Student's t- distribution to construct a confidence interval question

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Using the Student's t-distribution to construct a confidence interval is appropriate for small sample sizes, such as the given sample size of 10. However, the suitability also depends on whether the data is drawn from a normally distributed population. Concerns were raised about the normality of the data, as the sample's mean and standard deviation suggest potential skewness. The discussion emphasizes the importance of assessing the distribution characteristics of the data before applying the t-distribution. Ultimately, the decision hinges on both sample size and the underlying population distribution.
joe98
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The following are summary statistics for a data set. Would it be appropriate to use the
Student's t- distribution to construct a confidence interval for these data?
Explain clearly!

Sample size = 10
Mean = 8.905
Median = 6.105
Standard deviation = 9.690
Minimum = 0.512
Maximum = 39.920
Q1 = 1.967
Q3 = 8.103

My answer would be it would be appropriate since n is less than 40(small sample size), we can use t distribution.

Any other explanations guys
 
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joe98 said:
Would it be appropriate to use the
Student's t- distribution to construct a confidence interval for these data?

A confidence interval for what? The mean of the population they were sampled from?

This is a homework type problem, right? We begin to see why homework section wants such problems posed in a orderly format that includes a complete statement of the problem.

I suppose the issue here might be how much your numerical tables for the t-statistic depend on the population being normally distributed and whether you think your sample is.from a normally distributed population.
 
Stephen Tashi said:
A confidence interval for what? The mean of the population they were sampled from?

thats right, and that's the data given in the question,

the question says if it is suitable to use t distribution to construct a confidence interval using the given data.

Somehow i have to explain how its possible?

Any ideas?
 
so Stephen, your suggesting its not suitable to use tdistribution because its not normally disstributed but could there be any other reasons?
 
joe98 said:
so Stephen, your suggesting its not suitable to use tdistribution because its not normally disstributed but could there be any other reasons?

Joe, just simply look how t distribution looks. Is it symmetric? What about other properties? Do your data look like samples from this distribution? Etc.
 
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