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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.

Questions & Answers

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Solve the mean of variance
Veronica Reply
Step 1: Find the mean. To find the mean, add up all the scores, then divide them by the number of scores. ... Step 2: Find each score's deviation from the mean. ... Step 3: Square each deviation from the mean. ... Step 4: Find the sum of squares. ... Step 5: Divide the sum of squares by n – 1 or N.
kenneth
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Jibrin
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diveving the sum if all values
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let A1,A2 and A3 events be independent,show that (A1)^c, (A2)^c and (A3)^c are independent?
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data collected all over the world
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construct a less than and more than table
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The sample of 16 students is taken. The average age in the sample was 22 years with astandard deviation of 6 years. Construct a 95% confidence interval for the age of the population.
Aschalew Reply
Bhartdarshan' is an internet-based travel agency wherein customer can see videos of the cities they plant to visit. The number of hits daily is a normally distributed random variable with a mean of 10,000 and a standard deviation of 2,400 a. what is the probability of getting more than 12,000 hits? b. what is the probability of getting fewer than 9,000 hits?
Akshay Reply
Bhartdarshan'is an internet-based travel agency wherein customer can see videos of the cities they plan to visit. The number of hits daily is a normally distributed random variable with a mean of 10,000 and a standard deviation of 2,400. a. What is the probability of getting more than 12,000 hits
Akshay
1
Bright
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Bright
a= 0.20233 b=0.3384
Sufiyan
a
Shaynaynay
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Mohd Reply
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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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