The Normal Distribution: Worksheet | N 1, Exams of Health sciences

Material Type: Exam; Class: FIRST-YEAR INTEREST GROUP SMNR; Subject: Nursing; University: University of Texas - Austin; Term: Unknown 1989;

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Pre 2010

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The Normal Distribution: Worksheet
(Covered in class, but also read Williams, Chap. 5)
Relationships between the Sample, a Sampling Distribution and the Population
1. The normal distribution or normal curve is pictured in Williams'. Find the picture and
determine the proportions (percentages) under the curve which fall:
a. within 1 standard deviation from the mean ______________
b. within 2 standard deviations from the mean ______________
c. within 3 standard deviations from the mean ______________
Z-scores are used as an all-purpose calibration for the positions along the baseline of the
normal curve, because they can be used without any mention of the measurement being
taken for whatever variable is being described from the population. The z-score for 1
standard deviation is +1z and – 1z. Use the attached z-score table, locate the z-score for 1.0
and compare the area described in the table to your answer to 1.a. above.
What’s the difference?
Once you have mastered the z-score table, use it to find the proportion (percentage) under
the normal curve that would be determined by the center (the mean) and ±1.25 z.
_____________
How about the proportion above +2.05z? _________
How about below +2.05z? _____________
Here’s how the normal curve can be used to approximate proportions in a large population:
2. Assume the heights of women 18 to 24 are approximately normally distributed with μ=64
inches and σ=2.5 inches.
a. Draw a normal curve for this distribution, with the scale on the horizontal axes
indicating the heights at each of the major deviations.
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The Normal Distribution: Worksheet (Covered in class, but also read Williams, Chap. 5) Relationships between the Sample, a Sampling Distribution and the Population

  1. The normal distribution or normal curve is pictured in Williams'. Find the picture and determine the proportions (percentages) under the curve which fall: a. within 1 standard deviation from the mean ______________ b. within 2 standard deviations from the mean ______________ c. within 3 standard deviations from the mean ______________ Z-scores are used as an all-purpose calibration for the positions along the baseline of the normal curve, because they can be used without any mention of the measurement being taken for whatever variable is being described from the population. The z-score for 1 standard deviation is +1z and – 1z. Use the attached z-score table, locate the z-score for 1. and compare the area described in the table to your answer to 1.a. above. What’s the difference? Once you have mastered the z-score table, use it to find the proportion (percentage) under the normal curve that would be determined by the center (the mean) and ±1.25 z.

How about the proportion above +2.05z? _________ How about below +2.05z? _____________ Here’s how the normal curve can be used to approximate proportions in a large population:

  1. Assume the heights of women 18 to 24 are approximately normally distributed with μ= inches and σ=2.5 inches. a. Draw a normal curve for this distribution, with the scale on the horizontal axes indicating the heights at each of the major deviations.

b. What percent of women in this age group are taller than 64 inches? Taller than 66.5 inches? Shorter than 59 inches? c. If one were to take a random sample of 1000 women in this age group how many would we expect in our sample to be below -1.6 z-scores? When you move out + and - for the following z-scores on either side of the mean, what percentage of the normal distribution (or percentage of the sampling distribution) do you "capture" or account for? (You will need the TABLE of z-scores to do this.) z-score Percent of ND "captured"

  1. 1.0 ___________________
  2. 1.64 ___________________
  3. 2.58 ___________________
  4. 1.96 ___________________ One of the most common statistical problems is to generalize from a set of sample data statistics (to make an "educated guess") about the value of the population parameters. Most researchers want to know how accurately the value of the sample mean represents the value of the unknown population mean. In other words, we want to use the sample mean, x-bar ( X ), to make an inference about the value of the parameter, μ , for the population. To try to develop a sampling distribution from which such an approximation of μ for the population of all 7th grade boys' weights can be made. Use the following sheet. Assume the list of 7th graders' weights is the population and choose a sample of size 5 using the random number table you have already received. Find the mean of your sample of size 5. _________

standard error of the mean calculates how much variability there would be if we did take a true random sampling distribution from the population. Standard deviation of the sampling distribution of means is called the standard error of the mean. It's formula looks like This formula, again, calculates the standard error of a sampling distribution of the mean,

 M , and is used to create a confidence interval around the mean for the sample you took.

The formula must be calculated as shown above and then inserted into the following: CI 95 Xz 95 ( M )μXz 95 ( M ) Here are some practice problems:

  1. Given a sample of 50, you found a mean ( X ) of 7.38 and the CSS or the square of all the deviation scores ( (^) X  X) was 532. Calculate the standard error of the mean using the formula given above. Then create a 95% confidence interval around your sample mean. See Williams work this out on p. 62. WHEW! I know it is a lot to absorb! But these notions are central to the entire field of inferential statistics. Now try these last two questions to test your understanding.
  2. Sketch a picture of a sample (small) distribution and the distribution of a normally distributed population from which the sample was drawn. Write out the formula for finding the mean of the sample and the standard deviation for the population based on this smaller sample. Then sketch a picture of the sampling distribution of the mean and include the formulas for finding the standard error of the mean. Lastly sketch the distribution of a normally distributed population and include the formula for the standard deviation of the population (σ). Lastly include the formula for determining a confidence interval. This page will be handy for the final exam. M 2 = x n(n - 1)  
  1. A sample of 31 tires has been tested for mileage. The mean of the sample was found to be 38,000 miles meaning that this brand of tire, when sampled, lasted on average approximately 38,000 miles. The corrected sum of squares was found to be 37,200,000 miles. Find the standard error of the mean and construct a 95% confidence interval around the sample mean. Also construct a 90% confidence interval around your sample mean. Which of these looks more “confident?”
  2. Given that a sample (N=31) has a mean of 6.3 and a sample standard deviation (s) of 3. Find the standard error of the mean. Then construct an 80% confidence interval around the sample mean. Then take a break! Relax! This is almost (with a confidence interval of 95%) as bad as it gets! From now on, it's all down hill.... Here are some additional practice exercises for the strong of heart! Confidence Intervals and Hypothesis Testing (Not to be graded, answers given below)
  3. Bjorn Talooz, a Norwegian exchange student, would like to estimate the amount of money he spends daily in a typical school month, say October. A sample of 10 days shows the mean average expenditure to be $6.24 per day with a corrected sum of squares of $129.60. Please help Bjorn find a 95% confidence interval estimate of μ.
  4. The Howe, Doo, Yoo, Dew Answering Service wants to estimate the mean average number of calls handled per day. A sample of 50 days produced a mean of 326 calls with an s ˆ^ =48. Recall that s ˆ^ is the approximation of the population standard deviation and is calculated by taking the sq. root of (CSS/n-1). Compute the standard error of the mean and then produce a 90% confidence interval around μ.

Answers:

  1. standard error of mean = 1.2, $3.89 < μ < $8.
  2. standard error of mean = 6.79, 314 < μ < 337.
  3. standard error of mean = 19.8, 348.9 < μ < 451. 4. Reject the null, calculated t = 2. Sampling Frame of 7th Grade Boys Weights 1 96 2 116 3 64 4 102 5 135 6 162 7 83 8 87 9 104 10 113 11 144 12 76 13 82 14 97 15 68 16 114 17 132 18 94 19 105 20 86 21 98 22 107 23 124 24 101 25 94 26 79 27 116 28 78 29 110 30 88