When is the sample median preferred to the sample mean?

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SUMMARY

The discussion focuses on the preference of the sample median over the sample mean in statistical analysis, particularly in the presence of outliers and skewed distributions. Participants emphasize that the sample median is preferred when data is not symmetrically distributed, as it provides a better central tendency measure in such cases. The conversation also touches on the importance of measures of variation, highlighting that the mean and median are not measures of variation but rather measures of location. Understanding these concepts is crucial for accurate data analysis.

PREREQUISITES
  • Understanding of basic statistical concepts such as mean, median, and mode.
  • Familiarity with measures of variation, including standard deviation and interquartile range.
  • Knowledge of data distribution types, specifically symmetrical and skewed distributions.
  • Ability to identify outliers and their impact on statistical measures.
NEXT STEPS
  • Study the differences between measures of central tendency: mean, median, and mode.
  • Learn about the impact of outliers on statistical analysis and how to handle them.
  • Explore the concept of data distribution and its implications for choosing the appropriate average.
  • Investigate various measures of variation and their applications in different data contexts.
USEFUL FOR

Students, data analysts, and statisticians seeking to deepen their understanding of statistical measures and improve their data analysis skills, particularly in handling skewed data and outliers.

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Homework Statement



i have a few easy questions but i need some help with them:
1)
a) Why do we need averages?
b) Which average can have more than one value?
c) Which average represents the value when the total of all the sample values is shared out equally?
d) Which average has the same number of values above it below it?
e) When is the sample median preferred to the sample mean?
f) When is the sample mode preferred to the sample mean?
g) When is the sample mean preferred to both the sample median and the sample mode?

2)
a) Why do we need measures of variation ?
b) What measure of variation is most useful in the case of: (i) a symmetrical distribution, (ii) a skew distribution'?
c) Think of an example of sample data where the range would be a misleading measure of variation.
d) Name the measure of variation associated with the: (i) sample mean, (ii) sample median, (iii) sample mode.
e) Name the average associated with the: (i) sample standard deviation, (ii) sample inter-quartile range, (iii) range.


Homework Equations





The Attempt at a Solution



1)
a) to analyse the data
b) when there's more than one dependent variable
c) i don't know
d)i don't know
e)when there's numerical data
f) when there's discrete data
g) when the histogram is symmetrical

2)
a) i don't know
b) i) mean/standard deviation ii) median/interquartile range
c) i don't know
d) i don't know
e) i don't know

any help would be very appreciated.
thank you.
 
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1)
a) to analyse the data: WOULD "SUMMARIZE" BE A BETTER WORD THAN "ANALYZE"?
b) when there's more than one dependent variable: NO. I AM INCLINED TO SAY "MOVING AVERAGE" BUT THAT'LL DEPEND ON THE CONTEXT.
c) i don't know: CAN YOU THINK OF AN EXAMPLE?
d)i don't know: DITTO
e)when there's numerical data: NO -- IT HAS TO DO WITH SYMMETRY AND OUTLIERS
f) when there's discrete data: NO -- IT HAS TO DO WITH "NUMERICAL DATA" VS. _________ ("DISCRETE" CAN ALSO BE NUMERICAL; E.G., INTEGER NUMBERS ARE DISCRETE)
g) when the histogram is symmetrical: THIS WILL FOLLOW FROM E AND F ABOVE

2)
a) i don't know: TO SUMMARIZE EXPANSIVENESS OF DATA?
b) i) mean/standard deviation ii) median/interquartile range: MEAN AND MEDIAN AREN'T MEASURES OF VARIATION. (THEY ARE MEASURES OF LOCATION.)
c) i don't know: THINK "OUTLIER(S)"
d & e) i don't know: D & E ARE "MATCHING PAIRS," YOU NEED TO MAKE THE RIGHT MATCHES.
 
Last edited:
i don't undrerstand what they mean by measures of vairation ??
 
sara_87 said:
i don't undrerstand what they mean by measures of vairation ??
Consider these two sets of numbers:
Set #1 : {2,1,2,2,2,3,2,2}
Set #2 : {3,1,2,2,0,2,4,2}
Both sets have the same mean, median, and mode. The second set exhibits a lot more deviations from the mean than does the first set.
 
so why do we need measures of variation, I'm sorry i just don't understand.

and i still don't know how to do question 2

:(
 
For a), D H practically gave you the answer: because they give us some information we would otherwise miss.
For c): How is the range determined? Can you think, for example, of a set with a very wide range but very small variations?
 

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