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B. Heard
 (This material can not be copied or posted
without the author’s consent. Students may
      download one copy for personal use.)
 Standard    Normal Distribution
    The “standard” normal distribution is a normal
     distribution with mean zero and where the standard
     deviation (and variance) equals one.
    The Total Area under the curve is one (1) or 100%
     (This is true for all normal distributions regardless of
     the mean and standard deviation).
 Using Minitab for Normal Distribution
  calculations.
 Use Calc >> Probability Distributions >>
  Normal
 Examples Follow
 Example


 Theaverage fish in Happy Lake weighs 2
 pounds with a standard deviation of 0.5
 pounds. If Bob catches a fish that weighs 3.2
 pounds. What could you say about the
 catch?
Since this is the Cumulative
Distribution Function, it “fills”
from left to right.
Therefore, you could say his
catch was in the “Top 1 %”
 Example


 Theaverage fish in Happy Lake weighs 2
 pounds with a standard deviation of 0.5
 pounds. If Bob catches a fish that weighs
 1.35 pounds. What could you say about the
 catch?
Since this is the Cumulative
Distribution Function, it “fills”
from left to right.
Therefore, you could say his
catch was in the “Bottom 10 %”
 Other  types of questions
 If you have a normal distribution with a mu =
  100 and sigma = 15, what number corresponds
  to a z = -2

           -2 = (x – 100)/15
           Multiply both sides by 15 to get
           -30 = x – 100
           Add 100 to each side to get
           70 = x

           So “70” is my answer, I just did a little Algebra.
 Another  type of question
 Say we take 120 samples of size 81 each from a
  distribution we know is normal. Calculate the
  standard deviation of the sample means if we
  know the population variance is 25.
 (Answer next chart)
 Answer
 The Central Limit Theorem tells us the variance
 is the Population variance divided by the Sample
 Size. We can just take the square root to get
 the standard deviation.


        Variance = 25/81 or 0.309
        Standard Deviation = Square Root(25/81) = 5/9 = 0.556
 Findingz scores
 Example
    The area to the left of the “z” is 0.6262. What z
     score corresponds to this area.
    Use Calc >> Probability Distributions >> Normal
    (Set Mean = 0 and Standard Deviation to 1 and
     use “INVERSE Cumulative Probability”
Answer is 0.322
rounded to three
decimals. Remember
the distribution fills
from left to right.
 Another  type of question
 In a normal distribution with mu = 40 and
  sigma = 10 find P(32 < x < 44)
    Easy, but this takes a couple of steps.
    Using Calc >> Probability Distributions >> Normal
     find the probabililties that x < 32 and x < 44
     using the Cumulative Probability option.
 Continued




              Get results for
              Both 32 and
              then 44.
 Answer




                      Subtract
                      0.655422 –
                      0.211855
                      To get
                      0.443567
                      Or 0.444 rounded
                      to
                      three decimals
           P(32 < x < 44) = 0.444 based
           on
           the given mean and std
           deviation.
 Confidence    Intervals and Examples
    Charts follow
 Interpreting       Confidence Intervals
    If you have a 90% confidence interval of
     (15.5, 23.7) for a population mean, it simply
     means “There is a 90% chance that the
     population mean is contained in the interval
     (15.5, 23.7)
        It’s really that simple.
 Finding   Confidence Intervals
    A luxury car company wants to estimate the true
     mean cost of its competitor’s automobiles. It
     randomly samples 180 of its competitors sticker
     prices. The mean cost is $65,000 with a standard
     deviation of $3200. Find a 95% confidence
     interval for the true mean cost of the
     competitor’s automobiles. Write a statement
     about the interval.
 It randomly samples 180 of its competitors
  sticker prices. The mean cost is $65,000
  with a standard deviation of $3200. Find a
  95% confidence interval…
 Use Stat >> Basic Statistics >> 1 sample Z
      Make sure to click Options and set to 95%
 Click   your OK buttons…




                             Confidence Interval is
                             (64533, 65467), which
                             means we can be 95%
                             confident the true mean
                             cost of the competitor’s
                             vehicles are between
                             those two values.
 FindConfidence Intervals of Proportions
 Example
    An student wants to estimate what proportion of
     the student body eats on campus. The student
     randomly samples 200 students and finds 120 eat
     on campus. Using a 95% confidence
     interval, estimate the true proportion of
     students who eat on campus. Write a statement
     about the confidence level and interval.
   Example Solution
     p hat = 120/200 = 0.60
     q hat = 1- 0.60 = 0.40
     n p hat = 200 * 0.60 = 120
     n q hat = 200 * 0.40 = 80
     Using E = Zc* Square Root ((p hat * q hat)/n)
     = 1.96 * Square Root ((0.60*0.40)/200)
    =0.0679
    Now we subtract this from the mean for the left side of
      the interval and add it to the mean for the right side.
      (0.60 – 0.0679, 0.60 + 0.0679) = (0.5321, 0.6679)
    So with 95% confidence, we can say the population
      proportion of students who eat lunch on campus is
      (0.5321, 0.6679) or between 53.21% and 66.79%.
 Link   to charts will be posted at

    www.facebook.com/statcave


 PLEASENOTE THAT I WILL BE BACK HERE
 NEXT SUNDAY NIGHT FOR A BONUS LECTURE
 TO HELP YOU PREPARE FOR THE FINAL EXAM.

