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Part ii: possible distributions

____ Suppose that X followed the following theoretical distributions. Set up each distribution using the appropriate information from your data.
____ Uniform: X ~ U ____________ Use the lowest and highest values as a and b .
____ Normal: X ~ N ____________ Use x ¯ to estimate for μ and s to estimate for σ .
____ Must your data fit one of the above distributions? Explain why or why not.
____ Could the data fit two or three of the previous distributions (at the same time)? Explain.
____ Calculate the value k (an X value) that is 1.75 standard deviations above the sample mean. k = _________ (rounded to two decimal places) Note: k = x ¯ + (1.75) s
____ Determine the relative frequencies ( RF ) rounded to four decimal places.

Note

R F = frequency total number surveyed

  1. RF ( X < k ) = ______
  2. RF ( X > k ) = ______
  3. RF ( X = k ) = ______

Note

You should have one page for the uniform distribution, one page for the exponential distribution, and one page for the normal distribution.

____ State the distribution: X ~ _________
____ Draw a graph for each of the three theoretical distributions. Label the axes and mark them appropriately.
____ Find the following theoretical probabilities (rounded to four decimal places).

  1. P ( X < k ) = ______
  2. P ( X > k ) = ______
  3. P ( X = k ) = ______
____ Compare the relative frequencies to the corresponding probabilities. Are the values close?
____ Does it appear that the data fit the distribution well? Justify your answer by comparing the probabilities to the relative frequencies, and the histograms to the theoretical graphs.

Part iii: clt experiments

______ From your original data (before ordering), use a random number generator to pick 40 samples of size five. For each sample, calculate the average.
______ On a separate page, attached to the summary, include the 40 samples of size five, along with the 40 sample averages.
______ List the 40 averages in order from smallest to largest.
______ Define the random variable, X ¯ , in words. X ¯ = _______________
______ State the approximate theoretical distribution of X ¯ . X ¯ ~ ______________
______ Base this on the mean and standard deviation from your original data.
______ Construct a histogram displaying your data. Use five to six intervals of equal width. Label and scale it.
Calculate the value k ¯ (an X ¯ value) that is 1.75 standard deviations above the sample mean. k ¯ = _____ (rounded to two decimal places)
Determine the relative frequencies ( RF ) rounded to four decimal places.

  1. RF ( X ¯ < k ¯ ) = _______
  2. RF ( X ¯ > k ¯ ) = _______
  3. RF ( X ¯ = k ¯ ) = _______
Find the following theoretical probabilities (rounded to four decimal places).
  1. P ( X ¯ < k ¯ ) = _______
  2. P ( X ¯ > k ¯ ) = _______
  3. P ( X ¯ = k ¯ ) = _______
______ Draw the graph of the theoretical distribution of X .
______ Compare the relative frequencies to the probabilities. Are the values close?
______ Does it appear that the data of averages fit the distribution of X ¯ well? Justify your answer by comparing the probabilities to the relative frequencies, and the histogram to the theoretical graph.
In three to five complete sentences for each, answer the following questions. Give thoughtful explanations.
______ In summary, do your original data seem to fit the uniform, exponential, or normal distributions? Answer why or why not for each distribution. If the data do not fit any of those distributions, explain why.
______ What happened to the shape and distribution when you averaged your data? In theory, what should have happened? In theory, would “it” always happen? Why or why not?
______ Were the relative frequencies compared to the theoretical probabilities closer when comparing the X or X ¯ distributions? Explain your answer.

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Source:  OpenStax, Introductory statistics. OpenStax CNX. May 06, 2016 Download for free at http://legacy.cnx.org/content/col11562/1.18
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