Upcoming Schedule PSU Stat 2014 MondayTuesdayWednesdayThursdayFriday Jan 6 Sec 7.2 Jan 7Jan 8 Sec...

Upcoming SchedulePSU Stat 2014

Monday Tuesday Wednesday Thursday Friday

Jan 6Sec 7.2

Jan 7 Jan 8Sec 7.3

Jan 9 Jan 10Sec 7.4

Jan 13

Chapter 7 in a nutshell

Jan 14 Jan 15

Chapter 7 test

Jan 16 Jan 17

Final Review

MLK Jr DayNo School

Jan 21

Monday schedule

Final Review

Jan 22

Final Per 1-3

Jan 23

Final Per 4-6

Jan 24

Final Per 7,8

ReviewTerm SymbolSample standard deviation s

Population standard deviation s

Sample Variance s2

Population Variance s2

Bluman, Chapter 7 2

7-4 Confidence Intervals for Variances and Standard Deviations

When products that fit together (such as pipes) are manufactured, it is important to keep the variations of the diameters of the products as small as possible; otherwise, they will not fit together properly and will have to be scrapped.

In the manufacture of medicines, the variance and standard deviation of the medication in the pills play an important role in making sure patients receive the proper dosage.

For these reasons, confidence intervals for variances and standard deviations are necessary.

Bluman, Chapter 7 3

Chi-Square Distributions The chi-square distribution must be used to calculate

confidence intervals for variances and standard deviations.

The chi-square variable is similar to the t variable in that its distribution is a family of curves based on the number of degrees of freedom.

The symbol for chi-square is (Greek letter chi, pronounced “ki”).

A chi-square variable cannot be negative, and the distributions are skewed to the right.

Bluman, Chapter 7 4

2

Chi-Square Distributions

Bluman, Chapter 7 5

At about 100 degrees of freedom, the chi-square distribution becomes somewhat symmetric.

The area under each chi-square distribution is equal to 1.00, or 100%.

Formula for the Confidence Interval for a Variance; see page 388

Bluman, Chapter 7 6

2 22

2 2right left

1 1, d.f. = 1

n s n sn

Bluman, Chapter 7 7

2 2

2 2right left

1 1, d.f. = 1

n s n sn

Formula for the Confidence Interval for a Standard Deviation

Rounding Rule: Please refer to the bottom of page 388.

Chapter 7Confidence Intervals and Sample Size

Section 7-4Example 7-13

Page #387

Bluman, Chapter 7 8

Find the values for and for a 90% confidence interval when n = 25.

Example 7-13: Using Table G

Bluman, Chapter 7 9

To find , subtract 1 - 0.90 = 0.10. Divide by 2 to get 0.05.To find , subtract 1 - 0.05 to get 0.95.

2left2

right

2right2left

Use the 0.95 and 0.05 columns and the row corresponding to 24 d.f. in Table G.

Example 7-13: Using Table G

Bluman, Chapter 7 10

2 2right leftThe value is 36.415; the value is 13.848.

Using table G Generalized:

11

1) Calculate a which is the complement of the CL.2) chi square right: 3) chi square left: subtract the above value from 1

Rounding Rule

When you are computing a confidence interval for a population variance or standard deviation by using raw data, round off to one more decimal places than the number of decimal places in the original data.

When you are computing a confidence interval for a population variance or standard deviation by using a sample variance or standard deviation, round off to the same number of decimal places as given for the sample variance or standard deviation.

Confidence Interval for a Variance or Standard Deviation




Page #389


Find the 95% confidence interval for the variance and standard deviation of the nicotine content of cigarettes manufactured if a sample of 20 cigarettes has a standard deviation of 1.6 milligrams.

Example 7-14: Nicotine Content


To find , subtract 1 - 0.95 = 0.05. Divide by 2 to get 0.025.

To find , subtract 1 - 0.025 to get 0.975.

In Table G, the 0.025 and 0.975 columns with the d.f. 19 row yield values of 32.852 and 8.907, respectively.

2right

2left

Example 7-14: Nicotine Content


2 22

2 2right left

1 1

n s n s

21.5 5.5

1.5 5.5

1.2 2.3

You can be 95% confident that the true variance for the nicotine content is between 1.5 and 5.5 milligrams.

2 2

219 1.6 19 1.6

32.852 8.907

You can be 95% confident that the true standard deviation is between 1.2 and 2.3 milligrams.



Page #389


Find the 90% confidence interval for the variance and standard deviation for the price in dollars of an adult single-day ski lift ticket. The data represent a selected sample of nationwide ski resorts. Assume the variable is normally distributed.

59 54 53 52 51

39 49 46 49 48

Example 7-15: Cost of Ski Lift Tickets


Using technology, we find the variance of the data is approximately s2=28.2; however use the VARS key to use the exact value in the formula.

In Table G, the 0.05 and 0.95 columns with the d.f. 9 row yield values of 16.919 and 3.325, respectively.


19

2 22

2 2right left

1 1

n s n s

You can be 95% confident that the true variance for the cost of ski lift tickets is between 15.0 and 76.4.

29 28.2 9 28.2

16.919 3.325

15.0<𝜎2<76.4



You can be 95% confident that the true standard deviation is between $3.9 and $8.7.

15.0<𝜎2<76.4

To determine the interval for the standard deviation, don’t use the rounded answers of the variation. Use the exact values.

√15.0<𝜎<√76.4

3.9<𝜎<8.7

Homework

Sec 7.4 page 390 #5,8,9,11



Confidence Level

c2 leftColumn to use

c2 rigthColumn to use

90% 0.95 0.0595% 0.975 0.02598% 0.99 0.0199% 0.995 0.005

Upcoming Schedule PSU Stat 2014 MondayTuesdayWednesdayThursdayFriday Jan 6 Sec 7.2 Jan 7Jan 8 Sec...

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