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The Normal Distribution Chapter 2

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The Normal Distribution. Chapter 2. Continuous Random Variable. A continuous random variable: Represented by a function/graph. Area under the curve represents the proportions of the observations Total area is exactly 1. - PowerPoint PPT Presentation

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Page 1: The Normal Distribution

The Normal Distribution

Chapter 2

Page 2: The Normal Distribution

Continuous Random Variable

• A continuous random variable:– Represented by a function/graph.– Area under the curve represents the proportions of

the observations– Total area is exactly 1.

• How do we locate the median for a continuous random variable? the mean?

• The median is the value that divides the graph into equal area while the mean is the “balance” point.

Page 3: The Normal Distribution

Continuous Random Variable 1

What percent of the observations lie below 0.4?

0.50.4

A= .4(1) =0.4

40%

Page 4: The Normal Distribution

Continuous Random Variable 2

What proportion of the observations lie above 0.6?

0.6

A= 1.4(.5) =0.7

Notice, to find proportion for observation above, we can use the complement rule.

Page 5: The Normal Distribution

Continuous Random Variable 3

• Where is the mean and median?• How will the curve change as changes?

Page 6: The Normal Distribution

Normal Distributions

• Symmetric, single-peaked, and mound-shaped distributions are called normal distributions

• Normal curves:– Mean = median– The mean and standard deviation completely

determine the shape

Page 7: The Normal Distribution

The Normal Curve

• Will finding proportions work different than previous random variable examples?

• Empirical Rule Discovery

Page 8: The Normal Distribution

68% of observations fall within 1 of

Page 9: The Normal Distribution

95% of observations fall within 2 of

Page 10: The Normal Distribution

99.7% of observations fall within 3 of

Page 12: The Normal Distribution

68-95-99.7 Rule

34% 34%

13.5%13.5%2.35% 2.35%.15%

Applet

Page 13: The Normal Distribution

Percentiles?

34% 34%

13.5%13.5%2.35% 2.35%

50th 84th 16th

Page 14: The Normal Distribution

What’s Normal in Statistics?

• Normal distributions are good descriptions for real data allowing measures of relative position to be easily calculated (i.e. percentiles)

• Much of statistical inference (in this course) procedures area based on normal distributions

• FYI: many distributions aren’t normal

Page 15: The Normal Distribution

Distribution of dates is approximately normal with mean 1243 and standard deviation of 36 years.

1243 1279 1315 135112071135 1171

Page 16: The Normal Distribution

Assume the heights of college women are normally distributed with a mean of 65 inches and standard deviation of 2.5 inches.

65 67.5 70 72.562.557.5 60

Page 17: The Normal Distribution

What percentage of women are taller than 65 in.?

65 67.5 70 72.562.557.5 60

50%

Page 18: The Normal Distribution

What percentage of women are shorter than 65 in.?

65 67.5 70 72.562.557.5 60

50%

Page 19: The Normal Distribution

What percentage of women are between 62.5 in. and 67.5 in.?

65 67.5 70 72.562.557.5 60

68%

Page 20: The Normal Distribution

What percentage of women are between 60 in. and 70 in.?

65 67.5 70 72.562.557.5 60

95%

Page 21: The Normal Distribution

What percentage of women are between 60 and 67.5 in?

65 67.5 70 72.562.557.5 60

68%

13.5%

81.5%

Page 22: The Normal Distribution

What percentage of women are shorter than 70 in.?

65 67.5 70 72.562.557.5 60

50%

34%

97.5% 13.5%

Page 23: The Normal Distribution

Iliana’s Grade

• After 5 weeks of class Iliana must transfer from a stat class at Lanier to this class. Last week was the chapter 1 test in both classes. Iliana scored a 61 out of 70. Let’s say our test was out of 100 points. What score should she be given?

Page 24: The Normal Distribution

Iliana’s claim

• Iliana claims that her test at Lanier was harder than our test.

