Download Response The values in the bin because the higher or lower the

Response
The values in the bin because the higher or lower the values the center and spread are subjective
to change
This doesn’t answer the question.
Measures of center are represented by median or mean. the median is the middle value of all the
data and the mean is all the data added up together divided by the number of variables in the
data. Spread is measured either by the mean and standard deviation (the spread of the data from
the mean) or by the five number summary (minimum, quartile 1, median, quartile 3, max) and
the Inter Quartile Range.
This is true, but does not answer the question.
The shape of the distribution determines which numerical measures of center and spread are
appropriate for describing a given distribution of a quantitative variable. Mean and standard
deviation are used for a normal shaped/symmetrical distribution and median and IQR are used
for unsymmetrical distributions. Also taken into account are extreme values which influence the
mean but not the median.
PERFECT! Good job!
the shape od the distribution determines wich measure of center and spread are appropriate for
describing a given distribution of a quantitative variable. If the varibles is are quatitative a
histogrom or stemplot would be good and if it is catagorical then a pie or bar graph would be
good for that use.
Yes, it’s all true; however, the second sentence has nothing to do with the question.
The mean and standard deviation are the most appropriate for describing a given distribution of a
quantative variable. The mean would be used to find the center and the standard deviation would
be used to find the spread of the sum.
Yes, but only for fairly symmetric distributions.
To describe a given distribution of a quantitative variable it would be best to use the five-number
summary to find all the information such as the Median, Q1 and Q3 and also the Min and Max.
From there, if you wanted to show the information it would be best to make a Boxplot because it
is visually better.
So you would never ever use the mean and the standard deviation?
The two main numerical measures for the center of a distribution are the mean and the median. I
will use the mean in most cases.
Why? How about the measures of spread?
The presence of outliers and the shape of the distribution determine which numerical measure we
will use. There are 2 main numerical measures of the center and they are the mean and median.
When a distribution is symmetrical the mean and median would be about the same so you can
use either or if there isn't any outliers. When the distribution is skewed then we will use the
median as the measure of center because it is not affected by outliers. The spread is determined
by the IQR.
Very good. You just didn’t mention standard deviation. Otherwise, it’s perfect. Good job.
it all depends on the different types of graphs that you use
How?
Once the distribution has been displayed graphically we decided the overall pattern. You decided
the shape of the distribution.
So what’s the answer to the questions?
Use mean and the standard deviation as measures of center and spread only for symmetric
distributions with no outliers. Use the five-number summary (which gives the median, IQR and
range) for all other cases.
PERFECT. Good job!
If there was a histogram and the question was to determine the measures of center and spread,
then I would find out the MEDIAN and the IQR. The median is obviously getting the middle
number of the group of numbers. As to detemining the spread, I would use the IQR (finding the
median of the min group and max group) because then I can approximate the range of the spread.
So you would never ever use the mean and the standard deviation?
Describing numerically the measures of spread and center cannot be done through visualizing the
center. For instance, outliers can alter the mean, and not the median.
This is true, and that’s exactly the reason why we don’t want to use the mean as a measure of
center for distributions with outliers.
Therefore, one has to use the mathematical formulas in order to understand the data, with regards
to center and spread.
Yes, you need formulas to calculate them, but the question was which one of them would be
appropriate to use in what cases.
The IQR is the median for the lower and upper half of the data excluding the median.
No, the IQR is the difference between the quartiles.
It is utilized in understanding outliers and the over all distribution of the data.
the mean and the median determine the center. the mean works better withe the standard
deviation withe the graph is symmetric, and median works better with the IQR no matter what
kind of graph.
Yes.
What determines which measures of spread and center are appropriate for describing a given
distributon of a quatitative variable is what type of graph one is using (histogram,or stemplot) &
whether one is using mean (appropriate for symmetrical distributions) or meadian as center. For
spread (variability) Range is used to find the distance between the smallest point and the largerst
point, IQR is used to determine outliers.
These are all true, but didn’t really answer the question. You only touched on the answer when
you said “…whether one is using mean (appropriate for symmetrical distributions) …”
I would use mean and median because I would be given the average and center of the data. Mean
gives the numeric average while median shows me the center on the graph.
You would use both of them all the time? How about the spread?
It depends on the type of information you are looking for. For instance, Standard deviation is
used to look for distance between the mean and the furthest point of data and the five-point
summary is used to analyze the different averages between the data.
No, this is not correct, and doesn’t answer the question.
The five number summary will give you the measures of center and spread for describing a given
distribution. The measures I would give are the maximum/minimum non-outliers, the mean, the
median, the inter quartile range, and the quartiles.
For EVERY distributions?
I am having trouble understanding the question.
Read the responses of the others. Especially those with the correct answer.
The center can be determined by the median. The spread can be determined by the five number
summary, mainly the IQR. For a distribution, the five number summary should be used to
describe the extremes, center, and the quartiles. For a quantitative variable, you should use the
boxplot to visually depict the five number summary and help location possible outliers.
Yes, it’s true, but doesn’t answer the question at all.
The numerical measures of center and spread that are appropriate for describing a given
distrubition of quantitive variable are a bar graph and a histogram. The measures I would use are
the stem plot and the dot plot.
Plots are NOT numerical measures of center and spread.
The 5 number summary. A 2 way table or 5 number summary.
No, this is not correct at all.
Mean median range inter-quartile and standard deviation
This doesn’t make sense, and doesn’t answer the question.
range- will give me the distance from the min to the max median- will give me the number that is
in the center Q1,Q2, and IQR- will help me determine if I have any outliers Standard Diviation-
will help me determine the distance from the mean
Well, OK, but this doesn’t answer the question at all.
The shape of the data and any outliers determine how to measure center and spread. Extreme
outliers will affect the mean, so the median would be an appropriate measure in that case.
True.
A skewed distribution would push the median out to the right or left, so the mean would be more
appropriate.
No. This is not true.
And how about the measures of spread?
If I were given a graph that was symmetrical and unimodal in shape than I would use the Mean
and Standard deviation to determine the center and spread of the distribution. If I were given a
graph that was skewed left or right with or without possible outliers than I would use the Median
and Inter-quartile Range to determine the center and spread of the distribution because the
Median is not sensitive to outliers or skewed graphs.
PERFECT!
Each numerical measure of center and spread are all the same but each has a specific goal. Either
one can be used to describe a given distribution of quantitative variable. I usually go for the five
number summary since it finds the min, Q1, M, Q3, and max.
How about the mean and the standard deviation?
For center, there are two ways of measures of center and they are mean and median. Mean is
appropriate measure of center only for symmetric distributions with no outliers. In all other
cases, median should be used as a measure of center. For the spread, there are three ways of
measures of spread, and they are range, IQR (inter-quartile range), and standard deviation. Since
range and IQR are determined by the median, they should be used when median was the
appropriate way of measure. Same as the standard deviation, it should only be used when mean
was the appropriate way of measure.
PERFECT! (except that the range is determined by the median—that’s not true.)