Open Query 19

#$&*

course mth 152

11/15 11:45

If your solution to stated problem does not match the given solution, you should self-critique per instructions at

http://vhcc2.vhcc.edu/dsmith/geninfo/labrynth_created_fall_05/levl1_22/levl2_81/file3_259.htm.

Your solution, attempt at solution.

If you are unable to attempt a solution, give a phrase-by-phrase interpretation of the problem along with a statement of what you do or do not understand about it. This response should be given, based on the work you did in completing the assignment, before you look at the given solution.

019. ``q Query 19

*********************************************

Question: `q Query problem 13.6.9 wt vs ht 62,120; 62,140; 63,130; 65,150; 66,142; 67,13068,175; 68,135; 70,149; 72,168. Give the regression equation and the predicted weight when height is 70.

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

a=10(95748)-(663)(1439)/10(44059)-(663)^2= 957480-954057/440590-439569= 3423/1021=3.35

b=1439-3.35(663)/10= 1439-2221.05/10= 785.05/10= 78.5

y=3.35x-78.5

If the height is 70 then:

y=3.35(70)-78.5= 234.5-78.5= 156

the predicted weight when the hieght is 70 is 156

confidence rating #$&*:

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.............................................

Given Solution:

`aThe equation is obtained by substituting the weights for y and the heights for x in the formula for the regression line.

You get

y = 3.35 x - 78.4.

To predict weight when height is 70 you plug x = 70 into the equation:

y = 3.35 * 70 - 78.4.

You get

y = 156,

so the predicted weight for a man 70 in tall is 156 lbs. **

&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&

Self-critique (if necessary):

------------------------------------------------

Self-critique Rating:

*********************************************

Question: `q Query problem 13.6.12 reading 83,76, 75, 85, 74, 90, 75, 78, 95, 80; IQ 120, 104, 98, 115, 87, 127, 90, 110, 134, 119

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

a=10(90437)-(811)(1104)/10(66225)-(811)^2= 904370-895344/662250-657721= 9026/4529= 1.99

b=1104-1.99(811)/10= 1104-1613.89/10= -50.98

y=1.99x-50.98

confidence rating #$&*:

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.............................................

Given Solution:

`a

n = 10

sum x = 811

sum x ^2 = 66225

sum y = 1104

sum y^2 = 124060

sum xy = 90437

a = [10(90437) - (811)(1104)] / [10(66225) - (811^2)] = 1.993

a = 1.99

b = [1104 - (1.993)(811) / 10 = -51.23

y' = 1.993x - 51.23 is the eqation of the regression line.

**

STUDENT QUESTION

How did you get sum x ^2 = 66225??? Is it not 811 * 811 = 657721?

How did you come up with sum y^2 = 124060??? Is it not 1104 * 1104 = 1218816?

I worked it out, can you tell me where I went wrong??? And I will try to rework the problem.

INSTRUCTOR RESPONSE

You didn't distinguish between sum x^2 and (sum x)^2.

Sum x^2 means you figure out x^2 for every value of x, then add them. Remember that exponentiation precedes addition.

(sum x)^2 means you add all the x values then square them.

The same comment applies to sum y^2 vs. (sum y)^2.

You didn't ask, but sum xy can also be confusing:

Sum xy means multiply each x value by the corresponding y value, then add the products. This is order of operations: multiplication before addition

&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&

Self-critique (if necessary):

------------------------------------------------

Self-critique Rating:

*********************************************

Question: `q Query problem 13.6.15 years 0-5, sales 48, 59, 66, 75, 80, 89

What is the coefficient of correlation and how did you obtain it?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

n=6 sets of data

Sum x = 15

sum y = 418

sum xy = 1186

sum x^2 = 55

sum y^2 = 30266

r=6(1186)-(15)(418)/sq root of 6(55-15^2 * sq rt of 6(30266)-418^2

7116-6270/ sq rt 330-225 * sq rt of 181596-174724=

846/sq rt of 105 * sq rt of 6872=

846/10.24*82.89= 846/848.76= .996

the coefficient of correlation is .996

confidence rating #$&*:

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.............................................

Given Solution:

`a **STUDENT SOLUTION:

X Y XY X^2 Y^2

0 48 0 0 2304

1 59 59 1 3481

2 66 132 4 4356

3 75 225 9 5626

4 80 320 16 6400

5 90 450 25 8100

Sums=

15 418 1186 55 30266

The coefficient of the correlation: r = .996

I found the sums of the following:

x = 15, y = 418, x*y = 1186, x^2 = 55

n = 6 because there are 6 pairs in the data

I also had to find Ey^2 = 30266

I used the following formula:

r = 6(1186) - 15(418) / sq.root of 6(55) - (15)^2 * sq. root of 6(30266) - (418)^2 =

846 / sq. root of 105 * 6872 = 846 / sq. root of 721560 = 846 / 849.4 = .996 **

&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&

Self-critique (if necessary):

------------------------------------------------

Self-critique Rating:

*********************************************

Question: `q Query problem 13.6.24 % in West, 1850-1990, .8% to 21.2%

What population is predicted in the year 2010 based on the regression line?

What is the equation of your regression line and how did you obtain it?

YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY

Your solution:

2010 is 16 decades from 1850 so x=16

n=8

sum x=56

sum y=77.7

sum xy=786.4

sum x^2=560

a=8(786.4)-(56)(77.7)/8(560)-56^2=

6291.2-4351.2/4480-3136=

1940/1344=1.44

a=1.44

B=77.7-1.44(56)/8=

77.7-80.64/8=

-2.94/8= -.367

B= -.367

y=1.44(16)-.367=

23.04-.367=22.67

22.67% in the West

confidence rating #$&*:

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.............................................

Given Solution:

`aSTUDENT SOLUTION:

Calculating sums and regression line:

n = 8

sum x = 56

sum x^2 = 560

sum = 77.7

sum y^2 = 1110.43

sum xy = 786.4

a = 1.44

b = -.39

r = .99

In the year 2010 the x value will be 16.

y' = 1.44(16) - .39 = 22.65.

There is an expected 22.65% increase in population by the year 2010. **

&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&

Self-critique (if necessary):

------------------------------------------------

Self-critique Rating:

"

Self-critique (if necessary):

------------------------------------------------

Self-critique rating:

"

Self-critique (if necessary):

------------------------------------------------

Self-critique rating:

#*&!