• Does your previous method of assigning a grade take in consideration difficulty?

• If we have all of the data, what important facts can we utilize to improve our assignment of Iliana’s grade?

Page 25: The Normal Distribution

Important Facts

• Maximum possible on our test was 100 pts while Lanier’s test was 70 pts.

• Mean score on Lanier’s test was 50.5 pts while our test was 77.2 pts.

• Standard deviation on Lanier’s test was 5.3 pts while ours was 8.1 pts.

• Test scores from both high schools tend to be normally distributed.

• How will we fairly assign Iliana’s score?

Page 26: The Normal Distribution

Lanier’s distribution

50.5 55.8 61.1 66.4

Iliana

Page 27: The Normal Distribution

Lanier’s and McCallum’s distributions

50.5 55.8 61.1 66.4

Iliana

77.2 85.3 93.4 101.5

Iliana

•How can we find Iliana’s relative position?

Iliana’s score – class average standard deviation

Page 28: The Normal Distribution

Formula

• What is the formula to find the relative position for any distribution?

Iliana’s score – class average standard deviation

z–score=x

Page 29: The Normal Distribution

1. Suppose as student has taken two quizzes in a statistics course. On the first quiz the mean score was 32, the standard deviation was 8, and the student received a 44. The student obtained a 28 on the second quiz, for which the mean was 23 and the standard deviation was 3. If test scores are approximately normal, on which quiz did the student perform better relative to the rest of the class?

zx

First quiz: z 44 328 15.

Second quiz: z 28 233

1667.

Page 30: The Normal Distribution

Relative to their departments, which is better paid if the husband earns $14.60 and the wife earns $15.75?

z

14 60 12 80

12015

. ..

.Husband:

Wife: z

15 75 1350

180125

. ..

.

3. A married couple is employed by the same company. The husband works in a department for which the mean hourly rate is $12.80 and the standard deviation is $1.20. His wife is employed in a department where the mean rate is $13.50 and the standard deviation is $1.80.

Page 31: The Normal Distribution

z 15.93nd percentile

What percentile is the husband located in his department?

Page 32: The Normal Distribution

z 125. P z( . ) . . 125 1 8944 1056

What percent of employees in the wife’s department earn better than her?

Page 33: The Normal Distribution

What would the wife need to earn to match her husband’s relative position?

z

14 60 12 80

12015

. ..

.Husband:

Wife: z

15 75 1350

180125

. ..

.

x

1350180

15.

.. x 1350 2 7. .

x $16.20

The wife would need to earn $16.20 to match the husband’s relative position.

Page 34: The Normal Distribution

If the husband wanted to earn in the 95th percentile, how much should he earn per hour?

Need a z-score of 1.65!

Page 35: The Normal Distribution

z

14 60 12 80

12015

. ..

.

x 12 80120

..

165.

x 12 80 198. .

x $14.78

The husband will need to earn at least $14.78 to be in the 95th percentile.

Page 36: The Normal Distribution

2

– 2

14.24 .0228P x 59.60 .9772P x

14.24 59.60 .9772 .0228 .9544P x

Page 37: The Normal Distribution

89%

44.5%

5.5%

z-score = –1.60 z-score = 1.60

94.5%

36.921.60

11.32

x

36.921.60

11.32

x

The middle 89% of the data ranges from 18.81 to 55.03 ppb.

Page 38: The Normal Distribution

Warm Up Answer Check

• Probability of a president being 52 year old or younger is .3192.

• Probability of SAT math score less than 540 is .8907.

• Probability of Aprils having one or fewer frost days is .2389.

• Probability of hotdogs having over 500 mg of sodium is .2177.

.3488

.8627

.4

.2593

Page 39: The Normal Distribution

PREZ

Data is approximately normal.

Page 40: The Normal Distribution

SATM

Data is fairly normal.

Page 41: The Normal Distribution

FROST

Data is not normal.

Page 42: The Normal Distribution

HOTDG

Data is approximately normal.