 ENTER IN THE WEEK 7 iConnect AREA JUST
 LIKE YOU DID TONIGHT.

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Week 7 lecture_math_221_apr_2012

  • 1. B. Heard (This material can not be copied or posted without the author’s consent. Students may download one copy for personal use.)
  • 2.  Standard Normal Distribution  The “standard” normal distribution is a normal distribution with mean zero and where the standard deviation (and variance) equals one.  The Total Area under the curve is one (1) or 100% (This is true for all normal distributions regardless of the mean and standard deviation).
  • 3.  Using Minitab for Normal Distribution calculations.  Use Calc >> Probability Distributions >> Normal  Examples Follow
  • 4.  Example  Theaverage fish in Happy Lake weighs 2 pounds with a standard deviation of 0.5 pounds. If Bob catches a fish that weighs 3.2 pounds. What could you say about the catch?
  • 5. Since this is the Cumulative Distribution Function, it “fills” from left to right. Therefore, you could say his catch was in the “Top 1 %”
  • 6.  Example  Theaverage fish in Happy Lake weighs 2 pounds with a standard deviation of 0.5 pounds. If Bob catches a fish that weighs 1.35 pounds. What could you say about the catch?
  • 7. Since this is the Cumulative Distribution Function, it “fills” from left to right. Therefore, you could say his catch was in the “Bottom 10 %”
  • 8.  Other types of questions  If you have a normal distribution with a mu = 100 and sigma = 15, what number corresponds to a z = -2 -2 = (x – 100)/15 Multiply both sides by 15 to get -30 = x – 100 Add 100 to each side to get 70 = x So “70” is my answer, I just did a little Algebra.
  • 9.  Another type of question  Say we take 120 samples of size 81 each from a distribution we know is normal. Calculate the standard deviation of the sample means if we know the population variance is 25.  (Answer next chart)
  • 10.  Answer  The Central Limit Theorem tells us the variance is the Population variance divided by the Sample Size. We can just take the square root to get the standard deviation. Variance = 25/81 or 0.309 Standard Deviation = Square Root(25/81) = 5/9 = 0.556
  • 11.  Findingz scores  Example  The area to the left of the “z” is 0.6262. What z score corresponds to this area.  Use Calc >> Probability Distributions >> Normal  (Set Mean = 0 and Standard Deviation to 1 and use “INVERSE Cumulative Probability”
  • 12. Answer is 0.322 rounded to three decimals. Remember the distribution fills from left to right.
  • 13.  Another type of question  In a normal distribution with mu = 40 and sigma = 10 find P(32 < x < 44)  Easy, but this takes a couple of steps.  Using Calc >> Probability Distributions >> Normal find the probabililties that x < 32 and x < 44 using the Cumulative Probability option.
  • 14.  Continued Get results for Both 32 and then 44.
  • 15.  Answer Subtract 0.655422 – 0.211855 To get 0.443567 Or 0.444 rounded to three decimals P(32 < x < 44) = 0.444 based on the given mean and std deviation.
  • 16.  Confidence Intervals and Examples  Charts follow
  • 17.  Interpreting Confidence Intervals  If you have a 90% confidence interval of (15.5, 23.7) for a population mean, it simply means “There is a 90% chance that the population mean is contained in the interval (15.5, 23.7)  It’s really that simple.
  • 18.  Finding Confidence Intervals  A luxury car company wants to estimate the true mean cost of its competitor’s automobiles. It randomly samples 180 of its competitors sticker prices. The mean cost is $65,000 with a standard deviation of $3200. Find a 95% confidence interval for the true mean cost of the competitor’s automobiles. Write a statement about the interval.
  • 19.  It randomly samples 180 of its competitors sticker prices. The mean cost is $65,000 with a standard deviation of $3200. Find a 95% confidence interval…  Use Stat >> Basic Statistics >> 1 sample Z  Make sure to click Options and set to 95%
  • 20.
  • 21.  Click your OK buttons… Confidence Interval is (64533, 65467), which means we can be 95% confident the true mean cost of the competitor’s vehicles are between those two values.
  • 22.  FindConfidence Intervals of Proportions  Example  An student wants to estimate what proportion of the student body eats on campus. The student randomly samples 200 students and finds 120 eat on campus. Using a 95% confidence interval, estimate the true proportion of students who eat on campus. Write a statement about the confidence level and interval.
  • 23. Example Solution  p hat = 120/200 = 0.60  q hat = 1- 0.60 = 0.40  n p hat = 200 * 0.60 = 120  n q hat = 200 * 0.40 = 80  Using E = Zc* Square Root ((p hat * q hat)/n) = 1.96 * Square Root ((0.60*0.40)/200) =0.0679 Now we subtract this from the mean for the left side of the interval and add it to the mean for the right side. (0.60 – 0.0679, 0.60 + 0.0679) = (0.5321, 0.6679) So with 95% confidence, we can say the population proportion of students who eat lunch on campus is (0.5321, 0.6679) or between 53.21% and 66.79%.
  • 24.  Link to charts will be posted at  www.facebook.com/statcave  PLEASENOTE THAT I WILL BE BACK HERE NEXT SUNDAY NIGHT FOR A BONUS LECTURE TO HELP YOU PREPARE FOR THE FINAL EXAM.  ENTER IN THE WEEK 7 iConnect AREA JUST LIKE YOU DID TONIGHT.