, the video describes the effect of a hypothetical social media campaign to prevent cyber-bullying in schools. While the research shows that the campaign did indeed reduce cyber-bullying, the range of results, as determined by the 95% confidence interval, may not be so clear-cut.
The video also explores what it means if the range crosses the ‘line of no difference’. In that case, we should expect that the cyber-bullying could actually increase. Whenever making a decision on whether the results of an intervention warrant the cost and effort of implementing it, it’s important to take a close look at the confidence interval.
The National Collaborating Centre for Methods and Tools is funded by the Public Health Agency of Canada and affiliated with McMaster University. The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada.
NCCMT is one of six National Collaborating Centres (NCCs) for Public Health. The Centres promote and improve the use of scientific research and other knowledge to strengthen public health practices and policies in Canada.

Views: 11896
The NCCMT

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