Professor,
Statisticians use a confidence interval to depict the measure of vulnerability connected with a sample
estimate of a population parameter. Confidence intervals are constructed at a confidence level, for
example, ninety percent, selected by the user. Meaning, that if the same population is examined on
numerous occasions and interval estimates are made on each special event, the subsequent intervals
would section the true population parameter in approximately ninety percent of the cases. A
confidence expressed at a 1−α level can be considered of as the inverse of a significance level, α
('Interpreting', 1995).
Trisha
Reference
Interpreting a confidence interval of a mean (1995).Retrieved from
http://www.graphpad.com/guides/prism/6/statistics/index.htm?
stat_more_about_confidence_interval.htm
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Thread:Confidence IntervalPost:RE: Confidence IntervalAuthor: Sonya Jones Posted Date: February
21, 2016 11:48 PMStatus:Published
Professor and Class,
Confidence level describes the percentage of uncertainty associated with the sampling method. It
also shows how much can be expected to include the true population parameter (Stattrek, 2016). To
show the confidence level, it needs the margin of error. The margin of error expresses the maximum
expected difference between the true population and sample population.
Stattrek (2016). What is a confidence interval? Reviewed at:
http://stattrek.com/estimation/confidence-interval.aspx
,Sonya
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Thread:Unit 6.1 DiscussionPost:RE: Unit 6.1 DiscussionAuthor: Elizabeth Messenger Posted Date:
February 21, 2016 11:32 PMStatus:Published
Erin,
I have dealt with the measures of central tendency in my statistics class as well, so I am very familiar
with mean median and mode. I believe that they are very important to understand when looking at
any set of numbers so that we can get a clear understanding of a single number. I use central
tendency while I am at work actually. I am a server and I have to determine how much food I should
have backed up in order to be able to feed everyone smoothly. For instance on a sunday we are very
busy. By looking at the results in business from last sunday I know on average how many people will
want salads. While it is not 100% accurate, it still gives me a general idea of what I need to look
forward to.
-Elizabeth
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Thread:ScatterplotPost:RE: ScatterplotAuthor: Sonya Jones Posted Date: February 21, 2016 9:43
PMStatus:Published
A scatterplot is a graph that is designed to assist in plotting points for two variables. It assists in
showing the comparison of the two variables and how they relate to each other. The correlation in a
scatterplot is comprised of strength and direction. The strength is represented by the numerical
value, while the direction is whether the correlation is positive or negative. With the positive
correlation the two variables move in the same direction. That is as one increase, so does the other
one as well as when they decrease. With negative correlation, as one variable increases, the other
variable with decrease. They move in the opposite direction of each other.
http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html
,Sonya
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Thread:Standard DeviationPost:RE: Standard DeviationAuthor: Erin Galloway Posted Date: February
21, 2016 8:24 PMStatus:Published
Professor,
I agree that the standard deviation can often be difficult to understand. I would say the easiest way
for me to understand the standard deviation is that it shows us where the score is compared to the
mean. There are two ways to calculate the standard deviation. One way is the sample standard
deviation and the other was is the population standard deviation. To find the standard deviation you
first have to find the mean. After you find the mean you take each value in the data set and subtract
the mean from it. After this step you square each of the differences that you found in the previous
step and add them up. This gives you the sum of the squares. After that you will divide the the total
number of values in the data set and then subtract that by one. The final step is taking the square
root of the number found in the previous step and then you find the standard deviation.
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Thread:Unit 6.1 DiscussionPost:RE: Unit 6.1 DiscussionAuthor: Erin Galloway Posted Date: February
21, 2016 7:59 PMStatus:Published
Casey,
Thank you for your response. The measures of central tendencies and variability would be very
useful in creating behavioral plans. In my current position, I used the measures of central tendencies
to determine and observe the rates for our storage units. In my future career it is likely that I will use
these measures to determine if the different programs that are used are effective or not and what is
working. To answer your question, I think it is really important to take time to see why the data has a
sudden change. This could show you the reason behind some problems in a program so that you can
fix this.
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Thread:6.1Post:RE: 6.1Author: Casey Stlouis Posted Date: February 21, 2016 6:39
PMStatus:Published
Elizabeth,
This was a really good link I used to dig more into variablilty. This was the hardest part of this unit for
me. Standard diviation is not something I was familiar with and I do understand it better now and
can see how things can be figured out with standard diviation. I think in most research projects that
it is actually really imporntat to understand how the different sets of data can vary based on
circumtance as well as the way the experiment can change based on variables.
http://onlinestatbook.com/2/summarizing_distributions/variability.html
When I was looking at how different the 2 were I fond that variablilty really is more important to an
experiment than central tendency becuase seeing where the experiment can go wrong and then
explaining and fixign makes a person a good scientist.
Casey
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Thread:Confidence IntervalPost:RE: Confidence IntervalAuthor: Patricia Akinwale Posted Date:
February 21, 2016 6:12 PMStatus:Published
Professor,
According to our text, "Confidence interval indicates the range of values which we can expect to
contain a population value with a specified degree of confidence (e.g., 95%)" (Shaughnessy,
Zechmeister, and Zechmeister, 2015, pg. 443.). If a corresponding hypothesis test is performed, the
confidence level is the complement of respective level of significance. However, when presented
graphically, confidence intervals can be shown at several confidence levels, for example90%, 95% and
99%. "Definite elements may affect the confidence interval is including size of sample, level of